@article {9998, title = {Taming artificial intelligence: A theory of control{\textendash}accountability alignment among AI developers and users}, journal = {Academy of Management Review}, year = {In Press}, abstract = {

The growing agency of artificial intelligence (AI) systems, more specifically systems based on machine learning, has raised concern about the security, safety, and ethical risks of AI use. We argue that core to mitigating AI risks is proper alignment of control and accountability for the stakeholders involved in AI development and use. Control enables and accountability motivates stakeholders to achieve desired and avoid undesired outcomes using AI. However, AI systems{\textquoteright} capabilities for autonomous adaptivity reduce control even for the experts who create them. Moreover, increasing interdependencies between AI development and use render it difficult to unambiguously locate control and accountability. In this paper, we address these challenges for mitigating AI risks by postulating decentralized forms of stakeholder governance and integrative negotiations among stakeholders during the AI life cycle as conducive to aligning control and accountability for AI development and use. Further, we specify that extensive information sharing aided by perspective taking and a shared norm of accountability facilitate integrative negotiation strategies. We conclude by discussing the implications of our theory for management scholarship on the impact of AI and identify promising avenues for future research at micro, meso, and macro levels of analysis.

}, keywords = {accountability, artificial intelligence, control, risk, stakeholder negotiation}, doi = {10.5465/amr.2023.0117}, author = {Gudela Grote and Sharon Parker and Kevin Crowston} } @proceedings {2025, title = {Deskilling and upskilling with AI systems}, year = {2025}, month = {3/2025}, abstract = {

Introduction. Deskilling is a long-standing prediction of the use of information technology, raised anew by the increased capabilities of AI (AI) systems. A review of studies of AI applications suggests that deskilling (or levelling of ability) is a common outcome but systems can also require new skills, i.e., upskilling.
Method. To identify which settings are more likely to yield deskilling vs. upskilling, we propose a model of a human interacting with an AI system for a task. The model highlights the possibility for a worker to develop and exhibit (or not) skills in prompting for, and evaluation and editing of system output, thus yielding upskilling or deskilling.
Findings. We illustrate these model-predicted effects on work with examples of current studies of AI-based systems.
Conclusions. We discuss organizational implications of systems that deskill or upskill workers and suggest future research directions.

}, attachments = {https://waim.network/sites/crowston.syr.edu/files/GenAI_and_skills__iConference_2025_\%20information\%20matters\%20fb.pdf}, author = {Kevin Crowston and Bolici, Francesco} } @unpublished {wang2025rolehumancreativitypresence, title = {The Role of Human Creativity in the Presence of AI Creativity Tools at Work: A Case Study on AI-Driven Content Transformation in Journalism}, year = {2025}, url = {https://arxiv.org/abs/2502.05347}, author = {Sitong Wang and Jocelyn McKinnon-Crowley and Tao Long and Kian Loong Lua and Keren Henderson and Kevin Crowston and Jeffrey V. Nickerson and Mark Hansen and Lydia B. Chilton} } @proceedings {9999, title = {The task matters: The effect of perceived similarity to AI on intention to use in different task types}, year = {2025}, month = {1/2025}, address = {Waikaloa, HI}, abstract = {

With the development of AI technologies, especially generative AI (GAI) like ChatGPT, GAI is increasingly assisting people in various tasks. However, people may have different requirements for GAI when using it for different kinds of tasks. For instance, when brainstorming new ideas, people may want GAI to propose different ideas that supplement theirs with different problem-solving perspectives, but for decision-making tasks, they may prefer GAI adopt a similar problem-solving process with people to make a similar or even the same decision as they would. We conducted an online experiment examining how perceived similarities between GAI and human task-solving influence people{\textquoteright}s intention to use GAI, mediated by trust, for four task types (creativity, planning, intellective, and decision-making tasks). We demonstrate that the effect of similarity on trust (and so intent to use AI) depends on the type of task. This paper contributes to understanding the impact of task types on the relationship between perceived similarity and GAI adoption, with implications for future use of GAI in various task contexts.

}, doi = {10.24251/HICSS.2025.042}, attachments = {https://waim.network/sites/crowston.syr.edu/files/AI_similarity.pdf}, author = {Qingyu Liang and Kevin Crowston and Sangseok You} } @article {2024, title = {Artificial Intelligence and the Future of Citizen Science}, journal = {Citizen Science: Theory and Practice}, volume = {9}, year = {2024}, month = {11/2024}, pages = {32}, doi = {10.5334/cstp.812}, author = {Fortson, Lucy and Crowston, Kevin and Kloetzer, Laure and Ponti, Marisa} } @article {9999, title = {Deskilling and upskilling with generative AI systems}, year = {2024}, abstract = {

Deskilling is a long-standing prediction of the use of information technology, raised anew by the increased capabilities of generative AI (GAI) systems. A review of studies of GAI applications suggests that deskilling (or levelling of ability) is a common outcome. We propose a model of a human interacting with a GAI system for a task that suggests settings more likely to yield deskilling vs. upskilling. The model highlights the possibility for a worker to develop and exhibit (or not) skills in prompting for, and evaluation and editing of system output. We illustrate these effects with examples of current studies of GAI-based systems. We discuss organizational implications of systems that deskill or upskill workers and suggest future research.

}, attachments = {https://waim.network/sites/crowston.syr.edu/files/GAI_and_skills.pdf}, author = {Kevin Crowston and Bolici, Francesco} } @article {2024, title = {Editorial: Sharing work with AI: introduction to the special issue on the futures of work in the age of intelligent machines}, journal = {Information Technology \& People}, volume = {37}, year = {2024}, month = {Mar-12-2024}, pages = {2353 - 2356}, issn = {0959-3845}, doi = {10.1108/ITP-12-2024-994}, url = {https://www.emerald.com/insight/content/doi/10.1108/ITP-12-2024-994/full/htmlhttps://www.emerald.com/insight/content/doi/10.1108/ITP-12-2024-994/full/htmlhttps://www.emerald.com/insight/content/doi/10.1108/ITP-12-2024-994/full/xml}, author = {Crowston, Kevin and Erickson, Ingrid and Nickerson, Jeffrey} } @article {9999, title = {Framing and feelings on social media: The futures of work and intelligent machines}, journal = {Information, Technology \& People}, year = {2024}, abstract = {Purpose: This study explores interpretations and feelings about futures of work and intelligent machines expressed on social media. Design/methodology/approach: We investigate public interpretations, assumptions and expectations expressed in social media conversations through which users freely share their most recent ideas. In addition to frames, this study also coded the emotions and attitudes expressed in the text data. More specifically, a corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments were analyzed by using computer-aided textual analysis comprising a BERTopic model, and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment. Finally, relationships among frames and attitudes and frames and emotions were examined. Findings: Twelve clusters were found that related to futures of work with intelligent machines. Based on the prior literature, two frames were chosen from these clusters and analyzed in detail: (1) general impacts of intelligent machines on wealth and society and (2) replacement of tasks (augmentation and substitution). The general attitude observed in conversations was positive, moreover the most common emotion category was approval. Findings also showed there are relationships between frames and attitudes and frames and emotions. Originality: This work extends the prior literature on a topic relevant for academia and industry. Findings of this research can help realize potential needs and benefits from the public{\textquoteright}s vantage point in the case of possible transformations in the future of work with intelligent machines. The findings may also help enlighten researchers to shape research directions about futures of work. Furthermore, firms, organizations or industries may also employ framing methods to receive customers{\textquoteright} or workers{\textquoteright} responses, or even to influence the responses. Aside from the empirical findings, another crucial implication of this work is application of theory of technological frames for systematizing the interpretations of how people conceptualize the future of work with the technology of intelligent machines. This study constitutes a bridge that connects fields of IS, computational science and empirical social research. }, doi = {10.1108/ITP-01-2023-0049}, attachments = {https://waim.network/sites/crowston.syr.edu/files/frames\%20to\%20share.pdf}, author = {Ay{\c s}e {\"O}cal and Kevin Crowston} } @article {9998, title = {Making sense of AI systems development}, journal = {IEEE Transactions on Software Engineering}, volume = {50}, year = {2024}, month = {12/2023}, pages = {123{\textendash}140}, abstract = {We identify and describe episodes of sensemaking around challenges in modern Artificial-Intelligence (AI)-based systems development that emerged in projects carried out by IBM and client companies. All projects used IBM Watson as the development platform for building tailored AI-based solutions to support workers or customers of the client companies. Yet, many of the projects turned out to be significantly more challenging than IBM and its clients had expected. The analysis reveals that project members struggled to establish reliable meanings about the technology, the project, context, and data to act upon. The project members report multiple aspects of the projects that they were not expecting to need to make sense of yet were problematic. Many issues bear upon the current-generation AI{\textquoteright}s inherent characteristics, such as dependency on large data sets and continuous improvement as more data becomes available. Those characteristics increase the complexity of the projects and call for balanced mindfulness to avoid unexpected problems.}, doi = {10.1109/TSE.2023.3338857}, attachments = {https://waim.network/sites/crowston.syr.edu/files/sensemaking_tse_to_share.pdf}, author = {Mateusz Dolata and Kevin Crowston} } @conference {osterlund2024, title = {Mutual learning in human-AI interaction}, booktitle = {Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference}, year = {2024}, address = {Honolulu, HI}, abstract = {

We explore the bi-directional relationship between human and machine learning in citizen science. Theoretically, the study draws on the Zone of Proximal Development concept, which allows us to describe the augmentation of human learning by AI, human augmentation of machine learning and how tasks can be designed to facilitate co-augmentation. Methodologically, the study utilizes a design-science approach to explore the design, deployment, and evaluations of the Gravity Spy citizen science project. The findings highlight the challenges and opportunities of co-augmentation, where both humans and machines contribute to each other{\textquoteright}s learning and capabilities.\  The research contributes to the existing literature by emphasizing the role of ZPD in citizen science projects, showcasing how the concept supports ongoing learning for volunteers and keeps machine learning aligned with evolving data.

}, attachments = {https://waim.network/sites/crowston.syr.edu/files/TREW_Workshop_Paper.pdf}, author = {{\O}sterlund, Carsten and Crowston, Kevin and Jackson, Casey B. and Takou-Ayaoh, Marlene and Wu, Yunan and Katsaggelos, Aggelos K.} } @conference {2024, title = {ReelFramer: Human-AI Co-Creation for News-to-Video Translation}, booktitle = {CHI {\textquoteright}24: CHI Conference on Human Factors in Computing SystemsProceedings of the CHI Conference on Human Factors in Computing Systems}, year = {2024}, pages = {1 - 20}, publisher = {ACM}, organization = {ACM}, address = {Honolulu HI USANew York, NY, USA}, isbn = {9798400703300}, doi = {10.1145/3613904.3642868}, author = {Wang, Sitong and Menon, Samia and Long, Tao and Henderson, Keren and Li, Dingzeyu and Crowston, Kevin and Hansen, Mark and Nickerson, Jeffrey V and Chilton, Lydia B}, editor = {Mueller, Florian Floyd and Kyburz, Penny and Williamson, Julie R. and Sas, Corina and Wilson, Max L. and Dugas, Phoebe Toups and Shklovski, Irina} } @article {9998, title = {Supporting and augmenting human and machine learning in citizen science: Lessons from Gravity Spy}, journal = {Citizen Science: Theory and Practice}, volume = {9}, year = {2024}, month = {11/2024}, pages = {42}, doi = {10.5334/cstp.738}, author = {Carsten {\O}sterlund and Kevin Crowston and Corey B. Jackson and Yunan Wu and Alexander O. Smith and Aggelos K. Katsaggelos} } @proceedings {petridis2023anglekindling, title = {AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models}, year = {2023}, doi = {10.1145/3544548.3580907}, url = {https://savvaspetridis.github.io/papers/anglekindling.pdf}, author = {Petridis, Savvas and Diakopoulos, Nicholas and Crowston, Kevin and Hansen, Mark and Henderson, Keren and Jastrzebski, Stan and Nickerson, Jefrey V and Chilton, Lydia B} } @article {9998, title = {Artificial intelligence in information systems: State of the art and research roadmap}, journal = {Communications of the Association for Information Systems (CAIS)}, volume = {50}, year = {2022}, abstract = {

Many would argue that artificial intelligence (AI) is not just a technology but represents a paradigmatic shift in the relationship between humans and machines. Much of the literature assumes that AI-powered practices are substantially different and profoundly changes organizational structures, communication, affordances, and ecosystems. However, research in AI is often fragmented and lacks clarity. While the Information Systems (IS) field can play a pivotal role in the emergence and use of AI, there is a need for a clear direction that specifies how IS can contribute and what are to be the key research themes and questions. This paper draws on a PDW at ICIS 2020 and the discussions that followed. It summarizes and synthesizes five decades of the impact of AI on organizational practices, providing views from various perspectives. It identifies weaknesses in the current AI literature as measured against conceptual clarity, theoretical glue, cumulative tradition, parsimony, and applicability. The paper concludes by identifying direct actions that the IS research community can undertake to address these issues. The final contribution is a next-step research agenda to guide AI research in the coming years.

}, doi = {10.17705/1CAIS.05017}, attachments = {https://waim.network/sites/crowston.syr.edu/files/Artificial\%20Intelligence\%20in\%20Information\%20Systems\%20State\%20of\%20the\%20Art.pdf}, author = {P{\"a}r J. {\r A}gerfalk and Kieran Conboy and Kevin Crowston and Sirkka L. Jarvenpaa and Jenny Eriksson Lundstr{\"o}m and Patrick Mikalef and Sudha Ram} } @conference {9999, title = {Project archetypes: A blessing and a curse for AI development}, booktitle = {International Conference on Information Systems (ICIS)}, year = {2022}, address = {Copenhagen, Denmark}, abstract = {

Software projects rely on what we propose to call project archetypes, i.e., pre-existing mental images of how projects work. They guide distribution of responsibilities, planning, or expectations. However, with the technological progress, project archetypes may become outdated, ineffective, or counterproductive by impeding more adequate approaches. Understanding archetypes of software development projects is core to leverage their potential. The development of applications using machine learning and artificial intelligence provides a context in which existing archetypes might outdate and need to be questioned, adapted, or replaced. We analyzed 36 interviews from 21 projects between IBM Watson and client companies and identified four project archetypes members initially used to understand the projects. We then derive a new project archetype, cognitive computing project, from the interviews. It can inform future development projects based on AI-development platforms. Project leaders should pro-actively manage project archetypes while researchers should investigate what guides initial understandings of software projects.

}, url = {https://aisel.aisnet.org/icis2022/is_design/is_design/6 }, attachments = {https://waim.network/sites/crowston.syr.edu/files/icis_archetypes_rev1_v20_zora.pdf}, author = {Mateusz Dolata and Kevin Crowston and Gerhard Schwabe} } @article {2021, title = {Hybrid intelligence in business networks}, journal = {Electronic Markets}, year = {2021}, month = {Nov-06-2021}, issn = {1019-6781}, doi = {10.1007/s12525-021-00481-4}, attachments = {https://waim.network/sites/crowston.syr.edu/files/Ebel2021_Article_HybridIntelligenceInBusinessNe.pdf}, author = {Ebel, Philipp and S{\"o}llner, Matthias and Leimeister, Jan Marco and Crowston, Kevin and de Vreede, Gert-Jan} } @article {Noonpakdee2020, title = {The Adoption of Artificial Intelligence for Financial Investment Service}, journal = {2020 22nd International Conference on Advanced Communication Technology (ICACT)}, year = {2020}, pages = {396{\textendash}400}, publisher = {Global IT Research Institute - GIRI}, keywords = {AI, artificial intelligence, data, financial, fintech, investment service, Technology Adoption, to investment companies, to offer customers accessibility}, isbn = {9791188428045}, author = {Noonpakdee, Wasinee} } @article {Sidaoui2020, title = {AI feel you: customer experience assessment via chatbot interviews}, journal = {Journal of Service Management}, year = {2020}, abstract = {Purpose: While customer experience (CE) is recognized as a critical determinant of business success, both academics and managers are yet to find a means to gain a comprehensive understanding of CE cost-effectively. The authors argue that the application of relevant AI technology could help address this challenge. Employing interactively prompted narrative storytelling, and the authors investigate the effectiveness of sentiment analysis (SA) on extracting valuable CE insights from primary qualitative data generated via chatbot interviews. Design/methodology/approach: Drawing on a granular and semantically clear framework for studying CE feelings, an artificial intelligence (AI) augmented chatbot was designed. The chatbot interviewed a crowdsourced sample of consumers about their recalled service experience feelings. By combining free-text and closed-ended questions, the authors were able to compare extracted sentiment polarities against established measurement scales and empirically validate our novel approach. Findings: The authors demonstrate that SA can effectively extract CE feelings from primary chatbot data. This findings also suggest that further enhancement in accuracy can be achieved via improvements in the interplay between the chatbot interviewer and SA extraction algorithms. Research limitations/implications: The proposed customer-centric approach can help service companies to study and better understand CE feelings in a cost-effective and scalable manner. The AI-augmented chatbots can also help companies to foster immersive and engaging relationships with customers. This study focuses on feelings, warranting further research on AI{\textquoteright}s value in studying other CE elements. Originality/value: The unique inquisitive role of AI-infused chatbots in conducting interviews and analyzing data in realtime, offers considerable potential for studying CE and other subjective constructs.}, keywords = {artificial intelligence, chatbot, Customer experience, Customer feelings, Sentiment analysis, Storytelling}, issn = {17575818}, doi = {10.1108/JOSM-11-2019-0341}, author = {Sidaoui, Karim and Jaakkola, Matti and Burton, Jamie} } @article {Kuziemski2020, title = {AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings}, journal = {Telecommunications Policy}, volume = {44}, number = {6}, year = {2020}, pages = {101976}, publisher = {Elsevier Ltd}, abstract = {The rush to understand new socio-economic contexts created by the wide adoption of AI is justified by its far-ranging consequences, spanning almost every walk of life. Yet, the public sector{\textquoteright}s predicament is a tragic double bind: its obligations to protect citizens from potential algorithmic harms are at odds with the temptation to increase its own efficiency - or in other words - to govern algorithms, while governing by algorithms. Whether such dual role is even possible, has been a matter of debate, the challenge stemming from algorithms{\textquoteright} intrinsic properties, that make them distinct from other digital solutions, long embraced by the governments, create externalities that rule-based programming lacks. As the pressures to deploy automated decision making systems in the public sector become prevalent, this paper aims to examine how the use of AI in the public sector in relation to existing data governance regimes and national regulatory practices can be intensifying existing power asymmetries. To this end, investigating the legal and policy instruments associated with the use of AI for strenghtening the immigration process control system in Canada; {\textquotedblleft}optimising{\textquotedblright} the employment services{\textquotedblright} in Poland, and personalising the digital service experience in Finland, the paper advocates for the need of a common framework to evaluate the potential impact of the use of AI in the public sector. In this regard, it discusses the specific effects of automated decision support systems on public services and the growing expectations for governments to play a more prevalent role in the digital society and to ensure that the potential of technology is harnessed, while negative effects are controlled and possibly avoided. This is of particular importance in light of the current COVID-19 emergency crisis where AI and the underpinning regulatory framework of data ecosystems, have become crucial policy issues as more and more innovations are based on large scale data collections from digital devices, and the real-time accessibility of information and services, contact and relationships between institutions and citizens could strengthen {\textendash} or undermine - trust in governance systems and democracy.}, keywords = {Algorithmic accountability, artificial intelligence, Automated decision making, Public sector innovation}, issn = {03085961}, doi = {10.1016/j.telpol.2020.101976}, url = {https://doi.org/10.1016/j.telpol.2020.101976}, author = {Kuziemski, Maciej and Misuraca, Gianluca} } @article {Dogru2020, title = {AI in operations management: applications, challenges and opportunities}, journal = {Journal of Data, Information and Management}, volume = {2}, number = {2}, year = {2020}, pages = {67{\textendash}74}, publisher = {Journal of Data, Information and Management}, abstract = {We have witnessed unparalleled progress in artificial intelligence (AI) and machine learning (ML) applications in the last two decades. The AI technologies have accelerated advancements in robotics and automation, which have significant implications on almost every aspect of businesses, and especially supply chain operations. Supply chains have widely adopted smart technologies that enable real-time automated data collection, analysis, and prediction. In this study, we review recent applications of AI in operations management (OM) and supply chain management (SCM). Specifically, we consider the innovations in healthcare, manufacturing, and retail operations, since collectively, these three areas represent a majority of the AI innovations in business as well as growing problem areas. We discuss primary challenges and opportunities for utilizing AI in those industries. We also discuss trending research topics with significant value potential in these areas.}, keywords = {AI, artificial intelligence, Artificial Intelligence (AI), automation, machine learning, machine learning (ML), ml, om, operations management, Operations Management (OM), Robotics, scm, supply chain management, Supply Chain Management (SCM)}, issn = {2524-6356}, doi = {10.1007/s42488-020-00023-1}, author = {Dogru, Ali K and Keskin, Burcu B} } @article {Black2020, title = {AI-enabled recruiting: What is it and how should a manager use it?}, journal = {Business Horizons}, volume = {63}, number = {2}, year = {2020}, pages = {215{\textendash}226}, publisher = {Elsevier Ltd}, abstract = {AI-enabled recruiting systems have evolved from nice to talk about to necessary to utilize. In this article, we outline the reasons underlying this development. First, as competitive advantages have shifted from tangible to intangible assets, human capital has transitioned from supporting cast to a starring role. Second, as digitalization has redesigned both the business and social landscapes, digital recruiting of human capital has moved from the periphery to center stage. Third, recent and near-future advances in AI-enabled recruiting have improved recruiting efficiency to the point that managers ignore them or procrastinate their utilization at their own peril. In addition to explaining the forces that have pushed AI-enabled recruiting systems from nice to necessary, we outline the key strategic steps managers need to take in order to capture its main benefits.}, keywords = {AI-enabled recruiting, artificial intelligence, Digital recruiting technology, Human resources}, issn = {00076813}, doi = {10.1016/j.bushor.2019.12.001}, url = {https://doi.org/10.1016/j.bushor.2019.12.001}, author = {Black, J Stewart and van Esch, Patrick} } @conference {2020, title = {Algorithmic Journalism and Its Impacts on Work}, booktitle = {Computation + Journalism Symposium }, year = {2020}, edition = {(cancelled due to COVID; presented in 2021)}, abstract = {

In the artificial intelligence era, algorithmic journalists can produce news reports in natural language from structured data thanks to natural language generation (NLG) algorithms. This paper presents several algorithmic content generation models and discusses the impacts of algorithmic journalism on work within a framework consisting of three levels: replacing tasks of journalists, increasing efficiency, and developing new capabilities within journalism. The findings indicate that algorithmic journalism technology may lead some changes in journalism by enabling individual users to produce their own stories. This paper may contribute to an understanding of how algorithmic news is created and how algorithmic journalism technology impacts work.

}, url = {https://cpb-us-w2.wpmucdn.com/express.northeastern.edu/dist/d/53/files/2020/02/CJ_2020_paper_26.pdf}, attachments = {https://waim.network/sites/crowston.syr.edu/files/CJ_2020_paper_26.pdf}, author = {Ayse Dalgali and Kevin Crowston} } @article {2020, title = {Algorithms at work: The new contested terrain of control}, journal = {Academy of Management Annals}, volume = {14}, year = {2020}, month = {Jan-01-2020}, pages = {366 - 410}, issn = {1941-6520}, doi = {10.5465/annals.2018.0174}, author = {Kellogg, Katherine C. and Valentine, Melissa A. and Christin, Ang{\'e}le} } @article {Gentili2020, title = {Are machines stealing our jobs?}, journal = {Cambridge Journal of Regions, Economy and Society}, volume = {13}, number = {1}, year = {2020}, pages = {153{\textendash}173}, abstract = {This study aims to contribute empirical evidence to the debate about the future of work in an increasingly robotised world. We implement a data-driven approach to study the technological transition in six leading Organisation for Economic Co-operation and Development (OECD) countries. First, we perform a cross-country and cross-sector cluster analysis based on the OECD-STAN database. Second, using the International Federation of Robotics database, we bridge these results with those regarding the sectoral density of robots. We show that the process of robotisation is industry- and country-sensitive. In the future, participants in the political and academic debate may be split into optimists and pessimists regarding the future of human labour; however, the two stances may not be contradictory.}, keywords = {cluster analysis, e24, e66, j24, jel classifications, labour dislocation, robotisation}, issn = {1752-1378}, doi = {10.1093/cjres/rsz025}, author = {Gentili, Andrea and Compagnucci, Fabiano and Gallegati, Mauro and Valentini, Enzo} } @book {2020, title = {Artificial Intelligence and Judicial Modernization}, year = {2020}, publisher = {Springer Singapore}, organization = {Springer Singapore}, address = {Singapore}, isbn = {978-981-32-9879-8}, doi = {10.1007/978-981-32-9880-4}, author = {Cui, Yadong} } @article {2020, title = {Artificial intelligence and the world of work, a co-constitutive relationship}, journal = {Journal of the Association for Information Science and Technology}, year = {2020}, abstract = {

The use of intelligent machines{\textemdash}digital technologies that feature data- driven forms of customization, learning, and autonomous action{\textemdash}is rapidly growing and will continue to impact many industries and domains. This is consequential for communities of researchers, educators, and practitioners concerned with studying, supporting, and educating information profes- sionals. In the face of new developments in artificial intelligence (AI), the research community faces 3 questions: (a) How is AI becoming part of the world of work? (b) How is the world of work becoming part of AI? and (c) How can the information community help address this topic of Work in the Age of Intelligent Machines (WAIM)? This opinion piece considers these 3 questions by drawing on discussion from an engaging 2019 iConference workshop organized by the NSF supported WAIM research coordination net- work (note: https://waim.network).

}, issn = {2330-1635}, doi = {10.1002/asi.24388}, author = {{\O}sterlund, Carsten and Jarrahi, Mohammad Hossein and Willis, Matthew and Boyd, Karen and Wolf, Christine} } @conference {Sushina2020, title = {Artificial Intelligence in the Criminal Justice System: Leading Trends and Possibilities}, booktitle = {Proceedings of the 6th International Conference on Social, economic, and academic leadership (ICSEAL-6-2019)}, volume = {441}, year = {2020}, pages = {432{\textendash}437}, publisher = {Atlantis Press}, organization = {Atlantis Press}, address = {Paris, France}, keywords = {artificial intelligence, criminal justice system, digital technologies, Leadership}, isbn = {978-94-6252-974-8}, doi = {10.2991/assehr.k.200526.062}, url = {https://www.atlantis-press.com/article/125940991}, author = {Sushina, Tatyana and Sobenin, Andrew} } @conference {Dietzmann2020, title = {Assessing the Business Impact of Artificial Intelligence}, booktitle = {Proceedings of the 53rd Hawaii International Conference on System Sciences}, volume = {3}, year = {2020}, pages = {5170{\textendash}5179}, abstract = {El autor propone la creaci{\'o}n de una agencia que certificque los procesos de IA. El no certificado RCO. Tambien habla de las caracter{\'\i}sticas de la IA y la dificutlad para regularlas. Sustenta cual debe ser el ente encargado de regular la IA. Tiene en cuenta la historia de la IA y su evaluci{\'o}n en el mercado.}, isbn = {9780998133133}, doi = {10.24251/hicss.2020.635}, author = {Dietzmann, Christian and Alt, Rainer} } @article {Bessen2020, title = {Automation: A Guide for Policymakers}, year = {2020}, institution = {Brookings Institute}, abstract = {

\ldots evidence that automation is causing mass unemployment, perhaps things are about to change. Some people, such as Martin Ford (2015), argue that {\textquotedblleft}this time is different.{\textquotedblright} Perhaps the rate of technological change is much more rapid with new artificial intelligence technologies \ldots

}, url = {https://www.brookings.edu/research/automation-a-guide-for-policymakers/}, author = {Bessen, James and Goos, Maarten and Salomons, Anna and van den Berge, Wiljan} } @booklet {Jha2020, title = {Automation and Radiology{\textemdash}Part 1}, howpublished = {Academic Radiology}, volume = {27}, number = {1}, year = {2020}, pages = {147{\textendash}149}, publisher = {Elsevier Inc.}, issn = {18784046}, doi = {10.1016/j.acra.2019.10.026}, url = {https://doi.org/10.1016/j.acra.2019.10.026}, author = {Jha, Saurabh} } @booklet {Cebreros2020, title = {Automation Technologies and Employment at Risk : The Case of Mexico}, year = {2020}, publisher = {Banco de M{\'e}xico}, author = {Cebreros, Alfonso and Heffner-Rodr{\'\i}guez, Aldo and Livas, Ren{\'e} and Puggioni, Daniela} } @article {Johnson2020, title = {The benefits of eHRM and AI for talent acquisition}, journal = {Journal of Tourism Futures}, year = {2020}, abstract = {Purpose : The hospitality and tourism industry faces a number of workforce challenges, especially the high turnover rates and associated replacement costs associated with continually identifying and hiring new employees. The purpose of this paper is to discuss how hospitality and tourism organizations can use electronic human resource management (eHRM) and artificial intelligence (AI) to help recruit and select qualified employees, increase individual retention rates and decrease the time needed to replace employees. Specifically, it discusses how e-recruiting and e-selection and AI tools can help hospitality and tourism organizations improve recruiting and selection outcomes. Design/methodology/approach: Research on eHRM, AI, employee recruitment and employee selection are applied to the hospitality and tourism industry and insights for how eHRM and AI can be applied to the industry are discussed. Findings: eHRM and AI have the potential to transform how the hospitality and tourism industry recruit and select employees. However, care must be taken to ensure that the insights gained and the decisions made are well received by employees and lead to better employee and organizational outcomes. Research limitations/implications: This paper represents the first research that integrates research from eHRM and AI and applies it to the hospitality and tourism industry. Originality/value: This paper represents the first research that integrates research from eHRM and AI and applies it to the hospitality and tourism industry.}, keywords = {artificial intelligence, e-HRM, e-recruiting, e-selection, eHRM, Electronic human resource management, Employee selection, Recruitment, Selection}, issn = {2055592X}, doi = {10.1108/JTF-02-2020-0013}, author = {Johnson, Richard D and Stone, Dianna L and Lukaszewski, Kimberly M} } @article {Roccetti2020, title = {A Cautionary Tale for Machine Learning Design: why we Still Need Human-Assisted Big Data Analysis}, journal = {Mobile Networks and Applications}, volume = {25}, number = {3}, year = {2020}, pages = {1075{\textendash}1083}, publisher = {Mobile Networks and Applications}, abstract = {Supervised Machine Learning (ML) requires that smart algorithms scrutinize a very large number of labeled samples before they can make right predictions. And this is not always true either. In our experience, in fact, a neural network trained with a huge database comprised of over fifteen million water meter readings had essentially failed to predict when a meter would malfunction/need disassembly based on a history of water consumption measurements. With a second step, we developed a methodology, based on the enforcement of a specialized data semantics, that allowed us to extract only those samples for training that were not noised by data impurities. With this methodology, we re-trained the neural network up to a prediction accuracy of over 80\%. Yet, we simultaneously realized that the new training dataset was significantly different from the initial one in statistical terms, and much smaller, as well. We had reached a sort of paradox: We had alleviated the initial problem with a better interpretable model, but we had changed the replicated form of the initial data. To reconcile that paradox, we further enhanced our data semantics with the contribution of field experts. This has finally led to the extrapolation of a training dataset truly representative of regular/defective water meters and able to describe the underlying statistical phenomenon, while still providing an excellent prediction accuracy of the resulting classifier. At the end of this path, the lesson we have learnt is that a human-in-the-loop approach may significantly help to clean and re-organize noised datasets for an empowered ML design experience.}, keywords = {Human-in-the-loop methods, Human-machine-Bigdata interaction loop, Machine learning design, Smart data, Water metering and consumption}, issn = {15728153}, doi = {10.1007/s11036-020-01530-6}, author = {Roccetti, Marco and Delnevo, Giovanni and Casini, Luca and Salomoni, Paola} } @article {Kassens-Noor2020, title = {Cities of the Future? The Potential Impact of Artificial Intelligence}, journal = {AI}, volume = {1}, number = {2}, year = {2020}, pages = {192{\textendash}197}, abstract = {Artificial intelligence (AI), like many revolutionary technologies in human history, will have a profound impact on societies. From this viewpoint, we analyze the combined effects of AI to raise important questions about the future form and function of cities. Combining knowledge from computer science, urban planning, and economics while reflecting on academic and business perspectives, we propose that the future of cities is far from being a determined one and cities may evolve into ghost towns if the deployment of AI is not carefully controlled. This viewpoint presents a fundamentally different argument, because it expresses a real concern over the future of cities in contrast to the many publications who exclusively assume city populations will increase predicated on the neoliberal urban growth paradigm that has for centuries attracted humans to cities in search of work.}, keywords = {artificial intelligence, autonomous vehicle, future, smart cities, work}, issn = {2673-2688}, doi = {10.3390/ai1020012}, author = {Kassens-Noor, Eva and Hintze, Arend} } @article {Acemoglu2020, title = {Competing with Robots: Firm-Level Evidence from France}, journal = {AEA Papers and Proceedings}, volume = {110}, year = {2020}, pages = {383{\textendash}388}, abstract = {We study the firm-level implications of robot adoption in France. Of 55,390 firms in our sample, 598 adopted robots between 2010 and 2015, but these firms accounted for 20 percent of manufacturing employment. Adopters experienced significant declines in labor shares, the share of production workers in employment, and increases in value added and productivity. They expand their overall employment as well. However, this expansion comes at the expense of competitors, leading to an overall negative association between adoption and employment. Robot adoption has a large impact on the labor share because adopters are larger and grow faster than their competitors.}, keywords = {automation, competition, j23, j24, jel codes, l11, labor share, manufacturing, productivity, reallocation, robots, tasks}, issn = {2574-0768}, doi = {10.1257/pandp.20201003}, author = {Acemoglu, Daron and Lelarge, Claire and Restrepo, Pascual} } @conference {Gerber2020, title = {Conceptualization of the Human-Machine Symbiosis {\textendash} A Literature Review}, booktitle = {Proceedings of the 53rd Hawaii International Conference on System Sciences}, volume = {3}, year = {2020}, pages = {289{\textendash}298}, abstract = {The vision of a symbiotic partnership between humans and machines has existed since the 1960s. With this paper we provide the first conceptualization of the human-machine symbiosis (HMS) and make three important contributions: we present the fundamentals of HMS by focusing on objectives, requirements, and boundaries; we propose a framework for the design of HMS; and we review HMS research and, specifically, what the literature says with respect to whether HMS has already been achieved.}, isbn = {9780998133133}, doi = {10.24251/hicss.2020.036}, author = {Gerber, Alina and Derckx, Patrick and D{\"o}ppner, Daniel A and Schoder, Detlef} } @article {Zavrsnik2020, title = {Criminal justice, artificial intelligence systems, and human rights}, journal = {ERA Forum}, volume = {20}, number = {4}, year = {2020}, pages = {567{\textendash}583}, publisher = {The Author(s)}, abstract = {The automation brought about by big data analytics, machine learning and artificial intelligence systems challenges us to reconsider fundamental questions of criminal justice. The article outlines the automation which has taken place in the criminal justice domain and answers the question of what is being automated and who is being replaced thereby. It then analyses encounters between artificial intelligence systems and the law, by considering case law and by analysing some of the human rights affected. The article concludes by offering some thoughts on proposed solutions for remedying the risks posed by artificial intelligence systems in the criminal justice domain.}, keywords = {Algorithms, artificial intelligence, automation, Criminal justice, Fair trial, Human rights}, isbn = {1202702000602}, issn = {18639038}, doi = {10.1007/s12027-020-00602-0}, url = {http://dx.doi.org/10.1007/s12027-020-00602-0}, author = {Zavr{\v s}nik, Ale{\v s}} } @conference {Martnez-Plumed2020, title = {Does AI qualify for the job? A bidirectional model mapping labour and AI intensities}, booktitle = {AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society}, year = {2020}, pages = {94{\textendash}100}, abstract = {In this paper we present a setting for examining the relation between the distribution of research intensity in AI research and the relevance for a range of work tasks (and occupations) in current and simulated scenarios. We perform a mapping between labour and AI using a set of cognitive abilities as an intermediate layer. This setting favours a two-way interpretation to analyse (1) what impact current or simulated AI research activity has or would have on labour-related tasks and occupations, and (2) what areas of AI research activity would be responsible for a desired or undesired effect on specific labour tasks and occupations. Concretely, in our analysis we map 59 generic labour-related tasks from several worker surveys and databases to 14 cognitive abilities from the cognitive science literature, and these to a comprehensive list of 328 AI benchmarks used to evaluate progress in AI techniques. We provide this model and its implementation as a tool for simulations. We also show the effectiveness of our setting with some illustrative examples.}, keywords = {AI benchmarks, AI impact, AI intensity, Labour market, Simulation, tasks}, isbn = {9781450371100}, doi = {10.1145/3375627.3375831}, author = {Mart{\textquoteright}nez-Plumed, Fernando and Tolan, Song{\textquoteright}l and Pesole, Annarosa and Hern{\textquoteright}ndez-Orallo, Jos{\'e} and Fern{\textquoteright}ndez-Mac{\textquoteright}as, Enrique and G{\textquoteright}mez, Emilia} } @article {Bansal2020, title = {Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance}, year = {2020}, abstract = {

Increasingly, organizations are pairing humans with AI systems to improve decision-making and reducing costs. Proponents of human-centered AI argue that team performance can even further improve when the AI model explains its recommendations. However, a careful analysis of existing literature reveals that prior studies observed improvements due to explanations only when the AI, alone, outperformed both the human and the best human-AI team. This raises an important question: can explanations lead to complementary performance, i.e., with accuracy higher than both the human and the AI working alone? We address this question by devising comprehensive studies on human-AI teaming, where participants solve a task with help from an AI system without explanations and from one with varying types of AI explanation support. We carefully controlled to ensure comparable human and AI accuracy across experiments on three NLP datasets (two for sentiment analysis and one for question answering). While we found complementary improvements from AI augmentation, they were not increased by state-of-the-art explanations compared to simpler strategies, such as displaying the AI{\textquoteright}s confidence. We show that explanations increase the chance that humans will accept the AI{\textquoteright}s recommendation regardless of whether the AI is correct. While this clarifies the gains in team performance from explanations in prior work, it poses new challenges for human-centered AI: how can we best design systems to produce complementary performance? Can we develop explanatory approaches that help humans decide whether and when to trust AI input?

}, url = {http://arxiv.org/abs/2006.14779}, author = {Bansal, Gagan and Wu, Tongshuang and Zhou, Joyce and Fok, Raymond and Nushi, Besmira and Kamar, Ece and Ribeiro, Marco Tulio and Weld, Daniel S.} } @article {Huang2020, title = {Engaged to a Robot? The Role of AI in Service}, journal = {Journal of Service Research}, year = {2020}, abstract = {This article develops a strategic framework for using artificial intelligence (AI) to engage customers for different service benefits. This framework lays out guidelines of how to use different AIs to engage customers based on considerations of nature of service task, service offering, service strategy, and service process. AI develops from mechanical, to thinking, and to feeling. As AI advances to a higher intelligence level, more human service employees and human intelligence (HI) at the intelligence levels lower than that level should be used less. Thus, at the current level of AI development, mechanical service should be performed mostly by mechanical AI, thinking service by both thinking AI and HI, and feeling service mostly by HI. Mechanical AI should be used for standardization when service is routine and transactional, for cost leadership, and mostly at the service delivery stage. Thinking AI should be used for personalization when service is data-rich and utilitarian, for quality leadership, and mostly at the service creation stage. Feeling AI should be used for relationalization when service is relational and high touch, for relationship leadership, and mostly at the service interaction stage. We illustrate various AI applications for the three major AI benefits, providing managerial guidelines for service providers to leverage the advantages of AI as well as future research implications for service researchers to investigate AI in service from modeling, consumer, and policy perspectives.}, keywords = {artificial intelligence, augmentation, automation, engagement, feeling AI, human intelligence, mechanical AI, personalization, relationalization, replacement, robots, service process, service strategy, standardization, thinking AI}, issn = {15527379}, doi = {10.1177/1094670520902266}, author = {Huang, Ming Hui and Rust, Roland T} } @article {GomezdeAgreda2020, title = {Ethics of autonomous weapons systems and its applicability to any AI systems}, journal = {Telecommunications Policy}, volume = {5}, number = {5}, year = {2020}, pages = {101953}, publisher = {Elsevier Ltd}, abstract = {Most artificial intelligence technologies are dual-use. They are incorporated into both peaceful civilian applications and military weapons systems. Most of the existing codes of conduct and ethical principles on artificial intelligence address the former while largely ignoring the latter. But when these technologies are used to power systems specifically designed to cause harm, the question must be asked as to whether the ethics applied to military autonomous systems should also be taken into account for all artificial intelligence technologies susceptible of being used for those purposes. However, while a freeze in investigations is neither possible nor desirable, neither is the maintenance of the current status quo. Comparison between general-purpose ethical codes and military ones concludes that most ethical principles apply to human use of artificial intelligence systems as long as two characteristics are met: that the way algorithms work is understood and that humans retain enough control. In this way, human agency is fully preserved and moral responsibility is retained independently of the potential dual-use of artificial intelligence technology.}, keywords = {AI ethics, Autonomous weapons, CCW, Dual-use AI, Explainability, Meaningful human control}, issn = {03085961}, doi = {10.1016/j.telpol.2020.101953}, url = {https://doi.org/10.1016/j.telpol.2020.101953}, author = {G{\'o}mez de {\'A}greda, {\'A}ngel} } @article {Hacker2020, title = {Explainable AI under contract and tort law: legal incentives and technical challenges}, journal = {Artificial Intelligence and Law}, number = {0123456789}, year = {2020}, publisher = {Springer Netherlands}, abstract = {This paper shows that the law, in subtle ways, may set hitherto unrecognized incentives for the adoption of explainable machine learning applications. In doing so, we make two novel contributions. First, on the legal side, we show that to avoid liability, professional actors, such as doctors and managers, may soon be legally compelled to use explainable ML models. We argue that the importance of explainability reaches far beyond data protection law, and crucially influences questions of contractual and tort liability for the use of ML models. To this effect, we conduct two legal case studies, in medical and corporate merger applications of ML. As a second contribution, we discuss the (legally required) trade-off between accuracy and explainability and demonstrate the effect in a technical case study in the context of spam classification.}, keywords = {Contract law, Corporate takeovers, Explainability, Explainability-accuracy trade-off, Explainable AI, Interpretable machine learning, Medical malpractice, Tort law}, isbn = {0123456789}, issn = {15728382}, doi = {10.1007/s10506-020-09260-6}, url = {https://doi.org/10.1007/s10506-020-09260-6}, author = {Hacker, Philipp and Krestel, Ralf and Grundmann, Stefan and Naumann, Felix} } @proceedings {2020, title = {Factors Influencing Approval of Wikipedia Bots}, year = {2020}, address = {Wailea, HI}, abstract = {

Before a Wikipedia bot is allowed to edit, the operator of the bot must get approval. The Bot Approvals Group (BAG), a committee of Wikipedia bot developers, users and editors, discusses each bot request to reach consensus regarding approval or denial. We examine factors related to approval of a bot by analyzing 100 bots{\textquoteright} project pages. The results suggest that usefulness, value-based decision making and the bot{\textquoteright}s status (e.g., automatic or manual) are related to approval. This study may contribute to understanding decision making regarding the human-automation boundary and may lead to developing more efficient bots.

}, doi = {10.24251/HICSS.2020.018}, attachments = {https://waim.network/sites/crowston.syr.edu/files/HICSS_WikipediaPaper_3.9.new\%20kc\%20\%282\%29.pdf}, author = {Ayse Dalgali and Kevin Crowston} } @article {Reid-musson2020, title = {Feminist economic geography and the future of work}, journal = {EPA: Economy and Space}, year = {2020}, pages = {1{\textendash}12}, keywords = {corresponding author, department of geography, emily reid-musson, feminist economic geography, memorial university of newfoundland, newfoundland and labrador a1c, social reproduction, subjectivity, technology, work}, doi = {10.1177/0308518X20947101}, author = {Reid-musson, Emily and Cockayne, Daniel and Frederiksen, Lia and Worth, Nancy} } @booklet {Suran2020, title = {Frameworks for collective intelligence: A systematic literature review}, howpublished = {ACM Computing Surveys}, volume = {53}, number = {1}, year = {2020}, pages = {1{\textendash}36}, abstract = {Over the last few years, Collective Intelligence (CI) platforms have become a vital resource for learning, problem solving, decision-making, and predictions. This rising interest in the topic has to led to the development of several models and frameworks available in published literature. Unfortunately, most of these models are built around domain-specific requirements, i.e., they are often based on the intuitions of their domain experts and developers. This has created a gap in our knowledge in the theoretical foundations of CI systems and models, in general. In this article, we attempt to fill this gap by conducting a systematic review of CI models and frameworks, identified from a collection of 9,418 scholarly articles published since 2000. Eventually, we contribute by aggregating the available knowledge from 12 CI models into one novel framework and present a generic model that describes CI systems irrespective of their domains. We add to the previously available CI models by providing a more granular view of how different components of CI systems interact. We evaluate the proposed model by examining it with respect to six popular, ongoing CI initiatives available on the Web.}, keywords = {collective intelligence, Crowdsourcing, Human computer interaction, Systematic literature review, Web 2.0, Wisdom of crowds}, issn = {15577341}, doi = {10.1145/3368986}, author = {Suran, Shweta and Pattanaik, Vishwajeet and Draheim, Dirk} } @article {Abeliansky2020, title = {The Future of Work: Challenges for Job Creation Due to Global Demographic Change and Automation}, journal = {IZA Discussion Paper Series}, number = {12962}, year = {2020}, keywords = {demography, labor, unemployment}, url = {www.iza.org}, author = {Abeliansky, Ana and Algur, Eda and Bloom, David E and Prettner, Klaus} } @article {EganadelSol2020, title = {The Future of Work in Developing Economies}, journal = {MIT Sloan Management Review}, volume = {61}, number = {2}, year = {2020}, pages = {1{\textendash}3}, abstract = {

Much has been written about the rise of automation in developed countries. Economists have been busily creating models seeking to quantify the likely impact of automation on employment. However, far less has been written about the potential effects on work in developing nations. This is surprising, given that automation may be especially troublesome for developing economies. Here, del Sol and Joyce examine the effects of large-scale automation on workers in developing countries.

}, keywords = {Armenia, Asia, Austria, automation, Bolivia, Business And Economics{\textendash}Management, China, Developing countries{\textendash}LDCs, Employment, future, Georgia (country), Ghana, Impact analysis, Kenya, Kuala Lumpur Malaysia, Laos, Republic of North Macedonia, South Korea, Sri Lanka, United States{\textendash}US, Vietnam, Workers}, issn = {15329194}, author = {Egana del Sol, Pablo and Joyce, Connor and Del Sol, Pablo Ega{\~n}a and Joyce, Connor} } @article {Abeliansky2020, title = {The Future of Work: Meeting the Global Challenge of Demographic Change and Automation}, journal = {International Labour Review}, number = {April}, year = {2020}, pages = {1{\textendash}28}, abstract = {We explore future job creation needs under conditions of demographic, economic, and technological change. First, we estimate the implications for job creation in 2020{\textendash}2030 of population growth, changes in labor force participation, and the achievement of target unemployment rates, by age and gender. Second, we analyze the job creation needs by country income group. Finally, we examine the effects of accelerated automation. Overall, shifting demographics, changing labor force participation rates, reductions in unemployment to target levels of 8/4 percent (youth/adults), and automation combine to require the creation of approximately 340 million jobs in 2020{\textendash}2030.}, issn = {0020-7780}, doi = {10.1111/ilr.12168}, author = {Abeliansky, Ana L. and Algur, Eda and Bloom, David E and Prettner, Klaus} } @proceedings {2018, title = {The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning}, year = {2020}, type = {Working paper}, address = {Wailea, HI}, abstract = {

Machine learning (ML) constitute an algorithmic phenomenon with some distinctive characteristics (e.g., being trained, probabilistic). Our understanding of such systems is limited when it comes to how these unique characteristics play out in organizational settings and what challenges different groups of users will face in working with them. We explore how people developing or using an ML system come to understand its capabilities and challenges. We draw on the social construction of technology tradition to frame our analysis of interviews and discussion board posts involving designers and users of a ML-supported citizen-science crowdsourcing project named Gravity Spy. Our findings reveal some of the challenges facing different relevant social groups. We find that groups with less interaction with the technology have their understanding. We find that the type of understandings achieved by groups having less interaction with the technology is shaped by outside influences rather than the specifics of the system and its role in the project. Notable, some users mistake human input for ML input. This initial understanding of how different participants understand and engage with ML point to challenges that need to be overcome to help participants deal with the opaque position ML often hold in a work system.

}, doi = {10.24251/HICSS.2020.719 }, attachments = {https://waim.network/sites/crowston.syr.edu/files/Social_Construction_of_ML_in_GS_HICCS2020.pdf}, author = {Mahboobeh Harandi and Kevin Crowston and Corey Jackson and Carsten {\O}sterlund} } @article {2020, title = {How the FDA regulates AI}, journal = {Academic Radiology}, volume = {27}, year = {2020}, month = {Jan-01-2020}, pages = {58 - 61}, issn = {10766332}, doi = {10.1016/j.acra.2019.09.017}, author = {Harvey, H. Benjamin and Gowda, Vrushab} } @article {B{\ae}r{\o}e2020, title = {How to achieve trustworthy artificial intelligence for health}, journal = {Bulletin of the World Health Organization}, volume = {98}, number = {4}, year = {2020}, pages = {257{\textendash}262}, abstract = {Artificial intelligence holds great promise in terms of beneficial, accurate and effective preventive and curative interventions. At the same time, there is also awareness of potential risks and harm that may be caused by unregulated developments of artificial intelligence. Guiding principles are being developed around the world to foster trustworthy development and application of artificial intelligence systems. These guidelines can support developers and governing authorities when making decisions about the use of artificial intelligence. The HighLevel Expert Group on Artificial Intelligence set up by the European Commission launched the report Ethical guidelines for trustworthy artificial intelligence in 2019. The report aims to contribute to reflections and the discussion on the ethics of artificial intelligence technologies also beyond the countries of the European Union (EU). In this paper, we use the global health sector as a case and argue that the EU{\textquoteright}s guidance leaves too much room for local, contextualized discretion for it to foster trustworthy artificial intelligence globally. We point to the urgency of shared globalized efforts to safeguard against the potential harms of artificial intelligence technologies in health care.}, issn = {15640604}, doi = {10.2471/BLT.19.237289}, author = {B{\ae}r{\o}e, Kristine and Miyata-Sturm, Ainar and Henden, Edmund} } @article {Delfanti2020, title = {Humanly Extended Automation or the Future of Work Seen through Amazon Patents}, journal = {Science, Technology, \& Human Values}, year = {2020}, pages = {016224392094366}, abstract = {

Amazon{\textquoteright}s projects for future automation contribute to anxieties about the marginalization of living labor in warehousing. Yet, a systematic analysis of patents owned by Amazon suggests that workers are not about to disappear from the warehouse floor. Many patents portray machines that increase worker surveillance and work rhythms. Others aim at incorporating workers{\textquoteright} activities into machinery to rationalize the labor process in an ever more pervasive form of digital Taylorism. Patents materialize the company{\textquoteright}s desire for a technological future in which workers act and sense on behalf of machinery, becoming its living and sensing appendages. In this new relationship, humans extend machinery and its reach. Through the work-in-progress process of reaching increasing levels of automation, Amazon develops new technical foundations that consolidate its power in the digital workplace.

}, issn = {0162-2439}, doi = {10.1177/0162243920943665}, url = {http://journals.sagepub.com/doi/10.1177/0162243920943665}, author = {Delfanti, Alessandro and Frey, Bronwyn} } @proceedings {9999, title = {Impacts of the Use of Machine Learning on Work Design}, year = {2020}, month = {11/2020}, publisher = {ACM}, address = {Virtual Event, NSW, Australia}, abstract = {

The increased pervasiveness of technological advancements in automation makes it urgent to address the question of how work is changing in response. Focusing on applications of machine learning (ML) to automate information tasks, we draw on a simple framework for identifying the impacts of an automated system on a task that suggests 3 patterns for the use of ML{\textemdash}decision support, blended decision making and complete automation. In this paper, we extend this framework by considering how automation of one task might have implications for interdependent tasks and how automation applies to coordination mechanisms.

}, keywords = {artificial intelligence, automation, Coordination, machine learning, work design}, isbn = {978-1-4503-8054-6/20/11}, doi = {10.1145/3406499.3415070}, attachments = {https://waim.network/sites/crowston.syr.edu/files/Impacts_of_ML_for_HAI_2020.pdf}, author = {Kevin Crowston and Bolici, Francesco} } @article {Reim2020, title = {Implementation of Artificial Intelligence (AI): A Roadmap for Business Model Innovation}, journal = {AI}, volume = {1}, number = {2}, year = {2020}, pages = {180{\textendash}191}, abstract = {Technical advancements within the subject of artificial intelligence (AI) leads towards development of human-like machines, able to operate autonomously and mimic our cognitive behavior. The progress and interest among managers, academics and the public has created a hype among many industries, and many firms are investing heavily to capitalize on the technology through business model innovation. However, managers are left with little support from academia when aiming to implement AI in their firm{\textquoteright}s operations, which leads to an increased risk of project failure and unwanted results. This paper aims to provide a deeper understanding of AI and how it can be used as a catalyst for business model innovation. Due to the increasing range and variety of the available published material, a literature review has been performed to gather current knowledge within AI business model innovation. The results are presented in a roadmap to guide the implementation of AI to firm{\textquoteright}s operations. Our presented findings suggest four steps when implementing AI: (1) understand AI and organizational capabilities needed for digital transformation; (2) understand current BM, potential for BMI, and business ecosystem role; (3) develop and refine capabilities needed to implement AI; and (4) reach organizational acceptance and develop internal competencies.}, keywords = {artificial intelligence, business model innovation, business models, implementation}, issn = {2673-2688}, doi = {10.3390/ai1020011}, author = {Reim, Wiebke and {\r A}str{\"o}m, Josef and Eriksson, Oliver} } @article {Jung2020, title = {Industrial robots, employment growth, and labor cost: A simultaneous equation analysis}, journal = {Technological Forecasting and Social Change}, volume = {159}, number = {June}, year = {2020}, pages = {120202}, publisher = {Elsevier}, abstract = {In recent years, the global rapid expansion of industrial robots has induced ever-increasing concerns for the cause and effect of such growth, particularly with regard to its relationship with labor. This paper analyzes the factors underlying the adoption of industrial robots, employment growth and structure, and labor costs, taking into account the two-way causalities between these variables. For the empirical analysis, we use the three-stage least squares (3SLS) method for the system of simultaneous equations and apply it to the panel data constructed for 42 countries. Explanatory variables for each equation include the dependent variables of other equations and exogenous variables, such as the labor market environment, physical and human capital, and country-specific social environment. The empirical results of the present study indicate that the increase in both unit labor costs and hourly compensation level induces an extensive application of industrial robots. Subsequently, the expansion of industrial robots leads to a reduction of unit labor costs; however, the hourly compensation level increases, implying that the productivity-enhancing effect exceeds the wage-increasing effect of industrial robots. The extensive use of industrial robots tends to suppress employment growth, confirming the labor-substituting effect of industrial robots; the observed trend disproportionately affects low-skilled labor.}, keywords = {Compensation level, Employment growth, Industrial robots, Labor cost, Simultaneous equation analysis}, issn = {00401625}, doi = {10.1016/j.techfore.2020.120202}, url = {https://doi.org/10.1016/j.techfore.2020.120202}, author = {Jung, Jin Hwa and Lim, Dong Geon} } @booklet {Grimshaw2020, title = {International organisations and the future of work: How new technologies and inequality shaped the narratives in 2019}, howpublished = {Journal of Industrial Relations}, volume = {62}, number = {3}, year = {2020}, pages = {477{\textendash}507}, abstract = {In a critical review of seven prominent flagship reports from five international organisations {\textendash} the International Labour Organization (ILO), Organisation for Economic Co-operation and Development (OECD), United Nations Industrial Development Organization (UNIDO), United Nations Development Programme (UNDP) and World Bank {\textendash} this article explores how the policy narratives set out during 2019 and early 2020 have characterised the major future of work challenges associated with new technologies and inequality. It identifies some similarities in viewpoints, including about the unevenness of job changes caused by new technologies and about the declining labour income share, a key measure of inequality. However, there are major points of differentiation. The ILO, OECD and UNDP express serious concerns about the interaction between new technologies and growing inequalities, on the one hand, and a rise in precarious work, concentration of corporate power and erosion of labour bargaining power on the other. Also, UNIDO emphasises the inequalities in technological capacities between developed and developing countries, which make it difficult for markets to distribute the gains from growth evenly. While the World Bank makes some concessions, it remains less open to real-world heterodox evidence about how labour markets function in society. The World Bank aside, there is a growing consensus that labour institutions around the world need to be reinvigorated in order to respond to the challenges facing the future of work.}, keywords = {future of work, Inequality, International Labour Organization, international organisations, labour income share, new technologies}, issn = {14729296}, doi = {10.1177/0022185620913129}, author = {Grimshaw, Damian} } @conference {Azarova2020, title = {Key Advantages and Risks of Implementing Artificial Intelligence in the Activities of Professional Communicators}, booktitle = {Proceedings of the 2020 IEEE Communication Strategies in Digital Society Seminar, ComSDS 2020}, year = {2020}, pages = {82{\textendash}86}, abstract = {Nowadays we observe a wide penetration of digital technologies into communication experts practice. Literature review demonstrates a great interest of both technical and humanitarian scholars to this subject. The research results, obtained by opinion survey (young adults of 19-24 years old), illustrate possible pragmatic and ethical effects of AI applications as well as their advantages and risks.}, keywords = {AI technologies risks, artificial intelligence, digital technologies, professional communicators}, isbn = {9781728164410}, doi = {10.1109/ComSDS49898.2020.9101238}, author = {Azarova, Liudmila and Kudryavtseva, Maria and Sharakhina, Larisa} } @conference {Das2020, title = {Learning occupational task-shares dynamics for the future of work}, booktitle = {AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society}, year = {2020}, pages = {36{\textendash}42}, abstract = {The recent wave of AI and automation has been argued to differ from previous General Purpose Technologies (GPTs), in that it may lead to rapid change in occupations{\textquoteright} underlying task requirements and persistent technological unemployment. In this paper, we apply a novel methodology of dynamic task shares to a large dataset of online job postings to explore how exactly occupational task demands have changed over the past decade of AI innovation, especially across high, mid and low wage occupations. Notably, big data and AI have risen significantly among high wage occupations since 2012 and 2016, respectively. We built an ARIMA model to predict future occupational task demands and showcase several relevant examples in Healthcare, Administration, and IT. Such task demands predictions across occupations will play a pivotal role in retraining the workforce of the future.}, keywords = {AI, automation, future of work, Occupational Task Demands}, isbn = {9781450371100}, doi = {10.1145/3375627.3375826}, author = {Das, Subhro and Steffen, Sebastian and Clarke, Wyatt and Reddy, Prabhat and Brynjolfsson, Erik and Fleming, Martin} } @conference {2020, title = {Lessons for Supporting Data Science from the Everyday Automation Experience of Spell-Checkers}, booktitle = {Automation Experience across Domains (AutomationXP20), CHI{\textquoteright}20 Workshop, 26 April 2020, Virtual}, year = {2020}, month = {4/2020}, address = {Virtual workshop}, abstract = {

We apply two theoretical frameworks to analyze spell-checkers as a form of automation and apply the lessons learned to analyze opportunities to support data science. The analysis distinguishes between automation of analysis to suggest actions\  and automation of implementation of actions. Having the automation work in the same space as users (e.g., editing the same document) supports stigmergic coordination between the two, but attention is needed to ensure that the contributions can be combined and have a recognizable form that indicates their purpose.

}, attachments = {https://waim.network/sites/crowston.syr.edu/files/Everyday_automation\%20camera\%20ready.pdf}, author = {Kevin Crowston} } @article {Kernbach2020, title = {Machine learning-based clinical prediction modeling {\textendash} A practical guide for clinicians}, journal = {Artificial Intelligence in Precision Health}, number = {June}, year = {2020}, pages = {257{\textendash}278}, publisher = {Elsevier Inc.}, keywords = {Alzheimers disease detection, artificial intelligence, Convolutional neural networks, Deep neural networks, Ensemble machine learning methods}, isbn = {9780128171332}, doi = {10.1016/b978-0-12-817133-2.00011-2}, url = {https://arxiv.org/abs/2006.15069v1 http://dx.doi.org/10.1016/B978-0-12-817133-2.00011-2}, author = {Kernbach, Julius M. and Staartjes, Victor E.} } @article {Seeber2020, title = {Machines as teammates: A research agenda on AI in team collaboration}, journal = {Information and Management}, volume = {57}, number = {2}, year = {2020}, pages = {103174}, publisher = {Elsevier}, abstract = {What if artificial intelligence (AI) machines became teammates rather than tools? This paper reports on an international initiative by 65 collaboration scientists to develop a research agenda for exploring the potential risks and benefits of machines as teammates (MaT). They generated 819 research questions. A subteam of 12 converged them to a research agenda comprising three design areas {\textendash} Machine artifact, Collaboration, and Institution {\textendash} and 17 dualities {\textendash} significant effects with the potential for benefit or harm. The MaT research agenda offers a structure and archetypal research questions to organize early thought and research in this new area of study.}, keywords = {artificial intelligence, Design, Duality, Research agenda, Team collaboration}, issn = {03787206}, doi = {10.1016/j.im.2019.103174}, url = {https://doi.org/10.1016/j.im.2019.103174}, author = {Seeber, Isabella and Bittner, Eva and Briggs, Robert O and de Vreede, Triparna and de Vreede, Gert Jan and Elkins, Aaron and Maier, Ronald and Merz, Alexander B and Oeste-Rei{\ss}, Sarah and Randrup, Nils and Schwabe, Gerhard and S{\"o}llner, Matthias} } @article {Capatina2020, title = {Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users{\textquoteright} expectations}, journal = {Technological Forecasting and Social Change}, volume = {151}, number = {June 2019}, year = {2020}, pages = {119794}, publisher = {Elsevier}, abstract = {The increasing use of Artificial Intelligence (AI) in Social Media Marketing (SMM) triggered the need for this research to identify and further analyze such expectations of potential users of an AI-based software for Social Media Marketing; a software that will be developed in the next two years, based on its future capabilities. In this research, we seek to discover how the potential users of this AI-based software (owners and employees from digital agencies based in France, Italy and Romania, as well as freelancers from these countries, with expertise in SMM) perceive the capabilities that we offer, as a way to differentiate our technological solution from other available in the market. We propose a causal model to find out which expected capabilities of the future AI-based software can explain potential users{\textquoteright} intention to test and use this innovative technological solution for SMM, based on integer valued regression models. With this purpose, R software is used to analyze the data provided by the respondents. We identify different causal configurations of upcoming capabilities of the AI-based software, classified in three categories (audience, image and sentiment analysis), and will trigger potential users{\textquoteright} intention to test and use the software, based on an fsQCA approach.}, keywords = {artificial intelligence, Audience analysis, Image analysis, machine learning, Sentiment analysis, Social media marketing}, issn = {00401625}, doi = {10.1016/j.techfore.2019.119794}, url = {https://doi.org/10.1016/j.techfore.2019.119794}, author = {Capatina, Alexandru and Kachour, Maher and Lichy, Jessica and Micu, Adrian and Micu, Angela Eliza and Codignola, Federica} } @article {Wagner2020, title = {The nature of the Artificially Intelligent Firm - An economic investigation into changes that AI brings to the firm}, journal = {Telecommunications Policy}, volume = {44}, number = {6}, year = {2020}, pages = {101954}, publisher = {Elsevier Ltd}, abstract = {With the arrival of Artificial Intelligence (AI), the nature of the firm is changing and economic theory can provide guidance to businesses as well as to politics when formulating adequate strategies for this unknown terrain. By interpreting AI as a new type of agent within the firm, the theory of the firm can serve as a lingua franca to connect computer sciences and social sciences when dealing with the interdisciplinary phenomenon of AI. To achieve this, this paper adopts the perspective of the economic theory of the firm to systematically explore the changes that AI brings to the institution of the firm. In total, five interrelated propositions are discussed that are rooted in the traditional theory but trace the nature of the Artificially Intelligent Firm: AI intensifies the effects of economic rationality on the firm (1). AI introduces a new type of information asymmetry (2). AI can perforate the boundaries of the firm (3). AI can create triangular agency relationships (4) and AI has the potential to remove traditional limits of integration (5).}, keywords = {artificial intelligence, Asymmetric information, machine learning, Principal-agent problem, Theory of the firm}, issn = {03085961}, doi = {10.1016/j.telpol.2020.101954}, url = {https://doi.org/10.1016/j.telpol.2020.101954}, author = {Wagner, Dirk Nicolas} } @article {Spencer2020, title = {No automation please, we{\textquoteright}re British: Technology and the prospects for work}, journal = {Cambridge Journal of Regions, Economy and Society}, volume = {13}, number = {1}, year = {2020}, pages = {117{\textendash}134}, abstract = {This article assesses the impact and probably limits of automation. It looks, in particular, at the case of the UK economy. The prospects for automation are seen as necessarily uncertain and potentially regressive in their effects, with technology likely to sustain a large number of low-quality jobs. The deep-seated problems of the UK economy-low-investment, low-productivity and low-real wages-are seen as key impediments to forms of automation that work for all in society. It is argued that, without wider institutional reform, the UK will be unable to reap the full potential of automation.}, keywords = {automation, investment, robots, technology, work}, issn = {17521386}, doi = {10.1093/cjres/rsaa003}, author = {Spencer, David and Slater, Gary} } @conference {Sampson2020, title = {Predicting Automation of Professional Jobs in Healthcare}, booktitle = {Proceedings of the 53rd Hawaii International Conference on System Sciences}, volume = {3}, year = {2020}, pages = {3529{\textendash}3537}, isbn = {9780998133133}, doi = {10.24251/hicss.2020.433}, author = {Sampson, Scott} } @article {McLeay2020, title = {Replaced by a Robot: Service Implications in the Age of the Machine}, journal = {Journal of Service Research}, year = {2020}, abstract = {Service organizations, emboldened by the imperative to innovate, are increasingly introducing robots to frontline service encounters. However, as they augment or substitute human employees with robots, they may struggle to convince a distrusting public of their brand{\textquoteright}s ethical credentials. Consequently, this article develops and tests a holistic framework to ascertain a deeper understanding of customer perceptions of frontline service robots (FLSRs) than has previously been attempted. Our experimental studies investigate the effects of the (1) role (augmentation or substitution of human employees or no involvement) and (2) type (humanoid FLSR vs. self-service machine) of FLSRs under the following service contexts: (a) value creation model (asset-builder, service provider) and (b) service type (experience, credence). By empirically establishing our framework, we highlight how customers{\textquoteright} personal characteristics (openness-to-change and preference for ethical/responsible service provider) and cognitive evaluations (perceived innovativeness, perceived ethical/societal reputation, and perceived innovativeness-responsibility fit) influence the impact that FLSRs have on service experience and brand usage intent. Our findings operationalize and empirically support seminal frameworks from extant literature, as well as elaborate on the positive and negative implications of using robots to complement or replace service employees. Further, we consider managerial and policy implications for service in the age of machines.}, keywords = {brand usage intent, ethical/societal reputation, service experience, service innovativeness, service robots}, issn = {15527379}, doi = {10.1177/1094670520933354}, author = {McLeay, Fraser and Osburg, Victoria Sophie and Yoganathan, Vignesh and Patterson, Anthony} } @booklet {Willcocks2020, title = {Robo-Apocalypse cancelled? Reframing the automation and future of work debate}, howpublished = {Journal of Information Technology}, number = {2016}, year = {2020}, abstract = {Robotics and the automation of knowledge work, often referred to as AI (artificial intelligence), are presented in the media as likely to have massive impacts, for better or worse, on jobs skills, organizations and society. The article deconstructs the dominant hype-and-fear narrative. Claims on net job loss emerge as exaggerated, but there will be considerable skills disruption and change in the major global economies over the next 12 years. The term AI has been hijacked, in order to suggest much more going on technologically than can be the case. The article reviews critically the research evidence so far, including the author{\textquoteright}s own, pointing to eight major qualifiers to the dominant discourse of major net job loss from a seamless, overwhelming AI wave sweeping fast through the major economies. The article questions many assumptions: that automation creates few jobs short or long term; that whole jobs can be automated; that the technology is perfectible; that organizations can seamlessly and quickly deploy AI; that humans are machines that can be replicated; and that it is politically, socially and economically feasible to apply these technologies. A major omission in all studies is factoring in dramatic increases in the amount of work to be done. Adding in ageing populations, productivity gaps and skills shortages predicted across many G20 countries, the danger might be too little, rather than too much labour. The article concludes that, if there is going to be a Robo-Apocalypse, this will be from a collective failure to adjust to skills change over the next 12 years. But the debate needs to be widened to the impact of eight other technologies that AI insufficiently represents in the popular imagination and that, in combination, could cause a techno-apocalypse.}, keywords = {AI, automation, cognitive automation, future of work, Information Technology, Jobs, robotic process automation, skills}, isbn = {0268396220925}, issn = {14664437}, doi = {10.1177/0268396220925830}, author = {Willcocks, Leslie} } @booklet {Riemer2020, title = {The robo-apocalypse plays out in the quality, not in the quantity of work}, howpublished = {Journal of Information Technology}, year = {2020}, issn = {14664437}, doi = {10.1177/0268396220923677}, author = {Riemer, Kai and Peter, Sandra} } @article {Arduengo2020, title = {The Robot Economy : Here It Comes}, journal = {International Journal of Social Robotics}, number = {July}, year = {2020}, publisher = {Springer Netherlands}, keywords = {blockchain, Cloud robotics, Intelligent robots, IoRT, Robot economy}, issn = {1875-4805}, doi = {10.1007/s12369-020-00686-1}, url = {https://doi.org/10.1007/s12369-020-00686-1}, author = {Arduengo, Miguel and Sentis, Luis} } @booklet {Dottori2020, title = {Robots and employment: evidence from Italy}, howpublished = {Questioni di Economia e Finanza}, number = {572}, year = {2020}, publisher = {Banca d{\textquoteright}Italia}, abstract = {The relocation of more polluting industries in poorer countries due to gaps in environmental standards is known as the pollution haven effect, whereby the scale and the composition of output change across countries. Changes in the composition of the output mix might translate into changes of comparative advantages across countries, as revealed by trade flows. This paper focus on this issue and looks at the changes of bilateral revealed comparative advantages (RCAs) in the last decade between China and the major fourteen EU countries (EU14). Using industry level data on bilateral trade, air pollution, water pollution and several measures of environmental stringency, we find that, controlling for other factors that may have affected RCAs, such as labor costs, on average our EU14 countries have kept or improved their advantages with respect to China in both water polluting industries (such as paper and agro-based industries) and air polluting industries (such as basic metals and chemicals), while they have lost competitiveness in the more clean industries (such as machinery and fabricated metals).}, author = {Dottori, Davide} } @article {Petersen2020, title = {The Role of Discretion in the Age of Automation}, journal = {Computer Supported Cooperative Work: CSCW: An International Journal}, volume = {29}, number = {3}, year = {2020}, pages = {303{\textendash}333}, abstract = {This paper examines the nature of discretion in social work in order to debunk myths dominating prevalent debates on digitisation and automation in the public sector. Social workers have traditionally used their discretion widely and with great autonomy, but discretion has increasingly come under pressure for its apparent subjectivity and randomness. In Denmark, our case in point, the government recently planned to standardise laws to limit or remove discretion where possible in order for automation of case management to gain a foothold. Recent studies have focused on discretion in the public sector, but few have examined it explicitly and as part of real cases. As a consequence, they often leave the myths about discretion unchallenged. Inspired by the literature on discretion and CSCW research on rules in action, this study reports on an empirical investigation of discretion in child protection services in Denmark. The results of our analysis provide a new understanding of discretion as a cooperative endeavour, based on consultation and skill, rather than an arbitrary or idiosyncratic choice. In this manner, our study contradicts the myth of discretion inherent in the automation agenda. Correspondingly, we ask for attention to be given to systems that integrate discretion with technology rather than seek to undermine it directly or get around it surreptitiously. In this age of automation, this is not only an important but also an urgent task for CSCW researchers to fulfil.}, keywords = {Administrative work, automation, Casework, Decision-Making, Digital-ready legislation, Digitisation, Discretion, Rules in action, Social work}, issn = {15737551}, doi = {10.1007/s10606-020-09371-3}, author = {Petersen, Anette C.M. and Christensen, Lars Rune and Hildebrandt, Thomas T.} } @conference {Schneider2020, title = {Similarity Learning Networks for Animal Individual Re-Identification-Beyond the Capabilities of a Human Observer}, booktitle = {Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2020}, volume = {479}, year = {2020}, pages = {44{\textendash}52}, abstract = {Deep learning has become the standard methodology to approach computer vision tasks when large amounts of labeled data are available. One area where traditional deep learning approaches fail to perform is one-shot learning tasks where a model must correctly classify a new category after seeing only one example. One such domain is animal re-identification, an application of computer vision which can be used globally as a method to automate species population estimates from camera trap images. Our work demonstrates both the application of similarity comparison networks to animal re-identification, as well as the capabilities of deep convolutional neural networks to generalize across domains. Few studies have considered animal re-identification methods across species. Here, we compare two similarity comparison methodologies: Siamese and Triplet-Loss, based on the AlexNet, VGG-19, DenseNet201, MobileNetV2, and InceptionV3 architectures considering mean average precision (mAP)@1 and mAP@5. We consider five data sets corresponding to five different species: Humans, chimpanzees, humpback whales, fruit flies, and Siberian tigers, each with their own unique set of challenges. We demonstrate that Triplet Loss outperformed its Siamese counterpart for all species. Without any species-specific modifications, our results demonstrate that similarity comparison networks can reach a performance level beyond that of humans for the task of animal re-identification. The ability for researchers to re-identify an animal individual upon re-encounter is fundamental for addressing a broad range of questions in the study of population dynamics and community/behavioural ecology. Our expectation is that similarity comparison networks are the beginning of a major trend that could stand to revolutionize animal re-identification from camera trap data.}, isbn = {9781728171623}, doi = {10.1109/WACVW50321.2020.9096925}, author = {Schneider, Stefan and Taylor, Graham W. and Kremer, Stefan C.} } @article {Theresa2020, title = {Think with me, or think for me? On the future role of artificial intelligence in marketing strategy formulation}, journal = {The TQM Journal}, volume = {ahead-of-p}, number = {ahead-of-print}, year = {2020}, month = {jan}, abstract = {Purpose This paper explores if and how Artificial Intelligence can contribute to marketing strategy formulation.Design/methodology/approach Qualitative research based on exploratory in-depth interviews with industry experts currently working with artificial intelligence tools.Findings Key themes include: (1) Importance of AI in strategic marketing decision management; (2) Presence of AI in strategic decision management; (3) Role of AI in strategic decision management; (4) Importance of business culture for the use of AI; (5) Impact of AI on the business{\textquoteright} organizational model. A key consideration is a {\textquotedblleft}creative-possibility perspective,{\textquotedblright} highlighting the future potential to use AI not only for rational but also for creative thinking purposes.Research limitations/implications This work is focused only on strategy creation as a deliberate process. For this, AI can be used as an effective response to the external contingencies of high volumes of data and uncertain environmental conditions, as well as being an effective response to the external contingencies of limited managerial cognition. A key future consideration is a {\textquotedblleft}creative-possibility perspective.{\textquotedblright}Practical implications A practical extension of the Gartner Analytics Ascendancy Model (Maoz, 2013).Originality/value This paper aims to contribute knowledge relating to the role of AI in marketing strategy formulation and explores the potential avenues for future use of AI in the strategic marketing process. This is explored through the lens of contingency theory, and additionally, findings are expressed using the Gartner analytics ascendancy model.}, keywords = {AI, artificial intelligence, creativity, marketing strategy, marketing synergy, paper type research paper, rationality, tqm}, isbn = {1754-2731}, doi = {10.1108/TQM-12-2019-0303}, url = {https://doi.org/10.1108/TQM-12-2019-0303}, author = {Theresa, Eriksson and Alessandro, Bigi and Michelle, Bonera and Eriksson, Theresa and Bigi, Alessandro and Bonera, Michelle and Theresa, Eriksson and Alessandro, Bigi and Michelle, Bonera} } @article {Brundage2020, title = {Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims}, year = {2020}, pages = {1{\textendash}9}, abstract = {With the recent wave of progress in artificial intelligence (AI) has come a growing awareness of the large-scale impacts of AI systems, and recognition that existing regulations and norms in industry and academia are insufficient to ensure responsible AI development. In order for AI developers to earn trust from system users, customers, civil society, governments, and other stakeholders that they are building AI responsibly, they will need to make verifiable claims to which they can be held accountable. Those outside of a given organization also need effective means of scrutinizing such claims. This report suggests various steps that different stakeholders can take to improve the verifiability of claims made about AI systems and their associated development processes, with a focus on providing evidence about the safety, security, fairness, and privacy protection of AI systems. We analyze ten mechanisms for this purpose{\textendash}spanning institutions, software, and hardware{\textendash}and make recommendations aimed at implementing, exploring, or improving those mechanisms.}, url = {http://arxiv.org/abs/2004.07213}, author = {Brundage, Miles and Avin, Shahar and Wang, Jasmine and Belfield, Haydn and Krueger, Gretchen and Hadfield, Gillian and Khlaaf, Heidy and Yang, Jingying and Toner, Helen and Fong, Ruth and Maharaj, Tegan and Koh, Pang Wei and Hooker, Sara and Leung, Jade and Trask, Andrew and Bluemke, Emma and Lebensold, Jonathan and O{\textquoteright}Keefe, Cullen and Koren, Mark and Ryffel, Th{\'e}o and Rubinovitz, JB and Besiroglu, Tamay and Carugati, Federica and Clark, Jack and Eckersley, Peter and de Haas, Sarah and Johnson, Maritza and Laurie, Ben and Ingerman, Alex and Krawczuk, Igor and Askell, Amanda and Cammarota, Rosario and Lohn, Andrew and Krueger, David and Stix, Charlotte and Henderson, Peter and Graham, Logan and Prunkl, Carina and Martin, Bianca and Seger, Elizabeth and Zilberman, Noa and H{\'E}igeartaigh, Se{\'a}n {\'O} and Kroeger, Frens and Sastry, Girish and Kagan, Rebecca and Weller, Adrian and Tse, Brian and Barnes, Elizabeth and Dafoe, Allan and Scharre, Paul and Herbert-Voss, Ariel and Rasser, Martijn and Sodhani, Shagun and Flynn, Carrick and Gilbert, Thomas Krendl and Dyer, Lisa and Khan, Saif and Bengio, Yoshua and Anderljung, Markus} } @conference {Ferreira2020, title = {Understanding the Impact of Artificial Intelligence on Services}, booktitle = {International Conference on Exploring Services Science}, series = {Lecture Notes in Business Information Processing}, volume = {1}, number = {January}, year = {2020}, pages = {202{\textendash}213}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {The service sector is changing drastically due the use of robotics and other technologies, such as Artificial Intelligence (AI), Internet of things (IoT), Big Data and Biometrics. Consequently, further research opportunities in the service industry domain are also expected. In light of the above, the purpose of this paper is to explore the potentialities and limitations of service robots in the hospitality industry. To this end, this paper uses a conceptual approach based on a literature review. As a result, we found that in contexts of high customer contact, service robots should be considered to perform standardized tasks due to social/emotional and cognitive/analytical complexity. The hospitality industry is therefore considered closely related to empathic intelligence, as the integration of service robots has not yet reached the desired stage of service delivery. In a seemingly far-fetched context of our reality, organizations will have to decide whether the AI will allow the complete replacement of humans with robots capable of performing the necessary cognitive and emotional tasks. Or investing in balanced capacities by integrating robot-human systems that seems a rea- sonable option these days. Keywords:}, keywords = {{\'a} servitization {\'a} design, science research, service design}, isbn = {9783030387242}, doi = {10.1007/978-3-030-38724-2}, url = {http://link.springer.com/10.1007/978-3-030-38724-2}, author = {Ferreira, Pedro and Teixeira, Jorge Grenha and Teixeira, Lu{\'\i}s F.}, editor = {N{\'o}voa, Henriqueta and Dr{\u a}goicea, Monica and K{\"u}hl, Niklas} } @article {Krupiy2020, title = {A vulnerability analysis : Theorising the impact of artificial intelligence decision-making processes on individuals , society and human diversity from a social justice perspective}, journal = {Computer Law \& Security Review: The International Journal of Technology Law and Practice}, volume = {38}, year = {2020}, pages = {105429}, publisher = {Elsevier Ltd}, keywords = {artificial intelligence, data science, Decision-maki}, issn = {0267-3649}, doi = {10.1016/j.clsr.2020.105429}, url = {https://doi.org/10.1016/j.clsr.2020.105429}, author = {Krupiy, Tetyana Tanya} } @article {Clifton2020, title = {When machines think for us: The consequences for work and place}, journal = {Cambridge Journal of Regions, Economy and Society}, volume = {13}, number = {1}, year = {2020}, pages = {3{\textendash}23}, abstract = {The relationship between technology and work, and concerns about the displacement effects of technology and the organisation of work, have a long history. The last decade has seen the proliferation of academic papers, consultancy reports and news articles about the possible effects of Artificial Intelligence (AI) on work-creating visions of both utopian and dystopian workplace futures. AI has the potential to transform the demand for labour, the nature of work and operational infrastructure by solving complex problems with high efficiency and speed. However, despite hundreds of reports and studies, AI remains an enigma, a newly emerging technology, and its rate of adoption and implications for the structure of work are still only beginning to be understood. The current anxiety about labour displacement anticipates the growth and direct use of AI. Yet, in many ways, at present AI is likely being overestimated in terms of impact. Still, an increasing body of research argues the consequences for work will be highly uneven and depend on a range of factors, including place, economic activity, business culture, education levels and gender, among others. We appraise the history and the blurry boundaries around the definitions of AI. We explore the debates around the extent of job augmentation, substitution, destruction and displacement by examining the empirical basis of claims, rather than mere projections. Explorations of corporate reactions to the prospects of AI penetration, and the role of consultancies in prodding firms to embrace the technology, represent another perspective onto our inquiry. We conclude by exploring the impacts of AI changes in the quantity and quality of labour on a range of social, geographic and governmental outcomes.}, keywords = {artificial intelligence, automation, bias in machine learning, geography of technology, job displacement and growth}, issn = {17521386}, doi = {10.1093/cjres/rsaa004}, author = {Clifton, Judith and Clifton, Judith and Glasmeier, Amy and Gray, Mia} } @booklet {Commission2020, title = {White Paper on Artificial Intelligence - A European approach to excellence and trust}, howpublished = {COM(2020) 65 final}, year = {2020}, abstract = {Predicting the binding mode of flexible polypeptides to proteins is an important task that falls outside the domain of applicability of most small molecule and protein-protein docking tools. Here, we test the small molecule flexible ligand docking program Glide on a set of 19 non-α-helical peptides and systematically improve pose prediction accuracy by enhancing Glide sampling for flexible polypeptides. In addition, scoring of the poses was improved by post-processing with physics-based implicit solvent MM- GBSA calculations. Using the best RMSD among the top 10 scoring poses as a metric, the success rate (RMSD <= 2.0 {\r A} for the interface backbone atoms) increased from 21\% with default Glide SP settings to 58\% with the enhanced peptide sampling and scoring protocol in the case of redocking to the native protein structure. This approaches the accuracy of the recently developed Rosetta FlexPepDock method (63\% success for these 19 peptides) while being over 100 times faster. Cross-docking was performed for a subset of cases where an unbound receptor structure was available, and in that case, 40\% of peptides were docked successfully. We analyze the results and find that the optimized polypeptide protocol is most accurate for extended peptides of limited size and number of formal charges, defining a domain of applicability for this approach.}, url = {https://www.cambridge.org/core/product/identifier/CBO9781107415324A009/type/book_part}, author = {Commission, European} } @article {2019, title = {AI, robots and jobs: Estimation and implications}, year = {2019}, note = {{\textbullet} What AI can and cannot do {\textbullet} Dire prediction {\textbullet} Estimation methods and results {\textbullet} Policy implications {\textbullet} Case of Singapore}, url = {https://ehelf.nu.edu.kz/wp-content/uploads/2019/06/1-Eduardo-Araral-GSPP.pdf}, author = {Eduardo Araral} } @article {2019, title = {AI{\textquoteright}s path to the present and the painful transitions along the way}, journal = {Digital Policy, Regulation and Governance}, volume = {21}, year = {2019}, month = {Jan-05-2020}, pages = {305 - 321}, issn = {2398-50382398-5038}, doi = {10.1108/DPRG-09-2018-0051}, author = {Garcia-Murillo, Martha and MacInnes, Ian} } @article {2019, title = {AI trained on decades of food research can concoct better recipes}, journal = {FlavorBot}, year = {2019}, url = {https://futurism.com/ai-food-research-better-recipes} } @article {2019, title = {AI-Assisted Decision-making in Healthcare}, journal = {Asian Bioethics Review}, volume = {11}, year = {2019}, month = {Jan-09-2019}, pages = {299 - 314}, issn = {1793-8759}, doi = {10.1007/s41649-019-00096-0}, author = {Lysaght, Tamra and Lim, Hannah Yeefen and Xafis, Vicki and Ngiam, Kee Yuan} } @article {2019, title = {AI-Based Digital Assistants}, journal = {Business \& Information Systems Engineering}, volume = {61}, year = {2019}, month = {Jan-08-2019}, pages = {535 - 544}, issn = {2363-7005}, doi = {10.1007/s12599-019-00600-8}, author = {Maedche, Alexander and Legner, Christine and Benlian, Alexander and Berger, Benedikt and Gimpel, Henner and Hess, Thomas and Hinz, Oliver and Morana, Stefan and S{\"o}llner, Matthias} } @article {2019, title = {Algorithms, artificial intelligence and automated decisions concerning workers and the risks of discrimination: the necessary collective governance of data protection}, journal = {Transfer: European Review of Labour and Research}, volume = {25}, year = {2019}, month = {Jan-11-2019}, pages = {465 - 481}, issn = {1024-2589}, doi = {10.1177/1024258919876416}, author = {Todol{\'\i}-Signes, Adri{\'a}n} } @article {2019, title = {Algorithms at War: The Promise, Peril, and Limits of Artificial Intelligence}, journal = {International Studies Review}, year = {2019}, month = {Dec-06-2020}, issn = {1521-9488}, doi = {10.1093/isr/viz025}, author = {Jensen, Benjamin M and Whyte, Christopher and Cuomo, Scott} } @article {2019, title = {Amazon{\textquoteright}s AI expansion}, journal = {AI Daily}, year = {2019}, month = {06/2019}, type = {AI}, url = {https://www.aidaily.co.uk/articles/amazons-ai-expansion}, author = {Parth Mahendra} } @article {2019, title = {The ambiguous labor market impact of automating prediction}, year = {2019}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w25619}, author = {Agrawal, Ajay and Gans, Joshua and Goldfarb, Avi} } @article {2019, title = {Apple reminds us that behind the AI revolution lies an army of humans seeing our data}, journal = {Forbes}, year = {2019}, url = {https://www.forbes.com/sites/kalevleetaru/2019/07/30/apple-reminds-us-that-behind-the-ai-revolution-lies-an-army-of-humans-seeing-our-data/$\#$3dd2e8ba339d}, author = {Kalev Leetaru} } @article {2019, title = {Applications of artificial intelligence to imaging and diagnosis}, journal = {Biophysical Reviews}, volume = {11}, year = {2019}, month = {Jan-02-2019}, pages = {111 - 118}, issn = {1867-2450}, doi = {10.1007/s12551-018-0449-9}, author = {Nichols, James A. and Herbert Chan, Hsien W. and Baker, Matthew A. B.} } @article {2019, title = {Applying for your next job may be an automated nightmare}, journal = {Gizmodo}, year = {2019}, month = {04/2019}, type = {Automation}, keywords = {automation, job}, url = {https://gizmodo.com/applying-for-your-next-job-may-be-an-automated-nightmar-1834275825}, author = {Brian Merchant} } @article {2019, title = {Are robots competing for your job? }, journal = {The New Yorker}, year = {2019}, month = {03/2019}, type = {Annals of Technology}, url = {https://www.newyorker.com/magazine/2019/03/04/are-robots-competing-for-your-job}, author = {Jill Lepore} } @article {2019, title = {Are robots stealing our jobs? }, journal = {Socius: Sociological Research for a Dynamic World}, volume = {5}, year = {2019}, month = {Oct-01-2019}, pages = {237802311984624}, issn = {2378-0231}, doi = {10.1177/2378023119846249}, author = {Dahlin, Eric} } @article {2019, title = {Is an army of robots marching on Chinese jobs? }, journal = {IZA {\textendash} Institute of Labor Economics}, year = {2019}, month = {04/2019}, url = {https://www.iza.org/publications/dp/12281/is-an-army-of-robots-marching-on-chinese-jobs}, author = {Osea Giuntella and Tianyi Wang} } @article {2019, title = {Artificial intelligence and big data in entrepreneurship: a new era has begun}, journal = {Small Business Economics}, year = {2019}, month = {Jun-06-2019}, issn = {0921-898X}, doi = {10.1007/s11187-019-00202-4}, author = {Obschonka, Martin and Audretsch, David B.} } @article {2019, title = {Artificial Intelligence and Deep Learning: The Future of Medicine and Medical Practice}, journal = { Journal of The Association of Physicians of India ■ Vol. 67 }, year = {2019}, month = {05/2019}, url = {https://www.semanticscholar.org/paper/Artificial-Intelligence-and-Deep-Learning\%3A-The-of-Sanal-Paul/795dc72decfb12389bbf7076d82fef70421b9933}, author = {Madhusudana Girija Sanal and Kolin Paul and Senthil Kumar and Nirmal Kumar Gangul} } @article {2019, title = {Artificial intelligence and the future of labor demand}, year = {2019}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w25682}, author = {Acemoglu, Daron and Restrepo, Pascual} } @article {2019, title = {Artificial Intelligence and the Future of the Drug Safety Professional}, journal = {Drug Safety}, volume = {42}, year = {2019}, month = {Jan-04-2019}, pages = {491 - 497}, issn = {0114-5916}, doi = {10.1007/s40264-018-0746-z}, author = {Danysz, Karolina and Cicirello, Salvatore and Mingle, Edward and Assuncao, Bruno and Tetarenko, Niki and Mockute, Ruta and Abatemarco, Danielle and Widdowson, Mark and Desai, Sameen} } @article {2019, title = {Artificial intelligence conquers starcraft II in {\textquoteright}unimaginably unusual{\textquoteright} AI breakthrough}, journal = {Independent}, year = {2019}, url = {https://www.independent.co.uk/life-style/gadgets-and-tech/gaming/artificial-intelligence-starcraft-2-ai-deepmind-a9176601.html}, author = {Anthony Cuthbertson} } @article {2019, title = {Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers}, journal = {Industrial Management \& Data Systems}, volume = {119}, year = {2019}, month = {Dec-08-2019}, pages = {1411 - 1430}, issn = {0263-5577}, doi = {10.1108/IMDS-08-2018-0368}, author = {Belanche, Daniel and Casal{\'o}, Luis V. and Flavi{\'a}n, Carlos} } @article {2019, title = {Artificial intelligence in medicine: What is it doing for us today?}, journal = {Health Policy and Technology}, volume = {8}, year = {2019}, month = {Jan-06-2019}, pages = {198 - 205}, issn = {22118837}, doi = {10.1016/j.hlpt.2019.03.004}, author = {Becker, Aliza} } @article {2019, title = {Artificial intelligence in workplaces and how it will affect employment in Latvia}, journal = {Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference}, volume = {2}, year = {2019}, month = {Aug-06-2020}, pages = {154}, issn = {1691-5402}, doi = {10.17770/etr2019vol2.4151}, author = {{\v S}ukjurovs, Ilm{\={a}}rs and Zvirgzdina, Rosita and Jeromanova-Maura, Silva} } @article {2019, title = {As Walmart turns to robots, it{\textquoteright}s the human workers who feel like machines}, year = {2019}, month = {06/2019}, type = {Technology}, url = {https://www.washingtonpost.com/technology/2019/06/06/walmart-turns-robots-its-human-workers-who-feel-like-machines/}, author = {Drew Harwell} } @article {2019, title = {Automation and new tasks: How technology displaces and reinstates labor}, year = {2019}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w25684}, author = {Acemoglu, Daron and Restrepo, Pascual} } @article {2019, title = {Automation as Part of the Solution}, journal = {Journal of Management Inquiry}, volume = {28}, year = {2019}, month = {Jun-07-2021}, pages = {316 - 318}, issn = {1056-4926}, doi = {10.1177/1056492619827375}, author = {Levine, David I.} } @article {2019, title = {Automation, wage inequality and implications of a robot tax}, journal = {International Review of Economics \& Finance}, volume = {59}, year = {2019}, month = {Jan-01-2019}, pages = {500 - 509}, issn = {10590560}, doi = {10.1016/j.iref.2018.10.013}, author = {Zhang, Pengqing} } @article {2019, title = {Behavioural artificial intelligence: An agenda for systematic empirical studies of artificial inference}, journal = {AI \& SOCIETY}, year = {2019}, month = {Jun-12-2020}, issn = {0951-5666}, doi = {10.1007/s00146-019-00928-5}, author = {Pedersen, Tore and Johansen, Christian} } @book {2019, title = {Benefits and risks of artificial intelligence tools in workplaces}, volume = {11581}, year = {2019}, pages = {292 - 315}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-22215-4}, issn = {0302-9743}, doi = {10.1007/978-3-030-22216-1_22}, author = {Moore, Phoebe V.}, editor = {Duffy, Vincent G.} } @conference {2019, title = {Beyond Dyadic Interactions: Considering Chatbots as Community Members}, booktitle = {Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI {\textquoteright}19}, year = {2019}, pages = {1-13}, publisher = {ACM Press}, organization = {ACM Press}, address = {Glasgow, Scotland UK}, isbn = {9781450359702}, doi = {10.1145/3290605}, author = {Seering, Joseph and Luria, Michal and Kaufman, Geoff and Hammer, Jessica} } @article {2019, title = {Blame the boss, not the robot}, journal = {New Labor Forum}, volume = {28}, year = {2019}, month = {Oct-05-2020}, pages = {66 - 69}, issn = {1095-7960}, doi = {10.1177/1095796019837947}, author = {Smith, Zachary} } @article {2019, title = {Bots Coordinating Work in Open Source Software Projects}, journal = {Computer}, volume = {52}, year = {2019}, month = {Jan-09-2019}, pages = {52 - 60}, issn = {0018-9162}, doi = {10.1109/MC.2018.2885970}, author = {Hukal, Philipp and Berente, Nicholas and Germonprez, Matt and Schecter, Aaron} } @article {2019, title = {A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence}, journal = {California Management Review}, volume = {61}, year = {2019}, month = {Sep-08-2019}, pages = {5 - 14}, issn = {0008-1256}, doi = {10.1177/0008125619864925}, author = {Haenlein, Michael and Kaplan, Andreas} } @article {2019, title = {Can nurses remain relevant in a technologically advanced future?}, journal = {International Journal of Nursing Sciences}, volume = {6}, year = {2019}, month = {Jan-01-2019}, pages = {106 - 110}, issn = {23520132}, doi = {10.1016/j.ijnss.2018.09.013}, author = {Pepito, Joseph Andrew and Locsin, Rozzano} } @conference {2019, title = {A chatbot for supporting teams in the empathy map method}, booktitle = {Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences}, year = {2019}, publisher = {Hawaii International Conference on System Sciences}, organization = {Hawaii International Conference on System Sciences}, doi = {10.24251/HICSS.2019.029}, author = {Bittner, Eva and Shoury, Omid} } @article {2019, title = {Citizen attitudes about job replacement by robotic automation}, journal = {Futures}, volume = {109}, year = {2019}, month = {Jan-05-2019}, pages = {39 - 49}, issn = {00163287}, doi = {10.1016/j.futures.2019.04.005}, author = {Nam, Taewoo} } @article {2019, title = {Cognitively enhanced products, output growth, and labor market changes: Will artificial intelligence replace workers by automating their jobs? }, journal = {Economics, Management, and Financial Markets}, volume = {14}, year = {2019}, month = {Jan-01-2019}, pages = {38}, issn = {1842-3191}, doi = {10.22381/EMFM14120194} } @article {2019, title = {Collaboration and delegation between humans and AI: An experimental investigation of the future of work}, journal = {SSRN Electronic Journal}, year = {2019}, month = {Jan-01-2019}, doi = {10.2139/ssrn.3368813}, author = {F{\"u}gener, Andreas and Grahl, J{\"o}rn and Gupta, Alok and Ketter, Wolfgang} } @article {2019, title = {Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark}, journal = {European Journal of Cancer}, volume = {111}, year = {2019}, month = {Jan-04-2019}, pages = {30 - 37}, issn = {09598049}, doi = {10.1016/j.ejca.2018.12.016}, author = {Brinker, Titus J. and Hekler, Achim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Alexander Enk and Haferkamp, Sebastian and Karoglan, Ante and von Kalle, Christof and Weichenthal, Michael and Sattler, Elke and Schadendorf, Dirk and Gaiser, Maria R. and Klode, Joachim and Jochen Sven Utikal} } @conference {2019, title = {Consider the human work experience when integrating robotics in the workplace}, booktitle = {2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)}, year = {2019}, pages = {75 - 84}, publisher = {IEEE}, organization = {IEEE}, address = {Daegu, Korea (South)}, doi = {10.1109/HRI.2019.8673139}, url = {https://ieeexplore.ieee.org/document/8673139/http://xplorestaging.ieee.org/ielx7/8666012/8673065/08673139.pdf?arnumber=8673139}, author = {Welfare, Katherine S. and Hallowell, Matthew R. and Shah, Julie A. and Riek, Laurel D.} } @article {2019, title = {A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task}, journal = {European Journal of Cancer}, volume = {111}, year = {2019}, month = {Jan-04-2019}, pages = {148 - 154}, issn = {09598049}, doi = {10.1016/j.ejca.2019.02.005}, author = {Brinker, Titus J. and Hekler, Achim and Alexander Enk and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Fr{\"o}hling, Stefan and Jochen Sven Utikal and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenh{\"o}fer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Sondermann, Wiebke and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Alexander Enk and Gholam, Patrick and H{\"a}n{\ss}le, Holger and Salzmann, Martin and Sch{\"a}fer, Sarah and Sch{\"a}kel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Hauschild, Axel and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and St{\"o}lzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and B{\"a}r, Claudia Maria and Bender-S{\"a}belkampf, Sophia and Horbr{\"u}gger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, J{\"o}rg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and M{\"u}ller, Verena and Thomas, Benjamin and Jochen Sven Utikal and Alamri, Ali Saeed M. and Baczako, Andrea and Berking, Carola and Betke, Matthias and Haas, Carolin and Hartmann, Daniela and Heppt, Markus V. and Kilian, Katharina and Krammer, Sebastian and Lapczynski, Natalie Lidia and Mastnik, Sebastian and Nasifoglu, Suzan and Ruini, Cristel and Sattler, Elke and Schlaak, Max and Wolff, Hans and Achatz, Birgit and Bergbreiter, Astrid and Drexler, Konstantin and Ettinger, Monika and Haferkamp, Sebastian and Halupczok, Anna and Hegemann, Marie and Dinauer, Verena and Maagk, Maria and Mickler, Marion and Philipp, Biance and Wilm, Anna and Wittmann, Constanze and Gesierich, Anja and Glutsch, Valerie and Kahlert, Katrin and Kerstan, Andreas and Schilling, Bastian and Schr{\"u}fer, Philipp} } @article {2019, title = {Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task}, journal = {European Journal of Cancer}, volume = {113}, year = {2019}, month = {Jan-05-2019}, pages = {47 - 54}, issn = {09598049}, doi = {10.1016/j.ejca.2019.04.001}, author = {Brinker, Titus J. and Hekler, Achim and Alexander Enk and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Holland-Letz, Tim and Jochen Sven Utikal and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenh{\"o}fer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Alexander Enk and Gholam, Patrick and H{\"a}n{\ss}le, Holger and Salzmann, Martin and Sch{\"a}fer, Sarah and Sch{\"a}kel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Hauschild, Axel and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and St{\"o}lzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and B{\"a}r, Claudia Maria and Bender-S{\"a}belkampf, Sophia and Horbr{\"u}gger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, J{\"o}rg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and M{\"u}ller, Verena and Thomas, Benjamin and Jochen Sven Utikal and Alamri, Ali Saeed M. and Baczako, Andrea and Berking, Carola and Betke, Matthias and Haas, Carolin and Hartmann, Daniela and Heppt, Markus V. and Kilian, Katharina and Krammer, Sebastian and Lapczynski, Natalie Lidia and Mastnik, Sebastian and Nasifoglu, Suzan and Ruini, Cristel and Sattler, Elke and Schlaak, Max and Wolff, Hans and Achatz, Birgit and Bergbreiter, Astrid and Drexler, Konstantin and Ettinger, Monika and Haferkamp, Sebastian and Halupczok, Anna and Hegemann, Marie and Dinauer, Verena and Maagk, Maria and Mickler, Marion and Philipp, Biance and Wilm, Anna and Wittmann, Constanze and Gesierich, Anja and Glutsch, Valerie and Kahlert, Katrin and Kerstan, Andreas and Schilling, Bastian and Schr{\"u}fer, Philipp} } @book {2019, title = {Designing AI futures: A symbiotic vision}, volume = {1083}, year = {2019}, pages = {3 - 18}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-29742-8}, issn = {1865-0929}, doi = {10.1007/978-3-030-29743-5_1}, author = {Gill, Karamjit S.}, editor = {Kravets, Alla G. and Groumpos, Peter P. and Shcherbakov, Maxim and Kultsova, Marina} } @article {2019, title = {Digital Economics}, journal = {Journal of Economic Literature}, volume = {57}, year = {2019}, month = {Jan-03-2019}, pages = {3 - 43}, issn = {0022-0515}, doi = {10.1257/jel.20171452}, author = {Goldfarb, Avi and Tucker, Catherine} } @article {2019, title = {Digital inequalities in the age of artificial intelligence and big data}, journal = {Human Behavior and Emerging Technologies}, volume = {1}, year = {2019}, month = {Feb-04-2021}, pages = {141 - 148}, issn = {2578-1863}, doi = {10.1002/hbe2.140}, author = {Lutz, Christoph} } @article {2019, title = {Digitalization and the future of work: Macroeconomic consequences}, year = {2019}, publisher = {ZEW - Leibniz-Zentrum f{\"u}r Europ{\"a}ische Wirtschaftsforschung}, abstract = {Computing power continues to grow at an enormous rate. Simultaneously, more and better data is increasingly available and Machine Learning methods have seen significant breakthroughs in the recent past. All this pushes further the boundary of what machines can do. Nowadays increasingly complex tasks are automatable at a precision which seemed infeasible only few years ago. The examples range from voice and image recognition, playing Go, to self-driving vehicles. Machines are able to perform more and more manual and also cognitive tasks that previously only humans could do. As a result of these developments, some argue that large shares of jobs are "at risk of automation", spurring public fears of massive job-losses and technological unemployment. This chapter discusses how new digital technologies might affect the labor market in the near future. First, the chapter discusses estimates of automation potentials, showing that many estimates are severely upward biased because they ignore that workers in seemingly automatable occupations already take over hard-to-automate tasks. Secondly, it highlights that these numbers only refer to what theoretically could be automated and that this must not be equated with job-losses or employment effects - a mistake that is done often in the public debate. Thirdly, the chapter develops scenarios on how digitalization is likely to affect the German labor market in the next five years and derives implications for policy makers on how to shape the future of work. Germany is an interesting case to study, as it is a developed country at the technological frontier. In particular, the main challenge will not be the number, but the structure of jobs and the corresponding need for supply side adjustments to meet the shift in demand both within and between occupations and sectors.}, keywords = {automation, Digitalization, Inequality, unemployment}, url = {http://hdl.handle.net/10419/200063}, author = {Melanie Arntz and Terry Gregory and Ulrich Zierahn} } @conference {2019, title = {Does automation influence career decisions among South African students?}, booktitle = {the South African Institute of Computer Scientists and Information Technologists 2019Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019 on ZZZ - SAICSIT {\textquoteright}19}, year = {2019}, pages = {1 - 10}, publisher = {ACM Press}, organization = {ACM Press}, address = {Skukuza, South AfricaNew York, New York, USA}, isbn = {9781450372657}, doi = {10.1145/335110810.1145/3351108.3351137}, author = {Mbilini, Sakhumzi N. and le Roux, Daniel B. and Parry, Douglas A.} } @article {2019, title = {Does the use of synchrony and artificial intelligence in video interviews affect interview ratings and applicant attitudes?}, journal = {Computers in Human Behavior}, volume = {98}, year = {2019}, month = {Jan-09-2019}, pages = {93 - 101}, issn = {07475632}, doi = {10.1016/j.chb.2019.04.012}, author = {Suen, Hung-Yue and Chen, Mavis Yi-Ching and Lu, Shih-Hao} } @article {2019, title = {Is a driverless future also jobless?}, year = {2019}, institution = {W.E. Upjohn Institute}, doi = {10.17848/pb2019-17}, author = {Groshen, Erica L.} } @article {2019, title = {Economic, Social Impacts and Operation of Smart Factories in Industry 4.0 Focusing on Simulation and Artificial Intelligence of Collaborating Robots}, journal = {Social Sciences}, volume = {8}, year = {2019}, month = {Jan-05-2019}, pages = {143}, doi = {10.3390/socsci8050143}, author = {Benotsmane, Rabab and Kov{\'a}cs, Gy{\"o}rgy and Dud{\'a}s, L{\'a}szl{\'o}} } @book {2019, title = {Educating those most impacted by artificial intelligence}, volume = {11626}, year = {2019}, pages = {344 - 349}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-23206-1}, issn = {0302-9743}, doi = {10.1007/978-3-030-23207-8_63}, author = {Gemmell, Laura and Wenham, Lucy and Hauert, Sabine}, editor = {Isotani, Seiji and Mill{\'a}n, Eva and Ogan, Amy and Hastings, Peter and McLaren, Bruce and Luckin, Rose} } @book {2019, title = {The emergence of complexity}, year = {2019}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-31837-6}, issn = {2366-1658}, doi = {10.1007/978-3-030-31839-0}, author = {Hager, Paul and Beckett, David} } @article {2019, title = {Emotional processes in human-robot interaction during brief cognitive testing}, journal = {Computers in Human Behavior}, volume = {90}, year = {2019}, month = {Jan-01-2019}, pages = {331 - 342}, issn = {07475632}, doi = {10.1016/j.chb.2018.08.013}, author = {Desideri, Lorenzo and Ottaviani, Cristina and Malavasi, Massimiliano and di Marzio, Roberto and Bonifacci, Paola} } @article {2019, title = { Employment Transformation through Artificial Intelligence }, year = {2019}, note = {We all are moving at pace towards innovative technologies and adopting these technologies, human are being entered into the digital world, where they are going to be facilitated by transformed traditional systems into modern systems. In next few years, most of systems will be smart and able to do anything as human can do. This transformation will be a reason to bring the human into very comfort zone where they will take the advantages of these modern facilities. This transformation will help to government in developing the new aspects of developments in their country .As today, the traditional systems are being smart and intelligence along with that cities are also being smart day by day. This transformation will be a cause of bringing a big revolution for the human{\textquoteright}s life across the world. On another side, this transformation will have positive and negative impact on employability in different sectors. India is essentially entering into a new industrial revolution and it is going to wipe out millions of jobs in India. Innovative transformation through industry revolution will restructure the infrastructure and working environment in services as well as in manufacturing industries. Productivity and revenue of industries will be up after replacing existing methods with innovative methods. Basically, these innovative methods will replace the human with intellectual artificial (AI) machines which will transform the working environment of industries partially or entirely. AI Machines will be responsible for transformation in employability across the world. Machine will take control over the human work means in future most of the work will be executed by the Artificial..}, edition = {International Journal of Applied Engineering Research}, url = {https://scholar.google.co.in/citations?user=5wxReHAAAAAJ\&hl=en$\#$d=gs_md_cita-d\&u=\%2Fcitations\%3Fview_op\%3Dview_citation\%26hl\%3Den\%26user\%3D5wxReHAAAAAJ\%26citation_for_view\%3D5wxReHAAAAAJ\%3Ad1gkVwhDpl0C\%26tzom\%3D300}, author = {Dheeraj Singh, and Geetali Tilak} } @article {2019, title = {Examples of artificial intelligence in education}, year = {2019}, keywords = {process automation}, url = {https://emerj.com/ai-sector-overviews/examples-of-artificial-intelligence-in-education/}, author = {Daniel Faggella} } @article {2019, title = {Exploring and developing policies to future proof Washington{\textquoteright}s workers and businesses}, year = {2019}, institution = {Workforce Training and Education Coordinating Board}, url = {http://www.wtb.wa.gov/Documents/FutureofWork2018Report.pdf}, author = {Joe Wilcox and Lew McMurran} } @article {2019, title = {An Extensive Review on Recent Emerging Applications of Artificial Intelligence}, journal = {Asia-pacific Journal of Convergent Research Interchange}, volume = {5}, year = {2019}, month = {Jun-06-2021}, pages = {79 - 88}, issn = {25089080}, doi = {10.21742/apjcri10.21742/apjcri.2019.0610.21742/apjcri.2019.06.09}, url = {http://www.apjcri.org/papers/v5n2/9.pdf}, author = {Harini, B} } @conference {2019, title = {Fairer but not fair enough on the equitability of knowledge tracing}, booktitle = {the 9th International ConferenceProceedings of the 9th International Conference on Learning Analytics \& Knowledge - LAK19}, year = {2019}, pages = {335 - 339}, publisher = {ACM Press}, organization = {ACM Press}, address = {Tempe, AZ, USANew York, New York, USA}, isbn = {9781450362566}, doi = {10.1145/3303772.3303838}, author = {Doroudi, Shayan and Brunskill, Emma} } @book {2019, title = {The fourth industrial revolution: Trends and impacts on the world of work}, year = {2019}, pages = {177 - 194}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-94531-6}, doi = {10.1007/978-3-319-94532-3_115}, author = {Kim, Sang Yun}, editor = {McGrath, Simon and Mulder, Martin and Papier, Joy and Suart, Rebecca} } @article {2019, title = {From immigrants to robots: The changing locus of substitutes for workers}, year = {2019}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w25438}, url = {http://www.nber.org/papers/w25438.pdf}, author = {Borjas, George and Freeman, Richard} } @article {2019, title = {The future digital work force: Robotic process automation (RPA)}, journal = {Journal of Information Systems and Technology Management}, volume = {16}, year = {2019}, month = {Apr-01-2019}, doi = {10.4301/S1807-1775201916001}, author = {Madakam, Somayya and M. Holmukhe, Rajesh and Kumar Jaiswal, Durgesh} } @article {2019, title = {The future of health care: Protocol for measuring the potential of task automation grounded in the national health service primary care system}, journal = {JMIR Research Protocols}, volume = {8}, year = {2019}, month = {Jan-01-2019}, pages = {e11232}, doi = {10.2196/11232}, author = {Willis, Matthew and Duckworth, Paul and Coulter, Angela and Meyer, Eric T and Osborne, Michael} } @conference {2019, title = {The future of human-AI collaboration: A taxonomy of design knowledge for hybrid intelligence systems}, booktitle = {Hawaii International Conference on System Sciences (HICSS)}, year = {2019}, month = {09/2018}, abstract = {Recent technological advances, especially in the field of machine learning, provide astonishing progress on the road towards artificial general intelligence. However, tasks in current real-world business applications cannot yet be solved by machines alone. We, therefore, identify the need for developing socio-technological ensembles of humans and machines. Such systems possess the ability to accomplish complex goals by combining human and artificial intelligence to collectively achieve superior results and continuously improve by learning from each other. Thus, the need for structured design knowledge for those systems arises. Following a taxonomy development method, this article provides three main contributions: First, we present a structured overview of interdisciplinary research on the role of humans in the machine learning pipeline. Second, we envision hybrid intelligence systems and conceptualize the relevant dimensions for system design for the first time. Finally, we offer useful guidance for system developers during the implementation of such applications.}, url = {https://www.alexandria.unisg.ch/publications/254994}, author = {Dominik Dellermann and Adrian Calma and Nikolaus Lipusch and Thorsten Weber and Sascha Weigel and Philipp Ebel} } @article {2019, title = {The future of the work in America}, year = {2019}, month = {07/2019}, keywords = {consulting reports}, url = {https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-in-america-people-and-places-today-and-tomorrow}, author = {Susan Lund and James Manyika and Liz Hilton Segal and Andre Dua and Bryan Hancock and Scott Rutherford and Brent Macon} } @article {2019, title = {The future of women at work}, volume = {McKinsey Global Institute}, year = {2019}, month = {06/2019}, keywords = {consulting reports}, url = {https://www.mckinsey.com/~/media/mckinsey/featured\%20insights/gender\%20equality/the\%20future\%20of\%20women\%20at\%20work\%20transitions\%20in\%20the\%20age\%20of\%20automation/mgi-the-future-of-women-at-work-full-report-june\%202019.ashx}, author = {Anu Madgavkar and James Manyika and Mekala Krishnan and Kweilin Ellingrud and Lareina Yee and Jonathan Woetzel and Michael Chui and Vivian Hunt and Sruti Balakrishnan} } @article {2019, title = {Future of work initiatives promise lots of noise and lots of activity, but to what end?}, year = {2019}, url = {https://sloanreview.mit.edu/article/reframing-the-future-of-work/}, author = {Jeff Schwartz and John Hagel III and Maggie Wooll and Kelly Monahan} } @article {2019, title = {Getting ready for a post-work future}, journal = {Foresight and STI Governance}, volume = {13}, year = {2019}, month = {Jun-03-2021}, pages = {19 - 30}, doi = {10.17323/2500-2597.2019.1.19.30}, author = {Hines, Andy} } @article {2019, title = {Global commission on the future of work}, year = {2019}, institution = {International Labour Organization }, keywords = {government reports}, url = {https://www.ilo.org/global/topics/future-of-work/WCMS_569528/lang--en/index.htm}, author = {Cyril Ramaphosa and Stefan Lofven} } @article {2019, title = {Google{\textquoteright}s head of translation on fighting bias in language and why AI loves religious texts}, year = {2019}, url = {https://www.theverge.com/2019/1/30/18195909/google-translate-ai-machine-learning-bias-religion-macduff-hughes-interview}, author = {James Vincent} } @proceedings {2019, title = {The governance of artificial intelligence}, year = {2019}, month = {05/2019}, keywords = {AI use cases}, url = {https://www.bankofengland.co.uk/-/media/boe/files/speech/2019/managing-machines-the-governance-of-artificial-intelligence-speech-by-james-proudman}, author = {James Proudman} } @article {2019, title = {Governance of artificial intelligence and personal health information}, journal = {Digital Policy, Regulation and Governance}, volume = {21}, year = {2019}, month = {Jan-05-2020}, pages = {280 - 290}, issn = {2398-5038}, doi = {10.1108/DPRG-08-2018-0048}, author = {Winter, Jenifer Sunrise and Davidson, Elizabeth} } @article {2019, title = {Higher education in the age of Artificial Intelligence}, journal = {Postdigital Science and Education}, volume = {1}, year = {2019}, month = {Jan-04-2019}, pages = {236 - 239}, issn = {2524-485X}, doi = {10.1007/s42438-018-0005-8}, author = {Sudlow, Brian} } @article {2019, title = {How 5 data dynamos do their jobs}, year = {2019}, url = {https://www.nytimes.com/2019/06/12/reader-center/data-reporting-spreadsheets.html}, author = {Lindsey Rogers Cook} } @book {2019, title = {How artificial intelligence and machine learning can impact market design}, year = {2019}, pages = {567 - 586}, publisher = {University of Chicago Press}, organization = {University of Chicago Press}, isbn = {9780226613338}, doi = {10.7208/chicago/9780226613475.003.0023}, author = {Agrawal, Ajay and Gans, Joshua and Goldfarb, Avi} } @article {2019, title = {How big data is changing the job market}, year = {2019}, url = {https://www.dropbox.com/sh/8sxki5mwikjxlte/AAB6zvW5F0s2FIJ6jUmEW7P-a/Popular\%20press\%20about\%20impacts?dl=0\&preview=How+Big+Data+Is+Changing+the+Job+Market.pdf\&subfolder_nav_tracking=1}, author = {Editorial Team} } @article {2019, title = {How frightened should we be of AI ? }, year = {2019}, url = {https://www.newyorker.com/books/double-take/sunday-reading-the-rise-of-artificial-intelligence}, author = {Tad Friend} } @conference {2019, title = {How May I Help You? {\textendash} State of the Art and Open Research Questions for Chatbots at the Digital Workplace}, booktitle = {Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences}, year = {2019}, publisher = {Hawaii International Conference on System Sciences}, organization = {Hawaii International Conference on System Sciences}, isbn = {978-0-9981331-2-6}, doi = {10.24251/HICSS.2019.013}, author = {Meyer von Wolff, Raphael and Hobert, Sebastian and Schumann, Matthias} } @article {2019, title = {How one scientist coped when AI beat him at his life{\textquoteright}s work}, year = {2019}, url = {https://www.vox.com/future-perfect/2019/2/15/18226493/deepmind-alphafold-artificial-intelligence-protein-folding}, author = {Sigal Samuel} } @conference {2019, title = {How Smart is your Manufacturing? Build Smarter with AI}, booktitle = {2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC)2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC)}, year = {2019}, pages = {55 - 60}, publisher = {IEEE}, organization = {IEEE}, address = {Milwaukee, WI, USA}, isbn = {978-1-7281-2607-4}, doi = {10.1109/COMPSAC.2019.10183}, author = {Mcmahon, Mike and Mumper, Dale and Ihaza, Mitsuko and Farrar, Dominic} } @proceedings {2019, title = {How to Streamline AI Application in Government? A Case Study on Citizen Participation in Germany}, volume = {Lecture Notes in Computer Science 11685}, year = {2019}, pages = {233-247}, publisher = {Springer International Publishing}, address = {Cham}, abstract = {Artificial intelligence (AI) technologies are on the rise in almost every aspect of society, business and government. Especially in government, it is of interest how the application of AI can be streamlined: at least, in a controlled environment, in order to be able to evaluate potential (positive and negative) impact. Unfortunately, reuse in development of AI applications and their evaluation results lack interoperability and transferability. One potential remedy to this challenge would be to apply standardized artefacts: not only on a technical level, but also on an organization or semantic level. This paper presents findings from a qualitative explorative case study on online citizen participation in Germany that reveal insights on the current standardization level of AI applications. In order to provide an in-depth analysis, the research involves evaluation of two particular AI approaches to natural language processing. Our findings suggest that standardization artefacts for streamlining AI application exist predominantly on a technical level and are still limited.}, isbn = {978-3-030-27324-8}, issn = {0302-9743}, doi = {10.1007/978-3-030-27325-5}, author = {Balta, Dian and Kuhn, Peter and Sellami, Mahdi and Kulus, Daniel and Lieven, Claudius and Krcmar, Helmut}, editor = {Lindgren, Ida and Janssen, Marijn and Lee, Habin and Polini, Andrea and Rodr{\'\i}guez Bol{\'\i}var, Manuel Pedro and Scholl, Hans Jochen and Tambouris, Efthimios} } @article {2019, title = {Human resource technology disruptions and their implications for human resources management in healthcare organizations}, journal = {BMC Health Services Research}, volume = {19}, year = {2019}, month = {Jan-12-2019}, doi = {10.1186/s12913-019-4068-3}, author = {Tursunbayeva, Aizhan} } @article {2019, title = {Hybrid Intelligence}, journal = {Business \& Information Systems Engineering}, volume = {61}, year = {2019}, month = {Jan-10-2019}, pages = {637 - 643}, issn = {2363-7005}, doi = {10.1007/s12599-019-00595-2}, author = {Dellermann, Dominik and Ebel, Philipp and S{\"o}llner, Matthias and Leimeister, Jan Marco} } @conference {2019, title = {IBM Talent Management Solutions The role of AI in mitigating bias to enhance diversity and inclusion}, year = {2019}, note = {In this paper, we examine the nature of diversity and inclusion (D\&I), explore biases as an inhibitor to more diverse and inclusive workplaces, and provide insights into the role that AI can play in mitigating biases. We then offer practical recommendations to organizations who are looking to adopt AI in their HR practices.}, month = {03/2019}, url = {https://www.ibm.com/downloads/cas/2DZELQ4O}, author = {Haiyan Zhang and Sheri Feinzi and Louise Raisbec and Iain McCombe and Nigel Guenol and Jenny Montalt and Kimberley Messe} } @article {2019, title = {The impact of automation technologies for employment in Northern Ireland}, year = {2019}, publisher = {Nevin Economic Research Institute}, keywords = {economics of automation}, url = {https://www.nerinstitute.net/research/the-future-of-work-the-impact-of-automation-techno-1/}, author = {Lisa Wilson and Paul Mac Flynn} } @article {2019, title = {The impact of emerging technologies on work: a review of the evidence and implications for the human resource function}, journal = {Emerald Open Research}, volume = {1}, year = {2019}, month = {Jan-01-2019}, pages = {5}, doi = {10.12688/emeraldopenres.12907.1}, author = {Parry, Emma and Battista, Valentina} } @conference {2019, title = {Impacts of Artificial Intelligence on Public Administration: A Systematic Literature Review}, booktitle = {2019 14th Iberian Conference on Information Systems and Technologies (CISTI)}, year = {2019}, isbn = {978-989-98434-9-3}, url = {https://ieeexplore.ieee.org/document/8760778}, author = {Jo{\~a}o Reis and Paula Esp{\'\i}rito Santo and Lisbon, Portugal and Nuno Mel{\~a}o} } @proceedings {9999, title = {Impacts of machine learning on work}, year = {2019}, address = {Wailea, HI}, abstract = {

The increased pervasiveness of technological advancements in automation makes it urgent to address the question of how work is changing in response. Focusing on applications of machine learning (ML) that automate information tasks, we present a simple framework for identifying the impacts of an automated system on a task. From an analysis of popular press articles about ML, we develop 3 patterns for the use of ML--decision support, blended decision making and complete automation--with implications for the kinds of tasks and systems. We further consider how automation of one task might have implications for other interdependent tasks. Our main conclusion is that designers have a range of options for systems and that automation of tasks is not the same as automation of work.

}, keywords = {artificial intelligence, automation, machine learning, work design}, doi = {10.24251/HICSS.2019.719}, url = { http://hdl.handle.net/10125/60031}, attachments = {https://waim.network/sites/crowston.syr.edu/files/Impacts_of_machine_learning_on_work__revision_.pdf}, author = {Kevin Crowston and Bolici, Francesco} } @article {2019, title = {In the age of the smart artificial intelligence: AI{\textquoteright}s dual capacities for automating and informating work}, journal = {Business Information Review}, year = {2019}, month = {Dec-10-2020}, pages = {026638211988399}, publisher = {Sage}, abstract = {Recent developments in artificial intelligence (AI) have generated tidal waves, which are shaking the foundation of organizations and businesses. Even though AI is considered an unprecedented disruptive force for work automation, much can be learned from current research on the computerization of work. Drawing on the seminal work of Shoshana Zuboff, this article provides a balanced perspective on the dual affordances of AI systems for automating and informating work. Whereas AI offers unique capacities for automating cognitive work that once required high-skill workers, it may be a source of unintended consequences such as cognitive complacency or de-skilling workers. To overcome such effects, the informating capacities of AI systems can be invoked to augment work, generate a more comprehensive perspective on organization, and finally equip workers with new sets of intellectual skills. }, keywords = {Algorithmic management, artificial intelligence, augmentation, automating, informating, intelligent machine}, issn = {0266-3821}, doi = {10.1177/0266382119883999}, url = {https://journals.sagepub.com/doi/abs/10.1177/0266382119883999}, attachments = {https://waim.network/sites/crowston.syr.edu/files/In\%20the\%20Age\%20of\%20the\%20Smart\%20Artificial\%20Intelligence\%20AI\%E2\%80\%99s\%20Dual\%20Capacities\%20for\%20Automating\%20and\%20Informating.pdf}, author = {Jarrahi, Mohammad Hossein} } @conference {2019, title = {Inferring work task automatability from AI expert evidence}, booktitle = {the 2019 AAAI/ACM ConferenceProceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society - AIES {\textquoteright}19}, year = {2019}, pages = {485 - 491}, publisher = {ACM Press}, organization = {ACM Press}, address = {Honolulu, HI, USANew York, New York, USA}, isbn = {9781450363242}, doi = {10.1145/330661810.1145/3306618.3314247}, author = {Duckworth, Paul and Graham, Logan and Osborne, Michael} } @article {2019, title = {Integrating ethical values and economic value to steer progress in Artificial Intelligenc}, year = {2019}, month = {08/2019}, keywords = {ethics}, url = {https://www.nber.org/papers/w26130}, author = {Anton Korinek} } @article {2019, title = {Introduction: The Future of Jobs in an Increasingly Autonomous Economy}, journal = {Journal of Management Inquiry}, volume = {28}, year = {2019}, month = {Jun-07-2021}, pages = {298 - 299}, issn = {1056-4926}, doi = {10.1177/1056492619827373}, author = {Choi, David Y. and Kang, Jae Hyeung} } @article {2019, title = {Labor, technology and work organization: An introduction to the forum}, journal = {Journal of Industrial and Business Economics}, volume = {46}, year = {2019}, month = {Jan-09-2019}, pages = {313 - 321}, issn = {0391-2078}, doi = {10.1007/s40812-019-00126-w}, author = {Cirillo, Valeria and Molero Zayas, Jos{\'e}} } @article {2019, title = {A machine is cheaper than a human for the same task}, journal = {AI \& SOCIETY}, year = {2019}, month = {Feb-01-2019}, issn = {0951-5666}, doi = {10.1007/s00146-018-0874-0}, author = {Pereira, Lu{\'\i}s Moniz} } @article {2019, title = {Machine learning concepts, concerns and opportunities for a pediatric radiologist}, journal = {Pediatric Radiology}, volume = {49}, year = {2019}, month = {Jan-04-2019}, pages = {509 - 516}, issn = {0301-0449}, doi = {10.1007/s00247-018-4277-7}, author = {Moore, Michael M. and Slonimsky, Einat and Long, Aaron D. and Sze, Raymond W. and Iyer, Ramesh S.} } @inbook {2019, title = {Machine learning for clinical psychology and clinical neuroscience}, booktitle = {researchgate.net}, year = {2019}, abstract = {A rapid growth in computational power and an increasing availability of large, publicly-accessible, multimodal datasets present new opportunities for psychology and neuroscience researchers to ask novel questions, and to approach old questions in novel ways. Studies of the personal characteristics, situation-specific factors, and sociocultural contexts that result in the onset, development, maintenance, and remission of psychopathology, are particularly well-suited to benefit from machine learning methods. However, introductory textbooks for machine learning rarely tailor their guidance to the needs of psychology and neuroscience researchers. Similarly, the traditional statistical training of clinical scientists often does not incorporate these approaches. This chapter acts as an introduction to machine learning for researchers in the fields of clinical psychology and clinical neuroscience. We discuss these methods, illustrated through real and hypothetical applications in the fields of clinical psychology and clinical neuroscience. We touch on study design, selecting appropriate techniques, how (and how not) to interpret results, and more, to aid researchers who are interested in applying machine learning methods to clinical science data.}, url = {https://www.researchgate.net/publication/331000572_Machine_Learning_for_Clinical_Psychology_and_Clinical_Neuroscience}, author = {Marc N. Countanche and Lauren S. Hallion} } @conference {2019, title = {Machine learning in Artificial Intelligence: Towards a common understanding}, booktitle = {Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences}, year = {2019}, publisher = {Hawaii International Conference on System Sciences}, organization = {Hawaii International Conference on System Sciences}, doi = {10.24251/HICSS.2019.630}, author = {K{\"u}hl, Niklas and Goutier, Marc and Hirt, Robin and Satzger, Gerhard} } @article {2019, title = {A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic}, journal = {JCO Clinical Cancer Informatics}, year = {2019}, month = {Jan-04-2019}, pages = {1 - 17}, issn = {2473-4276}, doi = {10.1200/CCI.18.00056}, author = {Salvucci, Manuela and Rahman, Arman and Resler, Alexa J. and Udupi, Girish M. and McNamara, Deborah A. and Kay, Elaine W. and Laurent-Puig, Pierre and Longley, Daniel B. and Johnston, Patrick G. and Lawler, Mark and Wilson, Richard and Salto-Tellez, Manuel and Van Schaeybroeck, Sandra and Rafferty, Mairin and Gallagher, William M. and Rehm, Markus and Prehn, Jochen H.M.} } @article {2019, title = {Managing Machines: The governance of artificial intelligence}, year = {2019}, url = {https://www.bankofengland.co.uk/speech/2019/james-proudman-speech-at-fca-conference-on-governance-in-banking-london}, author = {James Proudman} } @article {2019, title = {Marketing AI recruitment: The next phase in job application and selection}, journal = {Computers in Human Behavior}, volume = {90}, year = {2019}, month = {Jan-01-2019}, pages = {215 - 222}, issn = {07475632}, doi = {10.1016/j.chb.2018.09.009}, author = {van Esch, Patrick and Black, J. Stewart and Ferolie, Joseph} } @article {2019, title = {Massive technological unemployment without redistribution: A case for cautious optimism}, journal = {Science and Engineering Ethics}, volume = {25}, year = {2019}, month = {Jan-10-2019}, pages = {1389 - 1407}, issn = {1353-3452}, doi = {10.1007/s11948-018-0070-0}, author = {Chomanski, Bartek} } @article {2019, title = {Mitigating bias in algorithmic employment screening: Evaluating claims and practices}, year = {2019}, abstract = {

There has been rapidly growing interest in the use of algorithms for employment assessment,especially as a means to address or mitigate bias in hiring. Yet, to date, little is known abouthow these methods are being used in practice. How are algorithmic assessments built, vali-dated, and examined for bias? In this work, we document and assess the claims and practicesof companies offering algorithms for employment assessment, using a methodology that can beapplied to evaluate similar applications and issues of bias in other domains. In particular, weidentify vendors of algorithmic pre-employment assessments (i.e., algorithms to screen candi-dates), document what they have disclosed about their development and validation procedures,and evaluate their techniques for detecting and mitigating bias. We find that companies{\textquoteright} for-mulation of {\textquotedblleft}bias{\textquotedblright} varies, as do their approaches to dealing with it. We also discuss the variouschoices vendors make regarding data collection and prediction targets, in light of the risks andtrade-offs that these choices pose. We consider the implications of these choices and we raise anumber of technical and legal considerations.

}, keywords = {social power of algorithms}, url = {https://www.researchgate.net/publication/333971698_Mitigating_Bias_in_Algorithmic_Employment_Screening_Evaluating_Claims_and_Practices}, author = {Manish Raghavan and Solon Barocas and Jon KleinbergKaren Levy} } @article {2019, title = {The moderating roles of perceived organizational support and competitive psychological climate}, journal = {Tourism Management}, volume = {73}, year = {2019}, month = {Jan-08-2019}, pages = {172 - 181}, issn = {02615177}, doi = {10.1016/j.tourman.2019.02.006}, author = {Li, Jun (Justin) and Bonn, Mark A. and Ye, Ben Haobin} } @book {2019, title = {Moral reasoning at work automation and ethics}, year = {2019}, pages = {69 - 77}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-15190-4}, url = {10.1007/978-3-030-15191-1_8}, author = {Kvalnes, {\O}yvind and Kvalnes, {\O}yvind} } @article {2019, title = {Negotiated and reciprocal exchange structures in human-agent cooperation}, journal = {Computers in Human Behavior}, volume = {90}, year = {2019}, month = {Jan-01-2019}, pages = {288 - 297}, issn = {07475632}, doi = {10.1016/j.chb.2018.08.012}, author = {Chiou, Erin K. and Lee, John D. and Su, Tianshuo} } @article {2019, title = {Net job creation in an increasingly autonomous economy: The challenge of a generation}, journal = {Journal of Management Inquiry}, volume = {28}, year = {2019}, month = {Jun-07-2021}, pages = {300 - 305}, issn = {1056-4926}, doi = {10.1177/1056492619827372}, author = {Choi, David Y. and Kang, Jae Hyeung} } @article {2019, title = {Nurses{\textquoteright} Views on the Potential Use of Robots in the Pediatric Unit}, journal = {Journal of Pediatric Nursing}, volume = {47}, year = {2019}, month = {Jan-07-2019}, pages = {e58 - e64}, issn = {08825963}, doi = {10.1016/j.pedn.2019.04.027}, author = {Liang, Hwey-Fang and Wu, Kuang-Ming and Weng, Cheng-Hsing and Hsieh, Hui-Wen} } @article {2019, title = {Physician perspectives on integration of artificial intelligence into diagnostic pathology}, journal = {npj Digital Medicine}, volume = {2}, year = {2019}, month = {Jan-12-2019}, doi = {10.1038/s41746-019-0106-0}, author = {Sarwar, Shihab and Dent, Anglin and Faust, Kevin and Richer, Maxime and Djuric, Ugljesa and Van Ommeren, Randy and Diamandis, Phedias} } @article {2019, title = {Pooling knowledge through artificial swarm intelligence to improve business decision making}, journal = {California Management Review}, volume = {61}, year = {2019}, month = {Sep-08-2019}, pages = {84 - 109}, issn = {0008-1256}, doi = {10.1177/0008125619862256}, author = {Metcalf, Lynn and Askay, David A. and Rosenberg, Louis B.} } @article {2019, title = {The potential for artificial intelligence in healthcare}, journal = {Future Healthcare Journal}, volume = {6}, year = {2019}, month = {Jan-06-2020}, pages = {94 - 98}, issn = {2514-6645}, doi = {10.7861/futurehosp.6-2-94}, author = {Davenport, Thomas and Kalakota, Ravi} } @article {2019, title = {Precarious lives: Job insecurity and well-being in rich democracies}, journal = {Social Forces}, volume = {97}, year = {2019}, month = {Jun-04-2019}, pages = {e1 - e3}, issn = {0037-7732}, doi = {10.1093/sf/soz022}, author = {Pugh, Allison J} } @article {2019, title = {The present and future of deep learning in radiology}, journal = {European Journal of Radiology}, volume = {114}, year = {2019}, month = {Jan-05-2019}, pages = {14 - 24}, issn = {0720048X}, doi = {10.1016/j.ejrad.2019.02.038}, url = {https://doi.org/10.1016/j.ejrad.2019.02.038}, author = {Saba, Luca and Biswas, Mainak and Kuppili, Venkatanareshbabu and Cuadrado Godia, Elisa and Suri, Harman S. and Edla, Damodar Reddy and Omerzu, Toma{\v z} and Laird, John R. and Khanna, Narendra N. and Mavrogeni, Sophie and Protogerou, Athanasios and Sfikakis, Petros P. and Viswanathan, Vijay and Kitas, George D. and Nicolaides, Andrew and Gupta, Ajay and Suri, Jasjit S.} } @article {2019, title = {Primer on artificial intelligence and robotics}, journal = {Journal of Organization Design}, volume = {8}, year = {2019}, month = {Jan-12-2019}, doi = {10.1186/s41469-019-0050-0}, author = {Raj, Manav and Seamans, Robert} } @article {2019, title = {Questions for artificial intelligence in health care}, journal = {JAMA}, volume = {321}, year = {2019}, month = {Jan-01-2019}, pages = {31}, issn = {0098-7484}, doi = {10.1001/jama.2018.18932}, author = {Maddox, Thomas M. and Rumsfeld, John S. and Payne, Philip R. O.} } @article {2019, title = {The Rebirth of CAD: How Is Modern AI Different from the CAD We Know?}, journal = {Radiology: Artificial Intelligence}, volume = {1}, year = {2019}, month = {Jan-05-2019}, pages = {e180089}, doi = {10.1148/ryai.2019180089}, author = {Oakden-Rayner, Luke} } @mastersthesis {2019, title = {Recruiters just wanna have AI?}, year = {2019}, edition = {Spring semester 2019}, url = {https://liu.diva-portal.org/smash/get/diva2:1333711/FULLTEXT01.pdf}, author = {Hannimari Savola and Bijona Troqe} } @article {2019, title = {A Review of the Social Impacts and Ethical Implications of Artificial Intelligence}, year = {2019}, publisher = {Global AI Ethics}, keywords = {ethics}, url = {https://arxiv.org/ftp/arxiv/papers/1907/1907.07892.pdf}, author = {Alexa Hagerty and Igor Rubinov} } @article {2019, title = {The rise of robots! Effects on employment and income}, journal = {{\"O}neri Dergisi}, year = {2019}, month = {Jun-02-2019}, pages = {1 - 17}, issn = {1300-0845}, doi = {10.14783/maruoneri.vi.522005}, author = {{\"O}ZCAN, Rasim} } @article {2019, title = {Rise of the Machines: Advances in Deep Learning for Cancer Diagnosis}, journal = {Trends in Cancer}, volume = {5}, year = {2019}, month = {Jan-03-2019}, pages = {157 - 169}, issn = {24058033}, doi = {10.1016/j.trecan.2019.02.002}, author = {Levine, Adrian B. and Schlosser, Colin and Grewal, Jasleen and Coope, Robin and Jones, Steve J.M. and Yip, Stephen} } @conference {2019, title = {The roles of initiated and received task interdependence}, booktitle = {Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences}, year = {2019}, publisher = {Hawaii International Conference on System Sciences}, organization = {Hawaii International Conference on System Sciences}, doi = {10.24251/HICSS.2019.119}, author = {Berntzen, Marthe and Wong, Sut I} } @article {2019, title = {Scaling up analogical innovation with crowds and AI}, journal = {Proceedings of the National Academy of Sciences}, volume = {116}, year = {2019}, pages = {1870-1877}, issn = {0027-8424}, doi = {10.1073/pnas.1807185116}, author = {Kittur, Aniket and Yu, Lixiu and Hope, Tom and Chan, Joel and Lifshitz-Assaf, Hila and Gilon, Karni and Ng, Felicia and Kraut, Robert E. and Shahaf, Dafna} } @article {2019, title = {The solution lies in education: Artificial intelligence \& the skills gap}, journal = {On the Horizon}, volume = {27}, year = {2019}, month = {Nov-03-2019}, pages = {1 - 4}, issn = {1074-8121}, doi = {10.1108/OTH-03-2019-096}, author = {Chrisinger, David} } @book {2019, title = {Steps toward a scaffolding design framework}, year = {2019}, pages = {149 - 161}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-12333-8}, issn = {1571-5035}, doi = {10.1007/978-3-030-12334-5_5}, author = {Correia, Ant{\'o}nio and Jameel, Shoaib and Paredes, Hugo and Fonseca, Benjamim and Schneider, Daniel}, editor = {Khan, Vassillis-Javed and Papangelis, Konstantinos and Lykourentzou, Ioanna and Markopoulos, Panos} } @article {2019, title = {A study of artificial intelligence and it{\textquoteright}s role on human resource management}, journal = {International Journal of Research and Analytical Review}, volume = {6}, year = {2019}, url = {https://www.researchgate.net/publication/331596981_A_Study_of_Artificial_Intelligence_and_its_role_in_Human_Resource_Management}, author = {Vivek V. Yawalkar} } @article {2019, title = {Synthesis of Strategies for Robotic Process Automation}, year = {2019}, url = {http://ceur-ws.org/Vol-2400/paper-53.pdf}, author = {Simone Agostinelli} } @book {2019, title = {Technology and Work Worth Doing (Not Jobs) Post-AlphaGo: A World-Building Workshop on the Future of Artificial Intelligence}, year = {2019}, publisher = {RAND Corporation}, organization = {RAND Corporation}, doi = {10.7249/CF398}, author = {Pendleton-Jullian, Ann and Lempert, Robert} } @article {2019, title = {Ten ways the precautionary principle undermines progress in artificial intelligence}, year = {2019}, month = {02/2019}, keywords = {consulting reports}, url = {https://itif.org/publications/2019/02/04/ten-ways-precautionary-principle-undermines-progress-artificial-intelligence}, author = {Daniel Castro and Michael McLaughlin} } @article {2019, title = {There is no general AI: Why Turing machines cannot pass the Turing test}, year = {2019}, url = {https://arxiv.org/abs/1906.05833}, author = {Jobst Landgrebe} } @article {2019, title = {Is this time different? A note on automation and labour in the fourth industrial revolution}, journal = {Journal of Industrial and Business Economics}, volume = {46}, year = {2019}, month = {Jan-09-2019}, pages = {323 - 331}, keywords = {economics of automation}, issn = {0391-2078}, doi = {10.1007/s40812-019-00123-z}, author = {Marengo, Luigi} } @article {2019, title = {Is this time different? How digitalization influences job creation and destruction}, journal = {Research Policy}, volume = {48}, year = {2019}, month = {Jan-10-2019}, pages = {103765}, issn = {00487333}, doi = {10.1016/j.respol.2019.03.010}, author = {Balsmeier, Benjamin and Woerter, Martin} } @article {2019, title = {{\textquotedblleft}This time may be a little different{\textquotedblright} {\textendash} exploring the Finnish view on the future of work}, journal = {International Journal of Sociology and Social Policy}, volume = {39}, year = {2019}, month = {Nov-03-2019}, pages = {22 - 37}, issn = {0144-333X}, doi = {10.1108/IJSSP-05-2018-0070}, author = {Pulkka, Ville-Veikko} } @book {2019, title = {Toward a conceptual framework for understanding AI action and legal reaction}, volume = {11489}, year = {2019}, pages = {453 - 459}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-18304-2}, issn = {0302-9743}, doi = {10.1007/978-3-030-18305-9_44}, author = {Dahya, Raheena and Morris, Alexis}, editor = {Meurs, Marie-Jean and Rudzicz, Frank} } @article {Frank2019, title = {Toward understanding the impact of artificial intelligence on labor}, journal = {Proceedings of the National Academy of Sciences}, volume = {116}, year = {2019}, month = {apr}, pages = {6531{\textendash}6539}, abstract = {

Rapid advances in artificial intelligence (AI) and automation technologies have the potential to significantly disrupt labor markets. While AI and automation can augment the productivity of some workers, they can replace the work done by others and will likely transform almost all occupations at least to some degree. Rising automation is happening in a period of growing economic inequality, raising fears of mass technological unemployment and a renewed call for policy efforts to address the consequences of technological change. In this paper we discuss the barriers that inhibit scientists from measuring the effects of AI and automation on the future of work. These barriers include the lack of high-quality data about the nature of work (e.g., the dynamic requirements of occupations), lack of empirically informed models of key microlevel processes (e.g., skill substitution and human{\textendash}machine complementarity), and insufficient understanding of how cognitive technologies interact with broader economic dynamics and institutional mechanisms (e.g., urban migration and international trade policy). Overcoming these barriers requires improvements in the longitudinal and spatial resolution of data, as well as refinements to data on workplace skills. These improvements will enable multidisciplinary research to quantitatively monitor and predict the complex evolution of work in tandem with technological progress. Finally, given the fundamental uncertainty in predicting technological change, we recommend developing a decision framework that focuses on resilience to unexpected scenarios in addition to general equilibrium behavior.

}, issn = {0027-8424}, doi = {10.1073/pnas.1900949116}, url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1900949116}, author = {Frank, Morgan R and Autor, David and Bessen, James E and Brynjolfsson, Erik and Cebrian, Manuel and Deming, David J and Feldman, Maryann and Groh, Matthew and Lobo, Jos{\'e} and Moro, Esteban and Wang, Dashun and Youn, Hyejin and Rahwan, Iyad} } @article {2019, title = {Towards a smart automated society: Cognitive technologies, knowledge production, and economic growth}, journal = {Economics, Management, and Financial Markets}, volume = {14}, year = {2019}, month = {Jan-01-2019}, pages = {44}, issn = {1842-3191}, doi = {10.22381/EMFM14120195}, author = {Mitchell Udell and Vojtech Stehel and Tomas Kliestik and Jana Kliestikova and Pavol Durana} } @article {2019, title = {Towards an AI economy that works for all}, year = {2019}, month = {02/2019}, keywords = {ethics}, url = {https://www.keystoneresearch.org/sites/default/files/FOW_TowardAIEconomyForAllFinalEdit.pdf}, author = {Stephen Herzenberg and John Alic} } @article {2019, title = {Towards intelligent regulation of Artificial Intelligence}, journal = {European Journal of Risk Regulation}, volume = {10}, year = {2019}, month = {Jan-03-2019}, pages = {41 - 59}, issn = {1867-299X}, doi = {10.1017/err.2019.8}, author = {BUITEN, Miriam C} } @article {2019, title = {Transforming the communication between citizens and government through AI-guided chatbots}, journal = {Government Information Quarterly}, volume = {36}, year = {2019}, month = {Jan-04-2019}, pages = {358 - 367}, issn = {0740624X}, doi = {10.1016/j.giq.2018.10.001}, url = {https://doi.org/10.1016/j.giq.2018.10.001}, author = {Androutsopoulou, Aggeliki and Karacapilidis, Nikos and Loukis, Euripidis and Charalabidis, Yannis} } @article {2019, title = {Unsupervised by any other name: Hidden layers of knowledge production in artificial intelligence on social media}, journal = {Big Data \& Society}, volume = {6}, year = {2019}, month = {May-01-2019}, pages = {205395171881956}, issn = {2053-9517}, doi = {10.1177/2053951718819569}, author = {Bechmann, Anja and Bowker, Geoffrey C} } @article {2019, title = {Use of Artificial Intelligence to Improve Resilience and Preparedness Against Adverse Flood Events}, journal = {Water}, volume = {11}, year = {2019}, month = {Jan-05-2019}, pages = {973}, doi = {10.3390/w11050973}, author = {Saravi, Sara and Kalawsky, Roy and Joannou, Demetrios and Rivas Casado, Monica and Fu, Guangtao and Meng, Fanlin} } @article {2019, title = {Using artificial intelligence in health-system pharmacy practice: Finding new patterns that matter}, journal = {American Journal of Health-System Pharmacy}, volume = {76}, year = {2019}, month = {May-04-2020}, pages = {622 - 627}, issn = {1079-2082}, doi = {10.1093/ajhp/zxz018}, author = {Flynn, Allen} } @article {2019, title = {What happens when the jobs disappear?}, volume = {The Superintendent journal}, year = {2019}, url = {https://super.journalxr.com/journal/index.php/TSJ}, author = {Andrew Yang} } @article {2019, title = {Why artificial intelligence will not outsmart complex knowledge work}, journal = {Work, Employment and Society}, volume = {33}, year = {2019}, month = {Jan-12-2019}, pages = {1058 - 1067}, issn = {0950-0170}, doi = {10.1177/0950017018817489}, author = {Pettersen, Lene} } @conference {2019, title = {Why small data holds the key to the future of artificial intelligence}, booktitle = {8th International Conference on Data Science, Technology and ApplicationsProceedings of the 8th International Conference on Data Science, Technology and Applications}, year = {2019}, pages = {340 - 347}, publisher = {SCITEPRESS - Science and Technology Publications}, organization = {SCITEPRESS - Science and Technology Publications}, address = {Prague, Czech Republic}, doi = {10.5220/0007956203400347}, author = {Greco, Ciro and Polonioli, Andrea and Tagliabue, Jacopo} } @article {2019, title = {Why we are failing to understand the societal impact of artificial intelligence}, journal = {Social research: An international quarterly}, volume = {86}, year = {2019}, pages = {pp. 477-498}, url = {https://muse.jhu.edu/article/732186}, author = {Lorena Jaume-Palasi} } @article {2019, title = {Will Artificial Intelligence Replace Radiologists?}, journal = {Radiology: Artificial Intelligence}, volume = {1}, year = {2019}, month = {Jan-05-2019}, pages = {e190058}, doi = {10.1148/ryai.2019190058}, author = {Langlotz, Curtis P.} } @article {2019, title = {Will artificial intelligence take over human resources recruitment and selection?}, journal = {Network Intelligence Studies}, volume = {VII}, year = {2019}, keywords = {artificial intelligence, human resources information systems, recruitment and selection}, url = {https://ideas.repec.org/a/cmj/networ/y2019i13p21-30.html}, author = {Bilal Hmoud and Varallya Laszlo} } @article {2019, title = {Will machine learning end the viability of radiology as a thriving medical specialty?}, journal = {The British Journal of Radiology}, volume = {92}, year = {2019}, month = {Jan-02-2019}, pages = {20180416}, issn = {0007-1285}, doi = {10.1259/bjr.20180416}, author = {Chan, Stephen and Siegel, Eliot L} } @article {2018, title = {10 examples of Artificial Intelligence you{\textquoteright}re using in daily life}, year = {2018}, month = {09/2018}, url = {https://beebom.com/examples-of-artificial-intelligence/}, author = {Rachit Agarwal} } @article {2018, title = {16 examples of Artificial Intelligence in your everyday life}, year = {2018}, month = {10/2018}, url = {https://medium.com/@the_manifest/16-examples-of-artificial-intelligence-ai-in-your-everyday-life-655b2e6a49de}, author = {The Manifest} } @article {2018, title = {7 job skills of the future (That AI{\textquoteright}s and robots can{\textquoteright}t do better than humans)}, year = {2018}, month = {08/2018}, edition = {Enterprise Tech}, url = {https://www.forbes.com/sites/bernardmarr/2018/08/06/7-job-skills-of-the-future-that-ais-and-robots-cant-do-better-than-humans/$\#$da0ce596c2e9}, author = {Bernard Marr} } @article {2018, title = {7 things I learned from building an AI chatbot for leadership development}, year = {2018}, url = {https://www.forbes.com/sites/kevinkruse/2018/10/15/ai-chatbot-leadership-development-training-hr/$\#$206492515ff0}, author = {Kevin Kruse} } @article {2018, title = {7 things I learned from building an AI chatbot for leadership development}, year = {2018}, url = {https://www.forbes.com/sites/kevinkruse/2018/10/15/ai-chatbot-leadership-development-training-hr/$\#$206492515ff0}, author = {Kevin Kruse} } @article {2018, title = {Accounting for the neglected dimensions of AI progress}, journal = {data-efficient ML}, year = {2018}, url = {https://arxiv.org/abs/1806.00610}, author = {Fernando Martine-Plumed and Shahar Avin and Miles Brundage and Allan Dafoe and Sean O hEigeartaigh and Jos{\'e} Hern{\'a}ndez-Orallo} } @book {2018, title = {Advances in intelligent systems and computing}, series = {Proceedings of the 1st International Conference on Intelligent Human Systems Integration }, year = {2018}, url = {https://link.springer.com/book/10.1007/978-3-030-11051-2?page=2}, author = {Advances in Intelligent Systems and Computing 722 Waldemar Karwowski} } @article {2018, title = {Advances in the development of a cognitive user interface}, journal = {MATEC Web of Conferences}, volume = {161}, year = {2018}, month = {Jan-01-2018}, pages = {01003}, doi = {10.1051/matecconf/201816101003}, url = {https://www.matec-conferences.org/10.1051/matecconf/201816101003https://www.matec-conferences.org/10.1051/matecconf/201816101003/pdf}, author = {Jokisch, Oliver and Huber, Markus}, editor = {Ronzhin, A. and Shishlakov, V.} } @article {2018, title = {A.I. And big data could power a new war on poverty}, year = {2018}, month = {01/2018}, url = {https://www.nytimes.com/2018/01/01/opinion/ai-and-big-data-could-power-a-new-war-on-poverty.html}, author = {Elisabeth a. Mason} } @article {2018, title = {AI and the Economy}, year = {2018}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w24689}, author = {Furman, Jason and Seamans, Robert} } @conference {2018, title = {AI Assistants as Non-human Actors in Service Design}, booktitle = {21st DMI: Academic Design Management Conference}, year = {2018}, url = {https://www.researchgate.net/publication/326997609_AI_Assistants_as_Non-human_Actors_in_Service_Design?enrichId=rgreq-80a84e881501993f8b87a3d6387900aa-XXX\&enrichSource=Y292ZXJQYWdlOzMyNjk5NzYwOTtBUzo2NTkyMjU4MjI5MTY2MTBAMTUzNDE4MzA5Mjk2MQ\%3D\%3D\&el=1_x_2\&_}, author = {TiTitta Jylkastta Jylk{\"a}s and Mikko {\"A}ij{\"a}l{\"a} and Tytti Vuorikari and V{\'e}saal Rajab} } @article {2018, title = {AI: Augmentation, more so than automation}, year = {2018}, publisher = {Singapore Management University}, issn = {2315-4284}, url = {https://cmp.smu.edu.sg/ami/all}, author = {Steven Miller} } @article {2018, title = {AI Could Provide Moment-by-Moment Nursing for a Hospital{\textquoteright}s Sickest Patients}, year = {2018}, url = {https://globaltechnologies.ca/ai-could-provide-moment-by-moment-nursing-for-a-hospitals-sickest-patients/}, author = {Behnood Gholami and Wassim M. Haddad and James M. Bailey} } @article {2018, title = {AI is coming after highly skilled jobs, and it{\textquoteright}s meeting resistance}, journal = {venturebeat}, year = {2018}, keywords = {AI}, url = {https://venturebeat.com/2018/03/04/ai-is-coming-after-highly-skilled-jobs-and-its-meeting-resistance/}, author = {Sascha Eder} } @conference {2018, title = {AI risk mitigation through democratic governance}, booktitle = {the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES {\textquoteright}18}, year = {2018}, pages = {366 - 367}, publisher = {ACM Press}, organization = {ACM Press}, address = {New Orleans, LA, USANew York, New York, USA}, isbn = {9781450360128}, doi = {10.1145/3278721.3278801}, author = {Garvey, Colin} } @article {2018, title = {AI stumbles in the spotlight}, year = {2018}, note = {Artificial intelligence experts {\textemdash} concerned about reported blunders with high-stakes AI systems from makers like Amazon and IBM {\textemdash} are urging more oversight, testing, and perhaps a fundamental rethinking of the underlying technology.}, url = {https://www.axios.com/artificial-intelligence-mistakes-limitations-amazon-ibm-14014597-03e9-43e3-b224-a91205a232c1.html}, author = {Kaveh Waddell} } @article {2018, title = {Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review}, journal = {Journal of Affective Disorders}, volume = {241}, year = {2018}, pages = {519-532}, issn = {01650327}, doi = {10.1016/j.jad.2018.08.073}, author = {Lee, Yena and Ragguett, Renee-Marie and Mansur, Rodrigo B. and Boutilier, Justin J. and Rosenblat, Joshua D. and Trevizol, Alisson and Brietzke, Elisa and Lin, Kangguang and Pan, Zihang and Subramaniapillai, Mehala and Chan, Timothy C.Y. and Fus, Dominika and Park, Caroline and Musial, Natalie and Zuckerman, Hannah and Chen, Vincent Chin-Hung and Ho, Roger and Rong, Carola and McIntyre, Roger S.} } @mastersthesis {2018, title = {Archetypes of artificial intelligence utilization}, year = {2018}, note = {How companies create and capture value from a novel business technology}, url = {https://aaltodoc.aalto.fi/handle/123456789/33983}, author = {Selim Saukkomaa} } @article {2018, title = {Are You Working with AI or Being Replaced by AI?}, journal = {Radiology}, volume = {287}, year = {2018}, month = {Jan-05-2018}, pages = {365 - 366}, issn = {0033-8419}, doi = {10.1148/radiol.2018184007}, author = {Bluemke, David A.} } @conference {2018, title = {Artificial General Intelligence}, year = {2018}, url = {https://ivizlab.org/wp-content/uploads/sites/2/2018/09/TurnerDiPaola_2018_ArtificialGeneralIntelligence.pdf}, author = {Matthew Ikl{\'e} and Arthur Franz and Rafal Rzepka and Ben Goertzel} } @article {2018, title = {Artificial Intelligence: A Case Study on Risk Mitigation}, journal = {International Journal of Computer Science and Network Security}, volume = {18}, year = {2018}, month = {04/2018}, pages = {9-12}, abstract = {Artificial intelligence technologies are expanding at an extraordinary rate with wide range of applications from machine translation to medical image analysis. Many applications are being developed and there is no doubt that in the near future this will create substantial risk for humanity. In addition, Artificial intelligence is a dual use are of technology as it can be used toward useful of harmful ends, for example autonomous drones can be used to deliver packages faster and easier and on the other hand, they can be used to deliver explosives. This literature review research investigates different types of artificial intelligence risks and proposes ways to mitigate these risks.}, keywords = {AI application, artificial intelligence, Risk mitigation}, author = {Ahmed AL-Gindy} } @article {2018, title = {Artificial intelligence and privacy in the fourth industrial revolution}, year = {2018}, institution = {Institute for Philosophy \& Public Policy}, url = {https://www.wilsoncenter.org/sites/default/files/ai_and_privacy.pdf}, author = {Sarah W. Denton and Eleonore Pauwels} } @article {2018, title = {Artificial intelligence and sports journalism: Is it a sweeping change?}, journal = {Technology in Society}, year = {2018}, issn = {0160791X}, doi = {10.1016/j.techsoc.2018.03.001}, author = {Yair Galily} } @article {2018, title = {Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making}, journal = {Business Horizons}, volume = {61}, year = {2018}, publisher = {Elsevier}, edition = {586}, chapter = {577}, abstract = {Artificial intelligence (AI) has penetrated many organizational processes, resulting in a growing fear that smart machines will soon replace many humans in decision making. To provide a more proactive and pragmatic perspective, this article highlights the complementarity of humans and AI and examines how each can bring their own strength in organizational decision-making process typically characterized by uncertainty, complexity, and equivocality. WIth a greater computational information processing capacity and an analytical approach, AI can extend humans{\textquoteright} cognition when addressing complexity, whereas human can still offer a more holistic, intuitive approach in dealing with uncertainty and equivocality in organizational decision making. This premise mirrors the idea of intelligence augmentation, which states that AI systems should be designed with the intention of augmenting, not replacing, human contribution.}, keywords = {Analytical and intuitive decision making, artificial intelligence, Human augmentation, Human-machine symbiosis, Organization decision making}, doi = {10.1016/j.bushor.2018.03.007}, author = {Mohammad Hossein Jarrahi} } @article {2018, title = {Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making}, journal = {Business Horizons}, volume = {61}, year = {2018}, month = {Jan-07-2018}, pages = {577 - 586}, issn = {00076813}, doi = {10.1016/j.bushor.2018.03.007}, author = {Jarrahi, Mohammad Hossein} } @conference {2018, title = {Artificial Intelligence Applications and Innovations}, booktitle = {14th IFIP WG 12.5 International Conference, AIAI 2018}, year = {2018}, url = {https://www.springer.com/gp/book/9783319920153}, author = {Lazaros Iliadis and Ilias Maglogiannis and Vassilis Plagianakos} } @article {2018, title = {Artificial intelligence can transform the economy}, year = {2018}, month = {09/2018}, url = {https://www.washingtonpost.com/opinions/artificial-intelligence-can-transform-the-economy/2018/09/18/50c9c9c8-bab8-11e8-bdc0-90f81cc58c5d_story.html}, author = {Erik Brynjolfsson and Xiang Hui and Meng Liu} } @book {2018, title = {Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide}, volume = {537}, year = {2018}, pages = {359 - 373}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-99604-2}, issn = {1868-4238}, doi = {10.1007/978-3-319-99605-9_27}, author = {Vassilis Galanos}, editor = {Kreps, David and Ess, Charles and Leenen, Louise and Kimppa, Kai} } @book {2018, title = {Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide}, volume = {537}, year = {2018}, pages = {359 - 373}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-99604-2}, issn = {1868-4238}, doi = {10.1007/978-3-319-99605-9_27}, author = {Vassilis Galanos}, editor = {Kreps, David and Ess, Charles and Leenen, Louise and Kimppa, Kai} } @conference {2018, title = {Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide}, booktitle = {IFIP International Conference on Human Choice and Computers}, year = {2018}, url = {https://doi.org/10.1007/978-3-319-99605-9_27}, author = {Vassilis Galanos} } @article {2018, title = {Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration}, journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences}, volume = {376}, year = {2018}, month = {Jan-09-2019}, pages = {20170357}, issn = {1364-503X}, doi = {10.1098/rsta.2017.0357}, author = {Mikhaylov, Slava Jankin and Esteve, Marc and Campion, Averill} } @article {2018, title = {Artificial intelligence: Implications for social inflation and insurance}, journal = {Risk Management and Insurance Review}, volume = {21}, year = {2018}, month = {Jan-12-2018}, pages = {373 - 387}, doi = {10.1111/rmir.12111}, author = {Kelley, Kevin H. and Fontanetta, Lisa M. and Heintzman, Mark and Pereira, Nikki} } @article {2018, title = {Artificial Intelligence in Cardiology}, journal = {Journal of the American College of Cardiology}, volume = {71}, year = {2018}, month = {Jan-06-2018}, pages = {2668 - 2679}, issn = {07351097}, doi = {10.1016/j.jacc.2018.03.521}, author = {Johnson, Kipp W. and Torres Soto, Jessica and Glicksberg, Benjamin S. and Shameer, Khader and Miotto, Riccardo and Ali, Mohsin and Ashley, Euan and Joel T. Dudley} } @article {2018, title = {Artificial Intelligence in Medicine and Radiation Oncology}, journal = {Cureus}, year = {2018}, month = {Jan-04-2019}, abstract = {Artificial Intelligence (AI) was reviewed with a focus on its potential applicability to radiation oncology. The improvement of process efficiencies and the prevention of errors were found to be the most significant contributions of AI to radiation oncology. It was found that the prevention of errors is most effective when data transfer processes were automated and operational decisions were based on logical or learned evaluations by the system. It was concluded that AI could greatly improve the efficiency and accuracy of radiation oncology operations.}, keywords = {artificial intelligence, big data, error analysis, error prevention, machine learning, process efficiency, process optimization, quality improvement, radiation oncology}, doi = {10.7759/cureus.2475}, url = {https://www.cureus.com/articles/11443-artificial-intelligence-in-medicine-and-radiation-oncology}, author = {Weidlich, Vincent and Weidlich, Georg A.} } @article {2018, title = {Artificial Intelligence in Service}, journal = {Journal of Service Research}, volume = {21}, year = {2018}, month = {May-05-2018}, pages = {155 - 172}, issn = {1094-6705}, doi = {10.1177/1094670517752459}, author = {Huang, Ming-Hui and Rust, Roland T.} } @article {2018, title = {Artificial intelligence in the computer-age threatens human beings and working conditions at workplaces}, journal = {Electronics Science Technology and Application}, volume = {5}, year = {2018}, month = {Feb-08-2019}, issn = {2251-2608}, doi = {10.18686/esta.v5i3.76}, author = {Saithibvongsa, Phothong and Yu, Jae Eon} } @mastersthesis {2018, title = {Artificial Intelligence In The Sport Industry}, year = {2018}, url = {https://www.politesi.polimi.it/bitstream/10589/142501/1/ARTIFICIAL\%20INTELLIGENCE\%20IN\%20THE\%20SPORT\%20INDUSTRY_JACOPO\%20MOSELE.pdf}, author = {Jacopo Mosele} } @article {2018, title = {Artificial Intelligence Is Automating Hollywood}, year = {2018}, month = {07/2018}, keywords = {AI use cases}, url = {https://futurism.com/artificial-intelligence-automating-hollywood-art}, author = {Dan Robitzki} } @article {2018, title = {Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter}, number = {ISSN 1871-9872}, year = {2018}, publisher = {Maastricht University}, keywords = {artificial intelligence, economics of automation, growth theory, innovation, labour demand, productivity, technology}, url = {http://ftp.iza.org/dp12005.pdf}, author = {Thomas Gries and Wim Naude} } @article {2018, title = {Artificial intelligence, machine learning and health systems}, journal = {Journal of Global Health}, volume = {8}, year = {2018}, month = {Sep-10-2019}, issn = {2047-2978}, doi = {10.7189/jogh.08.020303}, author = {Panch, Trishan and Szolovits, Peter and Atun, Rifat} } @article {2018, title = {Artificial intelligence, machine learning and the evolution of healthcare A bright future or cause for concern?}, journal = {British Journal of Radiology}, volume = {7}, year = {2018}, pages = {223-225}, type = {Editorial}, keywords = {artificial intelligence, deep learning, machine learning}, author = {L.D. Jones and D. Golan and S. A. Hanna and M. Ramachandran} } @article {2018, title = {Artificial intelligence, machine learning and the evolution of healthcare}, journal = {Bone \& Joint Research}, volume = {7}, year = {2018}, month = {Jan-03-2018}, pages = {223 - 225}, doi = {10.1302/2046-3758.73.BJR-2017-0147.R1}, author = {Jones, L. D. and D. Golan and S. A. Hanna and M. Ramachandran} } @article {2018, title = {As s essing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour}, year = {2018}, url = {https://arxiv.org/ftp/arxiv/papers/1806/1806.03192.pdf}, author = {Emilia G{\'o}mez and Carlos Castillo and Vicky Charisi and Ver{\'o}nica Dahl and Gustavo Deco and Blagoj Delipetrev and Nicole Dewandre and Miguel {\'A}ngel Gonz{\'a}lez-Ballester and Fabien Gouyon and Jos{\'e} Hern{\'a}ndez-Orallo and Perfecto Herrera and Anders Jonsson and Ansgar Koene and Martha Larson and Ram{\'o}n L{\'o}pez de M{\'a}ntaras and Bertin Martens and Marius Miron and Rub{\'e}n Moreno-Bote and Nuria Oliver and Antonio Puertas Gallardo and Heike Schweitzer and Nuria Sebastian and Xavier Serra and Joan Serr{\`a} and Song{\"u}l Tolan and Karina Vold} } @conference {2018, title = {Assisting tourism in rural Southern Africa using machine learning}, year = {2018}, publisher = {IEEE}, organization = {IEEE}, abstract = {Tourism is a major contributor to employment in southern Africa and a major contributor to gross domestic products of many southern African countries. One of the major tourist attractions in many southern African countries is the wild animals. Major national parks such as Etosha in Namibia and Central Kalahari in Botswana often have rangers available to assist tourists on their game safaris by recognising animals and describing their habitats. Many of the smaller reserves, however, do not have the luxury of rangers available to tourists. At such smaller reserves, tourists are left on their own to recognise the various animals. This paper describes the use of Google{\textquoteright}s TensorFlow to create an image recogniser trained for southern African mammals. The recogniser was embedded in an Android mobile app and could then assist tourists at smaller reserves.}, url = {https://ieeexplore.ieee.org/document/8465441}, author = {Laurie Butgereit and Laura Martinus} } @article {2018, title = {Automated Classification of chest X-ray images as normal or abnormal using Convolutional Neural Network}, journal = {Asian Journal of Convergence in Technology}, volume = {4}, year = {2018}, month = {04/2018}, abstract = {Chest X-Rays are generally used for diagnosing abnormalities in the thoracic area. Radiologists need to spend significant amount of time for interpreting scans. Automatic classification of these images could greatly help radiology interpretation process by enhancing real world diagnosis of problems. Hence, radiologists can focus on detecting abnormalities from the abnormal images rather than checking for it in all the images. In this paper, we present a machine learning approach to solve this problem. Here, the algorithm uses COnvolutional Neural Networks (CNN) to learn and classify chest X-ray images as normal or abnormal based on image features.}, keywords = {classification, machine learning, radiology}, author = {Aayushi Gupta and Anupama C and P Indumathi and Anuj Kumar} } @article {2018, title = {Automating the black art: Creative places for artificial intelligence in audio mastering}, journal = {Geoforum}, volume = {96}, year = {2018}, pages = {77-86}, issn = {00167185}, doi = {10.1016/j.geoforum.2018.08.005}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0016718518302392}, author = {Birtchnell, Thomas and Elliott, Anthony} } @article {2018, title = {Automation and the future of jobs in India}, year = {2018}, month = {11/2018}, publisher = {University of Pennsylvania}, type = {Economy, Politics, Science and Technology}, keywords = {economics of automation}, url = {https://casi.sas.upenn.edu/iit/kuriakoseiyer}, author = {Francis Kuriakose and Deepa Iyer} } @article {2018, title = {Automation and the future of work}, journal = {Centre for International Governance Innovation}, year = {2018}, url = {https://www.cigionline.org/publications/automation-and-future-work-scenarios-and-policy-options}, author = {Joel Blit and Samantha St. Amand and Joanna Wajda} } @article {2018, title = {Is automation labor-displacing? Productivity growth, employment, and the labor share}, year = {2018}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w24871}, author = {Autor, David and Salomons, Anna} } @article {2018, title = {Automation, taxes and transfers with international rivalry}, year = {2018}, publisher = {Australian National University}, keywords = {automation, global modelling, income distribution, taxes, transfers}, issn = {2206-0332}, url = {https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2018-09/44_2018_tyers_zhou.pdf}, author = {Rod Tyers and Yixiao Zhou} } @article {seidel2018autonomous, title = {Autonomous tools and design: a triple-loop approach to human-machine learning}, journal = {Communications of the ACM}, volume = {62}, year = {2018}, pages = {50{\textendash}57}, publisher = {ACM}, author = {Seidel, Stefan and Berente, Nicholas and Lindberg, Aron and Lyytinen, Kalle and Jeffrey V Nickerson} } @article {seidel2018autonomous, title = {Autonomous Tools in System Design: Reflective Practice in Ubisofts Ghost Recon Wildlands Project}, journal = {Computer}, volume = {51}, year = {2018}, pages = {16{\textendash}23}, publisher = {IEEE}, author = {Seidel, Stefan and Berente, Nicholas and Martinez, Beno\^{\i}t and Lindberg, Aron and Lyytinen, Kalle and Jeffrey V Nickerson} } @article {2018, title = {Autonomous trucks and the future of the american trucker}, year = {2018}, month = {09/2018}, url = {https://www.steveviscelli.com/self-driving-trucks}, author = {Steve Viscelli} } @article {2018, title = {Autonomous vehicles employment impact study}, year = {2018}, month = {09/2018}, url = {https://advi.org.au/wp-content/uploads/2018/09/Autonomous-Vehicles-Employment-Impact-Survey-COR050918-5.pdf}, author = {Brian Haratsis and Tony Carmichael and Mark Coutney and Jacob Fong} } @article {2018, title = {{\textquoteleft}The beginning of a wave{\textquoteright}: A.I. Tiptoes into the workplace}, journal = {The NewYork Times}, year = {2018}, keywords = {AI, impacts}, url = {https://www.nytimes.com/2018/08/05/technology/workplace-ai.html}, author = {Steve Lohr} } @article {2018, title = {Beyond r\&d: The role of embodied technological change in affecting employment}, year = {2018}, keywords = {Innovation; R\&D; Embodied Technological Change; Employment; GMM-SY}, issn = {2284-0400}, url = {https://ideas.repec.org/p/ssa/lemwps/2018-15.html}, author = {Gabriele Pelleegrino and Mariacristina Piva and Marco Vivarelli} } @article {2018, title = {Boundary spanning at the science{\textendash}policy interface: the practitioners{\textquoteright} perspectives}, journal = {Sustainability Science}, volume = {13}, year = {2018}, month = {Jan-07-2018}, pages = {1175 - 1183}, issn = {1862-4065}, doi = {10.1007/s11625-018-0550-9}, author = {Bednarek, A. T. and Wyborn, C. and Cvitanovic, C. and Meyer, R. and Colvin, R. M. and Addison, P. F. E. and Close, S. L. and Curran, K. and Farooque, M. and Goldman, E. and Hart, D. and Mannix, H. and McGreavy, B. and Parris, A. and Posner, S. and Robinson, C. and Ryan, M. and Leith, P.} } @article {2018, title = {Can artificial intelligence make work more human?}, journal = {Strategic HR Review}, volume = {17}, year = {2018}, month = {Aug-10-2018}, pages = {263 - 264}, issn = {1475-4398}, doi = {10.1108/SHR-10-2018-146}, author = {He, Emily} } @article {2018, title = {Character qualities and the imagination age}, journal = {Creative Education}, volume = {09}, year = {2018}, month = {Jan-01-2018}, pages = {152 - 164}, issn = {2151-4755}, doi = {10.4236/ce.2018.92012}, author = {Alvarez, Mar{\'\i}a Garc{\'\i}a} } @article {2018, title = {Chat bots are the new HR managers}, journal = {Strategic HR Review}, volume = {17}, year = {2018}, month = {Nov-06-2018}, pages = {162 - 163}, issn = {1475-4398}, doi = {10.1108/SHR-03-2018-0024}, author = {Sheth, Beerud} } @article {2018, title = {Cognitive and technological aspects of e-learning in context of robotization}, journal = {Cognitive Science {\textendash} New Media {\textendash} Education}, volume = {3}, year = {2018}, month = {Mar-06-2020}, pages = {65}, abstract = {The development of e-learning education led to the emergence of two main problems of such form of education, which are the user-system interaction from the cognitive prospective, and the analysis of massive data received out of students{\textquoteright} activity. The development of artificial intelligence concepts and robotic process automation (RPA) tools, both problems might be solved in a more efficient way. The article presents the intelligent system of feedbacks, realized as JavaScript extension to Moodle platform, which intends to strength cognitive output of the preformed learning activity, creating an illusion of the trainer{\textquoteright}s presence and, therefore, contribute to the resolution of the first problem. The resolution of the second problem is proposed using artificial intelligence worker built in Blue Prism RPA platform, which performs validation of test questions upon strict criteria of selection. Such validation process allows to select the questions which are coherent with the index of complexity and the index of differentiation capacity.}, keywords = {artificial intelligence worker, Blue Prism automation, intelligent system of feedbacks, robotic process automation}, issn = {2543-506X}, doi = {10.12775/CSNME.2017.013}, url = {http://apcz.umk.pl/czasopisma/index.php/CSNME/article/view/CSNME.2017.013}, author = {Shvets, Anna and Shvets, Valentyna} } @article {2018, title = {Collaborative intelligence: Humans and AI are joining forces}, year = {2018}, url = {https://hbr.org/2018/07/collaborative-intelligence-humans-and-ai-are-joining-forces}, author = {H. James Wilson and Paul R. Daugherty} } @article {2018, title = {Comment on {\textquotedblleft}Should we fear the robot revolution? (The correct answer is yes){\textquotedblright} by Andrew Berg, Ed Buffie, and Felipe Zanna}, journal = {Journal of Monetary Economics}, volume = {97}, year = {2018}, month = {Jan-08-2018}, pages = {149 - 152}, issn = {03043932}, doi = {10.1016/j.jmoneco.2018.05.012}, author = {Hanley, Douglas} } @article {2018, title = {Computational power and the social impact of artificial intelligence}, journal = {SSRN Electronic Journal}, year = {2018}, abstract = {Machine learning is computational process. To that end, it is inextricably tied to computational power - the tangible material of chips and semiconductors that the algorithms of machine intelligence operate on. Most obviously, computational power and computing architectures shape the speed of training and inference in machine learning, and therefore influence the rate of progress in the technology. But, these relationships are more nuanced than that: hardware shapes the methods used by researchers and engineers in the design and development of machine learning models. Characteristics such as the power consumption of chips also define where and how machine learning can be used in the real world. In a broader perspective, computational power is also important because of its specific geographies. Semiconductors are designed, fabricated, and deployed through a complex international supply chain. Market structure and competition among companies in this space influence the progress of machine learning. Moreover, since these supply chains are also considered significant from a national security perspective, hardware becomes an arena in which government industrial and trade policy has a direct impact on the fundamental machinery necessary for artificial intelligence (AI). This paper aims to dig more deeply into the relationship between computational power and the development of machine learning. Specifically, it examines how changes in computing architectures, machine learning methodologies, and supply chains might influence the future of AI. In doing so, it seeks to trace a set of specific relationship between this underlying hardware layer and the broader social impacts and risks around AI. On the hand, this examination shines a spotlight on how hardware works to exacerbate a range of concerns around ubiquitous surveillance, technological unemployment, and geopolitical conflict. On the other, it also highlights the potentially significant role that shaping the development of computing power might play in addressing these concerns.}, doi = {10.2139/ssrn.3147971}, author = {Tim Hwang} } @book {2018, title = {Creativity, the arts, and the future of work}, year = {2018}, pages = {283 - 310}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-78579-0}, doi = {10.1007/978-3-319-78580-6_9}, author = {Nathan, Linda F.}, editor = {Cook, Justin W.} } @article {2018, title = {A critical approach to human helping in information systems: Heteromation in the Brazilian correspondent banking system}, journal = {Information and Organization}, volume = {28}, year = {2018}, month = {Jan-09-2018}, pages = {111 - 128}, issn = {14717727}, doi = {10.1016/j.infoandorg.2018.08.002}, author = {Diane E. Bailey and Eduardo H. Diniz and Bonnie A. Nardi and Paul M. Leonardi and Dan Sholler} } @book {2018, title = {A critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America{\textquoteright}s labour force}, volume = {10963}, year = {2018}, pages = {217 - 232}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-95170-6}, issn = {0302-9743}, doi = {10.1007/978-3-319-95171-3_18}, author = {Wogu, Ikedinachi Ayodele and Misra, Sanjay and Assibong, Patrick and Adewumi, Adewole and Damasevicius, Robertas and Maskeliunas, Rytis}, editor = {Gervasi, Osvaldo and Murgante, Beniamino and Misra, Sanjay and Stankova, Elena and Torre, Carmelo M. and Rocha, Ana Maria A.C. and Taniar, David and Apduhan, Bernady O. and Tarantino, Eufemia and Ryu, Yeonseung} } @article {2018, title = {Cryptocurrency, Artificial Intelligence and basic income as innovative technological system}, journal = {Path of Science}, volume = {4}, year = {2018}, month = {Jul-08-2020}, pages = {2024 - 2030}, doi = {10.22178/pos10.22178/pos.37-6}, author = {Sopilnyk, Lyubomyr and Shevchuk, Andriy and Kopytko, Vasyl} } @book {2018, title = {Data Science for Undergraduates}, year = {2018}, publisher = {National Academies Press}, organization = {National Academies Press}, address = {Washington, D.C.}, isbn = {978-0-309-47559-4}, doi = {10.17226/25104}, url = {https://www.nap.edu/catalog/25104} } @article {2018, title = {DEFINITION, APPLICATION AND INFLUENCE OF ARTI FICIAL INTELLIGENCE ON DESIGN INDUSTRIES}, journal = {Landscape Architecture Frontiers}, volume = {6}, year = {2018}, month = {Jan-01-2018}, pages = {56}, issn = {2095-5405}, doi = {10.15302/J-LAF-20180207}, author = {Linghao Cai and Ling Fan and Wenbo Lai and LONG, Ying and Peng Wang and Xiangyang Xin} } @article {2018, title = {Developing an ethical framework}, journal = {Business Horizons}, volume = {61}, year = {2018}, month = {Jan-11-2018}, pages = {823 - 832}, issn = {00076813}, doi = {10.1016/j.bushor.2018.07.001}, author = {Wright, Scott A. and Schultz, Ainslie E.} } @article {2018, title = {Developing robots: The need for an ethical framework}, journal = {European View}, volume = {17}, year = {2018}, month = {Aug-04-2019}, pages = {37 - 43}, issn = {1781-6858}, doi = {10.1177/1781685818761016}, author = {Leveringhaus, Alex} } @article {2018, title = {Digital economy and the models of income distribution in the society}, journal = {SHS Web of Conferences}, volume = {44}, year = {2018}, month = {Jan-01-2018}, pages = {00005}, doi = {10.1051/shsconf/20184400005}, author = {Akaev, Askar and Rudskoi, Andrew and Devezas, Tessaleno}, editor = {Sarygulov, A. and Sergeev, V. and Ungv{\'a}ri, L. and Semmler, W.} } @article {2018, title = {Digital economy: backgrounds, main drivers and new challenges}, journal = {SHS Web of Conferences}, volume = {44}, year = {2018}, month = {Jan-01-2018}, pages = {00006}, doi = {10.1051/shsconf/20184400006}, author = {Akaev, Askar and Sarygulov, Askar and Sokolov, Valentin}, editor = {Sarygulov, A. and Sergeev, V. and Ungv{\'a}ri, L. and Semmler, W.} } @article {2018, title = {The discourse approach to boundary identification and corpus construction for theory review articles}, journal = {Journal of the Association for Information Systems}, year = {2018}, keywords = {article identification, boundary identification, citation search, keyword search, literature review, machine learning, research review, review article}, url = {https://www.researchgate.net/publication/325215971_Understanding_the_Elephant_The_Discourse_Approach_to_Boundary_Identification_and_Corpus_Construction_for_Theory_Review_Articles}, author = {Kai R. Larsen and Dirik S. Hovorka and Alan R. Dennis and Jevin D. West} } @article {2018, title = {Discussion for JME special issue: APST paper}, journal = {Journal of Monetary Economics}, volume = {97}, year = {2018}, month = {Jan-08-2018}, pages = {68 - 70}, issn = {03043932}, doi = {10.1016/j.jmoneco.2018.05.003}, author = {Hershbein, Brad} } @article {2018, title = {Dreyfus on the {\textquoteright}Fringe{\textquoteright}: information processing, intelligent activity, and the future of thinking machines}, year = {2018}, url = {https://www.researchgate.net/publication/323956550_Dreyfus_on_the_fringe_-_accepted_draft}, author = {Jeffrey White} } @article {2018, title = {Economic policy for artificial intelligence}, number = {24690}, year = {2018}, month = {06/2018}, abstract = {Recent progress in artificial intelligence (AI) {\textendash} a general purpose technology affecting many industries - has been focused on advances in machine learning, which we recast as a quality-adjusted drop in the price of prediction. How will this sharp drop in price impact society? Policy will influence the impact on two key dimensions: diffusion and consequences. First, in addition to subsidies and IP policy that will influence the diffusion of AI in ways similar to their effect on other technologies, three policy categories - privacy, trade, and liability - may be uniquely salient in their influence on the diffusion patterns of AI. Second, labor and antitrust policies will influence the consequences of AI in terms of employment, inequality, and competition.}, keywords = {economics of automation}, url = {https://econpapers.repec.org/paper/nbrnberwo/24690.htm}, author = {Ajay Agrawal and Joshua Gans and Avi Goldfarb} } @article {2018, title = {Economic policy for Artificial Intelligence}, year = {2018}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w24690}, author = {Agrawal, Ajay and Gans, Joshua and Goldfarb, Avi} } @article {2018, title = {The economics of artificial intelligence: Implications for the future of work}, year = {2018}, isbn = {978-92-2-031137-0}, issn = {978-92-2-031138-7}, url = {https://www.ilo.org/wcmsp5/groups/public/---dgreports/---cabinet/documents/publication/wcms_647306.pdf}, author = {Ekkehard Ernst and Rossana Merola and Daniel Samaan} } @mastersthesis {2018, title = {Economies of the future: Robots and Artificial Intelligence, the new economic motor or downfall of the working class?}, year = {2018}, month = {11/2018}, type = {master thesis}, abstract = {Technological progress and innovation have significantly contributed to global economic growth, societal advancement, and higher living standards. However, there is growing concern over the future that lies ahead because of increasing robotisation and progress in artificial intelligence (AI), which are feared to cause significant loss of labour demand. The body of posterior economic scientific work addressing this topic mostly concludes on a positive note. Namely, recent technological advancements have resulted in a net increase in labour demand, but this demand is redistributed to different tasks and occupations. Yet, future oriented research, most notably by Frey and Osborne (2017), has sparked a debate on the future of work due to estimations that indicate that over 40\% of jobs will become automatable in the next 20 years. Therefore, the societal question remains: Robots and Artificial Intelligence, the new economic motor or downfall of the working class?}, keywords = {economics of automation}, url = {https://repository.tudelft.nl/islandora/object/uuid\%3Af30b5d2e-d48d-4c90-8780-3d55a2e1a7d3}, author = {Koen Spaanderman} } @article {2018, title = {The effects of automation}, year = {2018}, url = {https://www.dropbox.com/sh/8sxki5mwikjxlte/AAB6zvW5F0s2FIJ6jUmEW7P-a/Popular\%20press\%20about\%20impacts?dl=0\&preview=effects+of+automation.pdf\&subfolder_nav_tracking=1}, author = {Jim L. Smith} } @book {2018, title = {eHealth - Making Health Care SmarterUse of Artificial Intelligence in Healthcare Delivery}, year = {2018}, publisher = {InTech}, organization = {InTech}, isbn = {978-1-78923-522-7}, doi = {http://dx.doi.org/10.5772/intechopen.74714}, author = {Reddy, Sandeep}, editor = {Heston, Thomas F.} } @article {2018, title = {Embracing the new world of work}, year = {2018}, url = {https://sfmagazine.com/post-entry/june-2018-embracing-the-new-world-of-work/}, author = {John M. Lewin} } @article {2018, title = {Embracing the sobering reality of technological influences on jobs, employment and human resource development}, journal = {European Journal of Training and Development}, volume = {42}, year = {2018}, month = {Mar-09-2018}, pages = {400 - 416}, issn = {2046-9012}, doi = {10.1108/EJTD-03-2018-0030}, author = {Chuang, Szufang and Graham, Carroll Marion} } @article {2018, title = {Ethics of using Artificial Intelligence to augment drafting legal documents}, journal = { Texas A\&M Journal of Property Law}, volume = {4}, year = {2018}, edition = {3}, url = {https://scholarship.law.tamu.edu/cgi/viewcontent.cgi?article=1080\&context=journal-of-property-law}, author = {David Hricik Hri and Asya-Lorrene S. Morgan and Kyle H. Williams} } @article {2018, title = {The evolving role of ICT in the economy}, year = {2018}, month = {06/2018}, keywords = {consulting reports}, url = {http://www.lse.ac.uk/business-and-consultancy/consulting/consulting-reports/the-evolving-role-of-ict-in-the-economy}, author = {Mirko Draca and Ralf Martin and Rosa Sanchis-Guarner} } @mastersthesis {2018, title = {Examination of cognitive load in the human-machine teaming context}, year = {2018}, month = {06/2018}, abstract = {The Department of Defense (DoD) is increasingly hoping to employ unmanned systems and artificial intelligence to achieve a strategic advantage over adversaries. While some tasks may be suitable for machine substitution, many parts of the DoD{\textquoteright}s mission continue to require boots on the ground and humans in the loop working in interdependent human-machine teams. The commercial unmanned systems marketplace and active UxS and autonomous systems offer military research and acquisitions professionals promising technical solutions, but may integrate poorly in a human-machine team application. The authors developed a framework for analyzing task-to-technology matches and team design for military human-machine teams. The framework is grounded in the cognitive theories of situational awareness and decision making, team dynamics, and functional allocation literature. Additionally, the research recommends developing a shared DoD-wide understanding of autonomous systems terms and taxonomy, and educating operational leaders, acquisitions staff, and executives about realistic expectations and employment of autonomous systems in human-machine environments.}, url = {https://hdl.handle.net/10945/59638}, author = {Clarke, Alan J. and Knudson, Daniel F. III} } @article {2018, title = {Experimental evidence on complimentarities between human capital and machine learning}, year = {2018}, month = {01/2018}, keywords = {economics of automation}, url = {https://hbswk.hbs.edu/item/different-strokes-for-different-folks-experimental-evidence-on-complementarities-between-human-capital-and-machine-learning}, author = {Prithwiraj Choudhury and Evan Starr and Rajshree Agarwal} } @article {2018, title = {Experimental evidence on productivity complementarities}, number = {18-065}, year = {2018}, publisher = {Harvard Business School Working Paper}, keywords = {Human Capital, Performance Productivity, Technological Innovation, Technology Adoption}, url = {https://www.hbs.edu/faculty/Pages/item.aspx?num=53855}, author = {Prithwiraj Choudhury} } @article {2018, title = {Explaining the decline in the u. S. Employment-to-population ratio: A review of the evidence}, year = {2018}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w24333}, author = {Abraham, Katharine and Kearney, Melissa} } @article {2018, title = {Explanation to Avert Surprise}, journal = {IUI Workshops}, year = {2018}, url = {https://www.semanticscholar.org/paper/Explanation-to-Avert-Surprise-Gervasio-Myers/8e3b3d9e9075095a87c96fa9690d2ccbf127234e}, author = {Melinda Gervasio and Karen Myers and Eric Yeh and Boone Adkins} } @article {2018, title = {Exploiting ability for human adaptation to facilitate improved human-robot interaction and acceptance}, journal = {The Information Society}, volume = {34}, year = {2018}, month = {Mar-05-2020}, pages = {153 - 165}, issn = {0197-2243}, doi = {10.1080/01972243.2018.1444255}, author = {Caleb-Solly, Praminda and Dogramadzi, Sanja and Huijnen, Claire A.G.J. and Heuvel, Herjan van den} } @article {2018, title = {Fedex follows Amazon into the robotic future}, year = {2018}, url = {https://www.nytimes.com/2018/03/18/technology/fedex-robots.html}, author = {Cade Metz} } @article {2018, title = {Financing Terror Enterprises Funding Operations in Prolonged Conflicts in South Asia}, year = {2018}, institution = {KW Publishers Pvt Ltd}, address = {New Delhi}, issn = {23939729}, url = {https://www.claws.in/images/publication_pdf/1589740822_1515901225_MP71-NikitaKohli(Final)_CLAWS.pdf}, author = {Nikita Kohli} } @article {2018, title = {foo.castr: visualising the future AI workforce}, journal = {Big Data Analytics}, volume = {3}, year = {2018}, month = {Jan-12-2018}, doi = {10.1186/s41044-018-0034-z}, author = {Amador Diaz Lopez, Julio and Molina-Solana, Miguel and Kennedy, Mark T.} } @article {2018, title = { forbes.com 10 Amazing Examples Of How Deep Learning AI Is Used In Practice? }, year = {2018}, author = {Bernard Marr} } @conference {2018, title = {A framework for understanding chatbots and their future}, booktitle = {the 11th International WorkshopProceedings of the 11th International Workshop on Cooperative and Human Aspects of Software Engineering - CHASE {\textquoteright}18}, year = {2018}, pages = {13 - 16}, publisher = {ACM Press}, organization = {ACM Press}, address = {Gothenburg, SwedenNew York, New York, USA}, isbn = {9781450357258}, doi = {10.1145/3195836.3195859}, author = {Paikari, Elahe and van der Hoek, Andr{\'e}} } @article {2018, title = {Future of artificial intelligence: Japan{\textquoteright}s path to growth}, journal = {American Journal Of Modern Physics And Application}, volume = {5}, year = {2018}, month = {05/2018}, pages = {48-52}, url = {https://www.researchgate.net/publication/326625497_Future_of_Artificial_Intelligence_Japan{\textquoteright}s_Path_to_Growth_Email_address}, author = {Salman Abdou and Nadeen Nustafa Kamal} } @article {2018, title = {The future of work, business education, and the role of AACSB}, journal = {Journal of Legal Studies Education}, volume = {35}, year = {2018}, month = {Jan-12-2018}, pages = {165 - 170}, doi = {10.1111/jlse.2018.35.issue-110.1111/jlse.12073}, author = {Beck-Dudley, Caryn L.} } @article {2018, title = {The Future of Work: Compulsory, by Martha Wells}, year = {2018}, url = {https://www.wired.com/story/future-of-work-compulsory-martha-wells/}, author = {Martha Wells} } @article {2018, title = {The future of work in the light of technological change}, volume = {UDC: 005.32:005.95/.96}, year = {2018}, type = {Original Scientific Paper}, abstract = {Abstract: Technological unemployment, a phenomenon that has been relevant for decades, is now reaching a new dimension. There is a growing number of discussions about whether technology is the main culprit for the rising trend of unemployment rates around the world, therefore, the paper discusses the impact of technological changes on the labour market. We conducted a survey in Slovenian companies with more than 100 employees in order to find out their view on replacing workers with technology, as well as the reasons and consequences of new technology. We discussed the results of our research and the views, findings and suggestions of various authors. We have found that technological unemployment is not a simple problem, as this phenomenon is intertwined with various issues, and that technology presents various dangers which may at first seem less visible.}, keywords = {Impact of technology on the labour market, Labour market, Technological unemployment}, url = {http://media3.novi.economicsandlaw.org/2017/07/Vol23/IJEAL-23-09.pdf}, author = {Vesna Novak and Denis Dizdarevic} } @article {2018, title = {The Future of Work: Robots Cooking Free Lunches?}, journal = {European View}, volume = {17}, year = {2018}, month = {Jun-10-2020}, pages = {241 - 241}, issn = {1781-6858}, doi = {10.1177/1781685818813010}, author = {Turk, Ziga} } @article {2018, title = {The Future of Work: The Trustless, by Ken Liu}, year = {2018}, url = {https://www.wired.com/story/future-of-work-trustless-ken-liu/}, author = {Ken Liu} } @article {2018, title = {Game changing value from Artificial Intelligence: eight strategies}, journal = {Strategy \& Leadership}, volume = {46}, year = {2018}, month = {Mar-01-2019}, pages = {16 - 22}, issn = {1087-8572}, doi = {10.1108/SL-11-2017-0106}, author = {Plastino, Eduardo and Purdy, Mark} } @article {2018, title = {G.M says its driverless car could be in fleets by next year}, year = {2018}, month = {01/2018}, keywords = {autonomous vehicles}, url = {https://www.nytimes.com/2018/01/12/business/gm-driverless-car.html}, author = {Neal E. Boudette} } @article {2018, title = {Google and others are building AI systems that doubt themselves}, year = {2018}, url = {https://www.technologyreview.com/s/609762/google-and-others-are-building-ai-systems-that-doubt-themselves/}, author = {Will Knight} } @article {2018, title = {Google glass is back with AI}, year = {2018}, month = {07/2018}, abstract = {An app for Glass aimed at factory workers can understand spoken language and respond verbally.}, url = {https://www.wired.com/story/google-glass-is-backnow-with-artificial-intelligence/}, author = {Tom Simonite} } @article {2018, title = {Google Researchers Are Learning How Machines Learn}, year = {2018}, url = {https://www.nytimes.com/2018/03/06/technology/google-artificial-intelligence.html}, author = {Cade Metz} } @article {2018, title = {High tech, low growth: Robots and the future of work abstract}, journal = {Historical Materialism}, volume = {26}, year = {2018}, month = {May-12-2019}, pages = {3 - 34}, doi = {10.1163/1569206X-00001745}, author = {Moody, Kim} } @article {2018, title = {High-skilled white-collar work? Machines can do that, too}, year = {2018}, url = {https://www.nytimes.com/2018/07/07/business/economy/algorithm-fashion-jobs.html}, author = {Noam Scheiber} } @article {2018, title = {How cheap labor drives China{\textquoteright}s AI Ambitions}, year = {2018}, month = {11/2018}, keywords = {human and machine intelligence}, url = {https://www.nytimes.com/2018/11/25/business/china-artificial-intelligence-labeling.html}, author = {Li Yuan} } @article {2018, title = {How do machine learning, robotic process automation, and blockchains affect the human factor in business process management? }, journal = {Communications of the Association for Information Systems}, year = {2018}, month = {Jan-01-2018}, pages = {297 - 320}, doi = {10.17705/1CAIS.04319}, author = {Mendling, Jan and Decker, Gero and Hull, Richard and Reijers, Hajo A. and Weber, Ingo} } @article {2018, title = {How does the digital transformation affect organizations? Key themes of change in work design and leadership}, journal = {management revu}, volume = {29}, year = {2018}, month = {Jan-01-2018}, pages = {114 - 138}, issn = {0935-9915}, doi = {10.5771/0935-9915-2018-2-114}, author = {Schwarzm{\"u}ller, Tanja and Brosi, Prisca and Duman, Denis and Welpe, Isabell M.} } @article {2018, title = {How driverless cars could disrupt the real estate industry}, year = {2018}, keywords = {autonomous vehicles}, url = {https://www.forbes.com/sites/elyrazin/2018/03/11/how-driverless-cars-could-disrupt-the-real-estate-industry/$\#$1595cb8613c1}, author = {Ely Razin} } @article {2018, title = {How leaders face the future of work ?}, volume = {59}, year = {2018}, url = {https://sloanreview.mit.edu/article/how-leaders-face-the-future-of-work/}, author = {Lynda Gratton} } @article {2018, title = {How machine learning can permanently capture legal expertise and optimize the law firm pyramid}, journal = {JBEL}, volume = {11}, year = {2018}, abstract = {As the legal industry gradually integrates artificial intelligence (AI) into its practice, the underlying technology continues to advance at a fever pitch. Machine learning platforms arguably represent the pinnacle of AI development, and this technology currently augments and replicates intelligent human tasks in ways never before conceived. The business applications of machine learning are bearing fruit across a spectrum of industries and professions. Yet despite machine learning{\textquoteright}s demonstrated promise, its forays into the legal industry have been uneven. In fact, the most advanced forms of machine learning have been relegated primarily to lower-level attorney tasks such as e-discovery, due-diligence, and legal research and, unfortunately, have yet to be embraced by the upper echelon legal decision-makers and strategists. This article explores this technology{\textquoteright}s underutilization in law and highlights the inroads made by machine learning in other professions such as healthcare. It then provides an illustration of the capacity of machine learning and develops detailed hypotheticals of machine learning{\textquoteright}s potential impact upon several representative areas of high-level legal decision-making, including lateral hiring, litigation strategy development, cost optimization, and overall law firm management. Finally, this article argues that incorporating machine learning will enable firms to permanently capture attorney expertise and develop deep reservoirs of reputational capital as a source of enduring competitive advantage.}, url = {https://digitalcommons.pepperdine.edu/jbel/vol11/iss2/3/}, author = {J. Mark Phillips} } @article {2018, title = {How real is the impact of artificial intelligence? The business information survey 2018}, journal = {Business Information Review}, volume = {35}, year = {2018}, month = {12/2019}, pages = {99 - 115}, keywords = {Artificial Intelligence (AI), blockchain, chatbot, cybersecurity, data economy, data governance, data lakes, data literacy, data quality, data trusts, data value, ethics, information literacy, intelligent virtual agents, machine learning (ML), Robotics}, issn = {0266-3821}, doi = {10.1177/0266382118790150}, url = {http://journals.sagepub.com/doi/10.1177/0266382118790150}, author = {Carter, Denise} } @article {2018, title = {How the anthropormorphization of virtual assistants influences user{\textquoteright}s trust}, journal = {Academy of Management Proceedings}, volume = {2018}, year = {2018}, month = {Jan-08-2018}, pages = {16328}, issn = {0065-0668}, doi = {10.5465/AMBPP.2018.16328abstract}, author = {Crone, Tim and Shafeie Zargar, Mahmood} } @article {2018, title = {How to respond to the fourth industrial revolution, or the second information technology revolution? Dynamic new combinations between technology, market, and society through open innovation}, journal = {Journal of Open Innovation: Technology, Market, and Complexity}, volume = {4}, year = {2018}, month = {Jan-09-2018}, pages = {21}, doi = {10.3390/joitmc4030021}, author = {Lee, MinHwa and Yun, JinHyo and Pyka, Andreas and Won, DongKyu and Kodama, Fumio and Schiuma, Giovanni and Park, HangSik and Jeon, Jeonghwan and Park, KyungBae and Jung, KwangHo and Yan, Min-Ren and Lee, SamYoul and Zhao, Xiaofei} } @book {2018, title = {How unequal? Insights on inequality }, series = {CEDA {\textendash} the Committee for Economic Development of Australia}, year = {2018}, month = {04/2018}, keywords = {ethics}, isbn = {0 85801 318 5}, url = {https://www.ceda.com.au/CEDA/media/General/Publication/PDFs/CEDA-How-unequal-Insights-on-inequality-April-2018-FINAL_WEB.pdf} } @article {2018, title = {Human and Machine Learning}, journal = {Computational Economics}, year = {2018}, month = {Sep-02-2019}, issn = {0927-7099}, doi = {10.1007/s10614-018-9803-z}, author = {Kao, Ying-Fang and Venkatachalam, Ragupathy} } @article {2018, title = {Human and smart machine co-learning with brain computer interface}, journal = {IEEE SMC Magazine}, volume = {4}, year = {2018}, keywords = {human and machine inttelligence}, url = {https://arxiv.org/abs/1802.06521}, author = {Chang - Shing Lee and Mei - Hui Wang and Li - Wei Ko and Naoyuki Kubota and Lu - An Lin and Shinya Kitaoka and Yu - Te Wang and Shun - Feng Su} } @article {2018, title = {Human capital management and future of work; job creation and unemployment: a literature review}, journal = {OALib}, volume = {05}, year = {2018}, month = {Jan-01-2018}, pages = {1 - 17}, issn = {2333-9721}, doi = {10.4236/oalib.1104859}, author = {Mukhalipi, Adamson} } @article {2018, title = { IBM Watson Talent The Business Case for AI in HR With Insights and Tips on Getting Started }, year = {2018}, url = {https://www.ibm.com/downloads/cas/AGKXJX6M}, author = {Nigel Guenole and Sheri Feinzig} } @article {2018, title = {Identifying factors reinforcing robotization: Interactive forces of employment, working hour and wage}, journal = {Sustainability}, volume = {10}, year = {2018}, month = {Jan-02-2018}, pages = {490}, doi = {10.3390/su10020490}, author = {Cho, Joonmo and Kim, Jinha} } @conference {2018, title = {Image Recognition of Disease-Carrying Insects: A System for Combating Infectious Diseases Using Image Classification Techniques and Citizen Science}, booktitle = {Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences}, year = {2018}, publisher = {Hawaii International Conference on System Sciences}, organization = {Hawaii International Conference on System Sciences}, doi = {10.24251/HICSS.2018.00010.24251/HICSS.2018.359}, url = {http://hdl.handle.net/10125/49887http://hdl.handle.net/10125/50247}, author = {Munoz, J. Pablo and Boger, Rebecca and Dexter, Scott and Low, Russanne and Li, Justin} } @article {2018, title = {Imagining a future of work that fosters mobility for all}, year = {2018}, url = {https://www.mobilitypartnership.org/imagining-future-work-fosters-mobility-all}, author = {Lawrence Katz and Ai-Jen Poo and Elaine Waxman} } @conference {2018, title = {The impact of artificial intelligence on the HR function}, booktitle = {IES Perspectives on HR 2018}, year = {2018}, keywords = {HR}, url = {https://www.employment-studies.co.uk/system/files/resources/files/mp142_The_impact_of_Artificial_Intelligence_on_the_HR_function-Peter_Reilly.pdf}, author = {Peter Reilly} } @article {2018, title = {The impact of automation on employment: Just the usual structural change? }, journal = {Sustainability}, volume = {10}, year = {2018}, month = {Jan-05-2018}, pages = {1661}, doi = {10.3390/su10051661}, author = {Vermeulen, Ben and Kesselhut, Jan and Pyka, Andreas and Saviotti, Pier} } @article {2018, title = { The impact of industrial robots on eu employment and wages: A local labour market approach}, year = {2018}, month = {04/2018}, publisher = {bruegel}, keywords = {economics of automation}, url = {https://bruegel.org/2018/04/the-impact-of-industrial-robots-on-eu-employment-and-wages-a-local-labour-market-approach/}, author = {Francesco Chiacchio and Georgios Petropoulos and David Pichler} } @article {2018, title = {The impact of technological progress on labour markets: policy challenges}, journal = {Oxford Review of Economic Policy}, volume = {34}, year = {2018}, month = {Feb-07-2018}, pages = {362 - 375}, issn = {0266-903X}, doi = {10.1093/oxrep/gry002}, author = {Goos, Maarten} } @article {2018, title = {The impact of technology and globalization on employment and equity}, journal = {International Journal of Global Sustainability}, volume = {3}, year = {2018}, month = {Oct-11-2019}, pages = {49}, doi = {10.5296/ijgs.v3i1.14127}, author = {Arogyaswamy, Bernard and Hunter, John} } @article {2018, title = {Implications of technology for growth, factor shares, and employment}, journal = {American Economic Review}, volume = {108}, year = {2018}, month = {Jan-06-2018}, pages = {1488 - 1542}, issn = {0002-8282}, doi = {10.1257/aer.20160696}, author = {Acemoglu, Daron and Restrepo, Pascual} } @article {2018, title = {Improving palliative care with deep learning}, journal = {BMC Medical Informatics and Decision Making}, volume = {18}, year = {2018}, month = {Jan-12-2018}, doi = {10.1186/s12911-018-0677-8}, author = {Avati, Anand and Jung, Kenneth and Harman, Stephanie and Downing, Lance and Ng, Andrew and Shah, Nigam H.} } @article {2018, title = {iNaturalist as a tool to expand the research value of museum specimens}, journal = {Applications in Plant Sciences}, volume = {6}, year = {2018}, month = {Jan-11-2018}, pages = {e01193}, keywords = {AI use cases}, doi = {10.1002/aps3.1193}, author = {Heberling, J. Mason and Isaac, Bonnie L.} } @article {2018, title = {Industrial employment and income inequality: Evidence from panel data}, journal = {Structural Change and Economic Dynamics}, volume = {45}, year = {2018}, month = {Jan-06-2018}, pages = {84 - 93}, issn = {0954349X}, doi = {10.1016/j.strueco.2018.02.006}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0954349X17302862https://api.elsevier.com/content/article/PII:S0954349X17302862?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0954349X17302862?httpAccept=text/plain}, author = {Mehic, Adrian} } @article {2018, title = {The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions}, journal = {Computers in Human Behavior}, volume = {85}, year = {2018}, month = {Jan-08-2018}, pages = {183 - 189}, issn = {07475632}, doi = {10.1016/j.chb.2018.03.051}, author = {Araujo, Theo} } @article {2018, title = {The internet and jobs opportunities and ambiguous trends}, year = {2018}, month = {02/2018}, keywords = {economics of automation}, url = {https://www.ceps.eu/system/files/PI2018_06_LP-EN-LW_InternetAndJobs.pdf}, author = {Lorenzo Pupillo and Eli Noam and Leonard Waverman} } @book {2018, title = {Investigating ergonomics in the context of human-robot collaboration as a sociotechnical system}, volume = {784}, year = {2018}, pages = {127 - 135}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-94345-9}, issn = {2194-5357}, doi = {10.1007/978-3-319-94346-6_12}, author = {R{\"u}cker, Daniel and Hornfeck, R{\"u}diger and Paetzold, Kristin}, editor = {Chen, Jessie} } @article {2018, title = {Is IT changing the world? Conceptions of causality for information systems theorizing }, journal = {MIS Quarterly}, volume = {42}, year = {2018}, pages = {1255-1280}, url = {https://dl.acm.org/citation.cfm?id=3370119.3370131}, author = {M. Lynne Markus and Frantz Rowe} } @article {2018, title = {{\textquoteleft}It{\textquoteright}s either a panda or a gibbon{\textquoteright}: AI winters and the limits of deep learning}, journal = {War on the rocks}, year = {2018}, type = {Commentary }, url = {https://warontherocks.com/2018/05/its-either-a-panda-or-a-gibbon-ai-winters-and-the-limits-of-deep-learning/}, author = {Robert Richbourg} } @book {2018, title = {Lecture Notes in Computer ScienceArtificial General IntelligenceTowards a Sociological Conception of Artificial Intelligence}, volume = {10999}, year = {2018}, pages = {130 - 139}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-97675-4}, issn = {0302-9743}, doi = {10.1007/978-3-319-97676-1}, author = {Jakub Mlynar and Hamed S. Alavi and Himanshu Verma and Lorenzo Cantoni}, editor = {Matthew Ikl{\'e} and Arthur Franz and Rafal Rzepka and Ben Goertzel} } @book {2018, title = {Lecture Notes in Computer ScienceDesign, User Experience, and Usability: Theory and PracticeComparing Human Against Computer Generated Designs: New Possibilities for Design Activity Within Agile Projects}, volume = {10918}, year = {2018}, pages = {693 - 710}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-91796-2}, issn = {0302-9743}, doi = {10.1007/978-3-319-91797-9_48}, author = {Fernandes, Farley and Filgueiras, Ernesto and Neves, Andr{\'e}}, editor = {Marcus, Aaron and Wang, Wentao} } @proceedings {2018, title = {A literature Analysis of Research on Artificial Intelligence in Management Information System (MIS)}, year = {2018}, abstract = {This article presents an overview of Artificial Intelligence (AI) research applied in the Management Information System field by analyzing the databases of the AIS journal basket list representing the major international journal on MIS. AN initial set of 438 published papers was identified based on our search criteria. From those, 74 were selected because of their appropriate fit with the research questions. They were organized into domains, type of research, data collection strategy and AI techniques. We found; (1) MIS Quarterly published 42\% of the papers; (2) 50\% of studies were on Information Systems applications, followed by 15\% on Knowledge Management; and (3) 7 AI techniques were presented. This paper provides an overview of applied AI in Management, highlights the most studies related topics and techniques and contributes to a research agenda on the subject.}, keywords = {artificial intelligence, Information Systems, Literature Analysis}, author = {Alexandre Moreira Nascimento and Maria Alexandra V. C. da Cunha and Fernando de Souza Meirelles and Eusebio Scornavacca and Vinicius Veloso de Melo} } @article {2018, title = { Looking though the Pygmalion Lens}, journal = {AI \& SOCIETY}, volume = {33}, year = {2018}, month = {Jan-11-2018}, pages = {459 - 465}, issn = {0951-5666}, doi = {10.1007/s00146-018-0866-0}, author = {Gill, Karamjit S.} } @book {2018, title = {Machine intelligence: Blessing or curse? It depends on us!}, year = {2018}, pages = {25 - 39}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-90868-7}, doi = {10.1007/978-3-319-90869-4_4}, author = {Helbing, Dirk}, editor = {Helbing, Dirk} } @book {2018, title = {Machine Learning for Ecology and Sustainable Natural Resource ManagementUse of Machine Learning (ML) for Predicting and Analyzing Ecological and {\textquoteleft}Presence Only{\textquoteright} Data: An Overview of Applications and a Good Outlook}, year = {2018}, pages = {27 - 61}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-96976-3}, doi = {10.1007/978-3-319-96978-7_2}, author = {Huettmann, Falk and Craig, Erica H. and Herrick, Keiko A. and Baltensperger, Andrew P. and Grant Humphries and Lieske, David J. and Miller, Katharine and Mullet, Timothy C. and Oppel, Steffen and Resendiz, Cynthia and Rutzen, Imme and Schmid, Moritz S. and Suwal, Madan K. and Young, Brian D.}, editor = {Grant Humphries and Magness, Dawn R. and Huettmann, Falk} } @book {2018, title = {Machine Learning for Ecology and Sustainable Natural Resource ManagementMachine Learning and {\textquoteleft}The Cloud{\textquoteright} for Natural Resource Applications: Autonomous Online Robots Driving Sustainable Conservation Management Worldwide?}, year = {2018}, pages = {353 - 377}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-96976-3}, doi = {10.1007/978-3-319-96978-7_18}, author = {Grant Humphries and Huettmann, Falk}, editor = {Grant Humphries and Magness, Dawn R. and Huettmann, Falk} } @inbook {2018, title = {Machine Learning in Wildlife Biology: Algorithms, Data Issues and Availability, Workflows, Citizen Science, Code Sharing, Metadata and a Brief Historical Perspective}, booktitle = {Machine Learning for Ecology and Sustainable Natural Resource Management}, year = {2018}, pages = {3 - 26}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-96976-3}, doi = {10.1007/978-3-319-96978-7_1}, author = {Grant Humphries and Huettmann, Falk}, editor = {Grant Humphries and Magness, Dawn R. and Huettmann, Falk} } @article {2018, title = {Machine learning, social learning and the governance of self-driving cars}, journal = {Social Studies of Science}, volume = {48}, year = {2018}, pages = {25-56}, abstract = {Self-driving cars, a quintessentially {\textquoteleft}smart{\textquoteright} technology, are not born smart. The algorithms that control their movements are learning as the technology emerges. Self-driving cars represent a high-stakes test of the powers of machine learning, as well as a test case for social learning in technology governance. Society is learning about the technology while the technology learns about society. Understanding and governing the politics of this technology means asking {\textquoteleft}Who is learning, what are they learning and how are they learning?{\textquoteright} Focusing on the successes and failures of social learning around the much-publicized crash of a Tesla Model S in 2016, I argue that trajectories and rhetorics of machine learning in transport pose a substantial governance challenge. {\textquoteleft}Self-driving{\textquoteright} or {\textquoteleft}autonomous{\textquoteright} cars are misnamed. As with other technologies, they are shaped by assumptions about social needs, solvable problems, and economic opportunities. Governing these technologies in the public interest means improving social learning by constructively engaging with the contingencies of machine learning.}, doi = {10.1177/0306312717741687}, author = {Jack Stilgoe} } @conference {2018, title = {Machines as Teammates: A Collaboration Research Agenda}, booktitle = {Hawaii International Conference on System Sciences}, year = {2018}, publisher = {Hawaii International Conference on System Sciences}, organization = {Hawaii International Conference on System Sciences}, doi = {10.24251/HICSS.2018.055}, url = {http://hdl.handle.net/10125/49887}, attachments = {https://waim.network/sites/crowston.syr.edu/files/SeeberEtAl_2018_MachinesAsTeammates.pdf}, author = {Seeber, Isabella and Bittner, Eva and Briggs, Robert O. and de Vreede, Gert-Jan and de Vreede, Triparna and Druckenmiller, Doug and Maier, Ronald and Merz, Alexander B. and Oeste-Rei{\ss}, Sarah and Randrup, Nils and Gerhard Schwabe and S{\"o}llner, Matthias} } @article {2018, title = {Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR)}, journal = {Systematic Reviews}, year = {2018}, month = {2018}, publisher = {Springer}, type = {Review}, abstract = {Systematic reviews (SR) are vital to health care, but have become complicated and time-consuming, due to the rapid expansion of evidence to be synthesised. Fortunately, many tasks of systematic reviews have the potential to be automated or may be assisted by automation. Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. Automation tools need to be able to work together, to exchange data and results. Therefore, we initiated the International Collaboration for the Automation of Systematic Reviews (ICASR), to successfully put all the parts of automation of systematic review production together. The first meeting was held in Vienna in October 2015. We established a set of principles to enable tools to be developed and integrated into toolkits. This paper sets out the principles devised at that meeting, which cover the need for improvement in efficiency of SR tasks, automation across the spectrum of SR tasks, continuous improvement, adherence to high quality standards, flexibility of use and combining components, the need for a collaboration and varied skills, the desire for open source, shared code and evaluation, and a requirement for replicability through rigorous and open evaluation. Automation has a great potential to improve the speed of systematic reviews. Considerable work is already being done on many of the steps involved in a review. The {\textquoteright}Vienna Principles{\textquoteright} set out in this paper aim to guide a more coordinated effort which will allow the integration of work by separate teams and build on the experience, code and evaluations done by the many teams working across the globe.}, keywords = {automation, Collaboration, Systematic review}, doi = {10.1186/s13643-018-0740-7}, author = {Elaine Beller and Justin Clark and Guy Tsafnat and Clive Adams and Heinz Diehl and Hans Lund and Mourad Ouzzani and Kristina Thayer and James Thomas and Tari Turner and Jun Xia and Karen Robinson and Paul Glasziou} } @article {2018, title = {Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR)}, journal = {Systematic Reviews}, volume = {7}, year = {2018}, month = {Jan-12-2018}, keywords = {science}, doi = {10.1186/s13643-018-0740-7}, author = {Elaine Beller and Justin Clark and Guy Tsafnat and Clive Adams and Heinz Diehl and Hans Lund and Mourad Ouzzani and Kristina Thayer and James Thomas and Tari Turner and Jun Xia and Karen Robinson and Paul Glasziou} } @article {2018, title = {Making Sure We Don{\textquoteright}t Forget the Basics When Using Machine Learning}, journal = {JNCI: Journal of the National Cancer Institute}, volume = {111}, year = {2018}, month = {Sep-10-2019}, pages = {529 - 530}, issn = {0027-8874}, doi = {10.1093/jnci/djy179}, author = {Winn, Aaron N and Neuner, Joan M} } @article {2018, title = {Managing talented worker in the era of new psychological contract}, journal = {Jurnal Aplikasi Manajemen}, volume = {16}, year = {2018}, month = {Jan-03-2018}, pages = {20 - 26}, issn = {16935241}, doi = {10.21776/ub.jam.2018.016.01.03}, author = {Haryadi, Haryadi and Anggraeni, Ade Irma and Ibrahim, Daing Nasir} } @article {2018, title = {Medicine and the rise of the robots: a qualitative review of recent advances of artificial intelligence in health}, journal = {BMJ Leader}, volume = {2}, year = {2018}, month = {Apr-06-2020}, pages = {59 - 63}, doi = {10.1136/leader-2018-000071}, author = {Loh, Erwin} } @article {2018, title = {A method to link advances in Artificial Intelligence to occupational abilities}, journal = {AEA Papers and Proceedings}, volume = {108}, year = {2018}, month = {Jan-01-2018}, pages = {54 - 57}, issn = {2574-0768}, doi = {10.1257/pandp.20181021}, author = {Felten, Edward W. and Raj, Manav and Seamans, Robert} } @article {2018, title = {New education models for the future of work force}, number = {IZA Policy Paper No. 143}, year = {2018}, month = {10/2018}, publisher = {Global Labor Organization }, keywords = {industry 4.0; robotics; sequential versus dual education systems; human resources management and policy}, url = {http://ftp.iza.org/pp143.pdf}, author = {Francesco Pastore} } @article {2018, title = {The nordic future of work drivers, institutions, and politics}, year = {2018}, institution = {Nordic Council of Ministers}, url = {https://norden.diva-portal.org/smash/get/diva2:1265618/FULLTEXT01.pdf}, author = {Jon Erik D{\o}lvik and Johan R{\o}ed Steen} } @article {2018, title = {Occupational Classifications With A Machine Learning Approach}, year = {2018}, keywords = {administrative data, machine learning, occupational classifications, transaction data, UMETRICS}, url = {https://www.iza.org/publications/dp/11738/occupational-classifications-a-machine-learning-approach}, author = {Akina Ikudo and Julia Lane and Joseph Staudt and Bruce A. Weinberg} } @article {2018, title = {The OD imperative to add inclusion to the algorithms of artificial intelligence}, year = {2018}, month = {01/2018}, abstract = {This article details concerns about the potential of machine learning processes to incorporate human biases inherent in social data into artificial intelligence systems that influence consequential decisions in the courts, business and financial transactions, and employment situations. It details incidents of biased decisions and recommendations made by artificial intelligence systems that have been given the patina of objectivity because they were made by machines supposedly free of human bias. The article offers suggestions for addressing the systemic biases that are impacting the viability, credibility, and fairness of machine learning processes and artificial intelligence system.}, url = {https://www.researchgate.net/publication/323830092_AI_x_I_AI2_The_OD_imperative_to_add_inclusion_to_the_algorithms_of_artificial_intelligence}, author = {Frederick A. Miller and Judith H. Katz and Roger Gans} } @article {2018, title = {The operating system for the digital enterprise}, journal = {Proceedings of the International Conference on Business Excellence}, volume = {12}, year = {2018}, month = {Jan-05-2018}, pages = {54 - 69}, doi = {10.2478/picbe-2018-0007}, author = {Anagnoste, Sorin} } @article {2018, title = {An overview of autonomous vehicles safety}, year = {2018}, abstract = {The new world of autonomous vehicles is posing many challenges to automotive safety. This paper at first describes the status of the ISO 26262 functional safety standard, with specific focus on its application to semiconductors. Then the paper proposes a way to analyze the reliability of a functional safety component, taking into account its safety goal. After that, the paper describes why functional safety and reliability are necessary but not sufficient for AVs: they need to be combined with security, with safety of intended functionality and ultimately with a {\textquotedblleft}responsibility sensitive safety{\textquotedblright}, in order to provide the overall level of trust that the community is expecting from autonomous vehicles.}, url = {https://ieeexplore.ieee.org/document/8353618} } @article {2018, title = {Ownership when AI robots do more of the work and earn more of the income}, journal = {Journal of Participation and Employee Ownership}, volume = {1}, year = {2018}, month = {Nov-06-2018}, pages = {74 - 95}, issn = {2514-7641}, doi = {10.1108/JPEO-04-2018-0015}, author = {Freeman, Richard B.} } @article {2018, title = {Paving the way for the future of work}, journal = {Canadian Public Policy}, year = {2018}, month = {Mar-11-2019}, pages = {1 - 10}, issn = {0317-0861}, doi = {10.3138/cpp.2018-012}, author = {Anani, Namir} } @article {2018, title = {Platforms at work: Automated hiring platforms and other new intermediaries in the organization of work}, year = {2018}, url = {http://dmgreene.net/wp-content/uploads/2018/09/Ajunwa-Greene-Platforms-at-Work-Accepted-Version.pdf}, author = {Ifeoma Ajunwa and Daniel Greene} } @article {2018, title = {The predictions on the future of labour are not grounded; some arguments for a bayesian approach}, journal = {Postmodern Openings}, volume = {9}, year = {2018}, month = {Jan-09-2020}, pages = {36 - 63}, issn = {20680236}, doi = {10.18662/po/35}, author = {Rotila, Viorel} } @article {2018, title = {A principled machine learning framework improves accuracy of stage II colorectal cancer prognosis}, journal = {npj Digital Medicine}, volume = {1}, year = {2018}, month = {Jan-12-2018}, doi = {10.1038/s41746-018-0057-x}, author = {Dimitriou, Neofytos and Arandjelovi{\'c}, Ognjen and Harrison, David J. and Caie, Peter D.} } @article {2018, title = {The productivity j-curve: How intangibles complement general purpose technologies}, year = {2018}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w25148}, author = {Brynjolfsson, Erik and Rock, Daniel and Syverson, Chad} } @article {2018, title = {Promethean AI uses artificial intelligence to help artists fill out game worlds}, year = {2018}, keywords = {AI use cases}, url = {https://venturebeat.com/2018/07/18/promethean-ai-uses-artificial-intelligence-to-help-artists-fill-out-game-worlds/}, author = {Dean Takahashi} } @proceedings {2018, title = {Recent advances in social \& cognitive robotics and imminent ethical challenges}, volume = {211}, year = {2018}, keywords = {ethics}, url = {https://www.atlantis-press.com/proceedings/rais-18/25902731}, author = {Ali Meghdari and Minoo Alemi} } @article {2018, title = {Recommendations to improve the nation{\textquoteright}s workforce and labor market information system}, year = {2018}, month = {01/2018}, url = {https://www.doleta.gov/wioa/wiac/docs/Second_Draft_of_the_WIAC_Final_Report.pdf} } @article {2018, title = {Reflections on the meaning of automated education}, journal = {education policy analysis archives}, volume = {26}, year = {2018}, month = {May-01-2018}, pages = {115}, doi = {10.14507/epaa.26.3863}, author = {Coelho, Heitor} } @article {2018, title = {Reinventing capitalism to address automation: Sharing work to secure employment and income}, journal = {Competition \& Change}, volume = {22}, year = {2018}, month = {Jan-08-2020}, pages = {343 - 362}, issn = {1024-5294}, doi = {10.1177/1024529418783579}, author = {Rafi Khan, Shahrukh} } @article {aroyo2018reports, title = {Reports of the Workshops Held at the Sixth AAAI Conference on Human Computation and Crowdsourcing}, journal = {AI Magazine}, volume = {39}, year = {2018}, pages = {57{\textendash}63}, author = {Aroyo, Lora and Dumitrache, Anca and Jeffrey V Nickerson and Lease, Matthew and Michelucci, Pietro} } @conference {2018, title = {Research on the application of artificial intelligence technology in human resource management}, booktitle = {2018 2nd International Conference on Systems, Computing, and Applications2018 2nd International Conference on Systems, Computing, and Applications (SYSTCA 2018)}, year = {2018}, publisher = {Francis Academic Press}, organization = {Francis Academic Press}, doi = {10.25236/systca.18.038} } @article {2018, title = {Researchably{\textquoteright}s AI parsers medical research for pharmaceutical companies}, year = {2018}, month = {10/2018}, url = {https://venturebeat.com/2018/10/02/researchablys-ai-parses-medical-research-for-pharmaceutical-companies/}, author = {Kyle Wiggers} } @conference {2018, title = {Rethinking AI strategy and policy as entangled super wicked problems}, booktitle = {the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES {\textquoteright}18}, year = {2018}, pages = {122 - 122}, publisher = {ACM Press}, organization = {ACM Press}, address = {New Orleans, LA, USANew York, New York, USA}, isbn = {9781450360128}, doi = {10.1145/3278721.3278746}, author = {Gruetzemacher, Ross} } @article {2018, title = {Robot Assisted Surgical Ward Rounds: Virtually Always There}, journal = {Journal of Innovation in Health Informatics}, volume = {25}, year = {2018}, month = {Sep-03-2018}, pages = {041}, issn = {2058-4555}, doi = {10.14236/jhi.v25i1.982}, author = {Stefanie M. Croghan and Paul Carroll and Sarah Reade and Amy E Gillis and Paul F. Ridgway} } @article {2018, title = {Robot companions: A legal and ethical analysis}, journal = {The Information Society}, volume = {34}, year = {2018}, month = {Mar-05-2020}, pages = {130 - 140}, issn = {0197-2243}, doi = {10.1080/01972243.2018.1444249}, author = {Bertolini, Andrea and Aiello, Giuseppe} } @article {2018, title = {Robot revolution: Myth or reality }, journal = {Proceedings of the IEEE}, volume = {106}, year = {2018}, month = {Jan-12-2018}, pages = {2095 - 2097}, issn = {0018-9219}, doi = {10.1109/JPROC.2018.2877520}, author = {Joel Trussell, H.} } @article {2018, title = {Robot vs. tax inspector or how the fourth industrial revolution will change the tax system: a review of problems and solutions}, journal = {Journal of Tax Reform}, volume = {4}, year = {2018}, month = {Jan-01-2018}, pages = {6 - 26}, abstract = {The fourth Industiral Revolution and the accelerated development of cyber-physical technologies lead to essential changes in national tax systems and international taxation. The main areas in which taxation meets cyber-physical technologies are digitization, robotization, M2M and blockchain technologies. Each of these areas has its own opportunities and problems. Three main approaches towards possible solutions for these new problems are identified. The first is to try to apply taxation to new cyber-physical technologies and products of their application. This approach includes the OECD{\textquoteright}s Action 1 plan on Base Erosion and Profit Shifting. It also includes the spread of traditional taxes on new objects - personal data, cryptocurrencies, imputed income of robots. The second is to replace digital transactions and shortfalls in revenues by traditional objects of taxation in the form of tangible assets and people and / or increase tax pressure (including by improving tax administration with use of Big Data) and the degree of progressiveness of taxes already levied on such objects. The third approach is to set a course on building a new tax space with smart taxes based on real-time principles, smart contracts and Big Data. This implies a transition to automatic taxation using blockchain technologies, which focus on the functions of applying distributed ledgers of business transactions in real-time. At present, the general trends are such that the first and second are prevalent, which is manifested in an increase in the relative importance of property, sales and employment taxes. Concerning the third approach, any movement in this direction is still facing a number oftechnical and other problems and is thus being discussed mainly at the conceptual level}, keywords = {blockchain, cyber-physical technologies, digitization, taxes in Big Data, taxes on cryptocurrencies, taxes on digital goods, taxes on robots}, issn = {24128872}, doi = {10.15826/jtr.2018.4.1.042}, url = {https://jtr.urfu.ru/en/archive/journal/95/article/1113/}, author = {Vishnevsky, Valentine P. and Chekina, Viktoriia D.} } @article {2018, title = {Robotic process automation}, journal = {Business \& Information Systems Engineering}, volume = {60}, year = {2018}, month = {Jan-08-2018}, pages = {269 - 272}, issn = {2363-7005}, doi = {10.1007/s12599-018-0542-4}, author = {van der Aalst, Wil M. P. and Bichler, Martin and Heinzl, Armin} } @article {2018, title = {Robotic Process Automation for Auditing}, journal = {Journal of Emerging Technologies in Accounting}, volume = {15}, year = {2018}, month = {Jan-07-2018}, pages = {1 - 10}, issn = {1554-1908}, doi = {10.2308/jeta-10589}, author = {Moffitt, Kevin C. and Rozario, Andrea M. and Vasarhelyi, Miklos A.} } @article {2018, title = {Robots and computers enhance us more than they replace us}, journal = {The American Economist}, year = {2018}, month = {Oct-08-2018}, pages = {056943451879267}, issn = {0569-4345}, doi = {10.1177/0569434518792674}, author = {Diamond, Arthur M.} } @article {2018, title = {Robots and Organization Studies: Why Robots Might Not Want to Steal Your Job}, journal = {Organization Studies}, year = {2018}, month = {04/2018}, pages = {017084061876556}, edition = {2}, abstract = {A number of recent high-profile studies of robotics and artificial intelligence (or AI) in economics and sociology have predicted that many jobs will soon disappear due to automation, with few new ones replacing them. While techno-optimists and techno-pessimists contest whether a jobless future is a positive development or not, this paper points to the elephant in the room. Despite successive waves of computerization (including advanced machine learning), jobs have not disappeared. And probably won{\textquoteright}t in the near future. To explain why, some basic insights from organization studies can make a contribution. I propose the concept of {\textquoteright}bounded automation{\textquoteright} to demonstrate how organizational forces mould the application of technology in the employment sector. If work does not vanish in the age of AI, then poorly paid jobs will most certainly proliferate, I argue. Finally, a case is made for the scholarly community to engage with wider social justice concerns. This I term public organization studies.}, keywords = {artificial intelligence, bounded automation, neoliberalism, public organization studies, Robotics, unemployment, work}, issn = {0170-8406}, doi = {10.1177/0170840618765568}, url = {http://journals.sagepub.com/doi/10.1177/0170840618765568}, author = {Fleming, Peter} } @article {2018, title = { Robots worldwide: The impact of automation on employment and trade}, number = {36}, year = {2018}, month = {10/2018}, keywords = {economics of automation, Employment, off-shoring, re-shoring, robot, technology}, url = {https://www.ilo.org/wcmsp5/groups/public/---dgreports/---inst/documents/publication/wcms_648063.pdf}, author = {Francesco Carnonero and Ekkehard Ernst and Enzo Weber} } @book {2018, title = {The role of technological progress and structural change in the labour market}, year = {2018}, pages = {15 - 41}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-90547-1}, issn = {2511-2023}, doi = {10.1007/978-3-319-90548-8_2}, author = {Bosio, Giulio and Cristini, Annalisa}, editor = {Bosio, Giulio and Minola, Tommaso and Origo, Federica and Tomelleri, Stefano} } @article {2018, title = {Should we fear the robot revolution?}, journal = {Journal of Monetary Economics}, volume = {97}, year = {2018}, month = {Jan-08-2018}, pages = {117 - 148}, issn = {03043932}, doi = {10.1016/j.jmoneco.2018.05.014}, author = {Berg, Andrew and Buffie, Edward F. and Zanna, Luis-Felipe} } @article {2018, title = {Skill shift automation and the future of the workforce}, year = {2018}, month = {05/2018}, url = {https://www.mckinsey.com/featured-insights/future-of-work/skill-shift-automation-and-the-future-of-the-workforce}, author = {Jaccques Bughin and Eric Hazan and Susan Lund and Peter Dahlstrom and Anna Wiesinger and Amresh Subramaniam} } @book {2018, title = {The social consequences of the digital revolution}, volume = {6}, year = {2018}, publisher = {Edizioni Ca{\textquoteright} Foscari}, organization = {Edizioni Ca{\textquoteright} Foscari}, address = {Venice}, isbn = {978-88-6969-274-1}, issn = {2610-9085}, doi = {10.30687/2610-968910.30687/978-88-6969-273-410.30687/978-88-6969-273-4/008}, url = {http://edizionicafoscari.unive.it/collane/societa-e-trasformazioni-sociali/http://edizionicafoscari.unive.it/libri/978-88-6969-274-1/http://edizionicafoscari.unive.it/libri/978-88-6969-274-1/the-social-consequences-of-the-digital-revolution/}, author = {Basso, Pietro and Chiaretti, Giuliana and Krzywdzinski, Martin and Gerber, Christine and Evers, Maren} } @article {2018, title = {Social machines and the Internet : What went wrong?}, journal = {BiD: textos universitaris de biblioteconomia i documentaci�}, year = {2018}, month = {Jan-01-2018}, issn = {15755886}, doi = {10.1344/BiD2018.41.8} } @article {2018, title = {Social robots as cultural objects: The sixth dimension of dynamicity?}, journal = {The Information Society}, volume = {34}, year = {2018}, month = {Mar-05-2020}, pages = {141 - 152}, issn = {0197-2243}, doi = {10.1080/01972243.2018.1444253}, author = {Fortunati, Leopoldina and Sarrica, Mauro and Ferrin, Giovanni and Brondi, Sonia and Honsell, Furio} } @article {2018, title = {Socio-economic and legal impact of autonomous robotics and ai entities}, journal = {IEEE Technology and Society Magazine}, volume = {37}, year = {2018}, month = {Jan-03-2018}, pages = {70 - 79}, issn = {0278-0097}, doi = {10.1109/MTS.2018.2795120}, author = {Broman, Morgan M. and Finckenberg-Broman, Pamela} } @article {2018, title = {Sustainable skills for the world of work in the digital age}, journal = {Systems Research and Behavioral Science}, volume = {35}, year = {2018}, month = {Jan-07-2018}, pages = {399 - 405}, doi = {10.1002/sres.v35.410.1002/sres.2540}, author = {Sousa, Maria Jos{\'e} and Wilks, Daniela}, editor = {Laszlo, Alexander} } @article {2018, title = {System architecture of a driverless electric car in the grand cooperative driving challenge}, journal = {IEEE Intelligent Transportation Systems Magazine}, volume = {10}, year = {2018}, month = {Jan-21-2018}, pages = {47 - 59}, issn = {1939-1390}, doi = {10.1109/MITS.2017.2776135}, author = {Xu, Philippe and Dherbomez, Gerald and Hery, Elwan and Abidli, Abderrahmen and Bonnifait, Philippe} } @article {2018, title = {Technology and employment: Mass unemployment or job creation? Empirical evidence from European patenting firms}, journal = {Research Policy}, volume = {47}, year = {2018}, month = {Jan-11-2018}, pages = {1762 - 1776}, issn = {00487333}, doi = {10.1016/j.respol.2018.06.008}, author = {Van Roy, Vincent and V{\'e}rtesy, D{\'a}niel and Vivarelli, Marco} } @article {2018, title = {Technology, productivity and employment: an empirical analysis of indian industries}, journal = {Journal of Business Thought}, volume = {9}, year = {2018}, month = {Jan-04-2020}, pages = {1 - 10}, doi = {10.18311/jbt/2018/21173}, author = {Aggarwal, Suresh Chand} } @article {2018, title = {Technology-induced bias in the theory of evidence-based medicine}, journal = {Journal of Evaluation in Clinical Practice}, volume = {24}, year = {2018}, month = {Jan-10-2018}, pages = {945 - 949}, doi = {10.1111/jep.12972}, author = {Eustace, Scott} } @article {2018, title = {Techno-unemployment: A framework for assessing the effects of information and communication technologies on work}, journal = {Telematics and Informatics}, volume = {35}, year = {2018}, month = {Jan-10-2018}, pages = {1863 - 1876}, issn = {07365853}, doi = {10.1016/j.tele.2018.05.013}, author = {Garcia-Murillo, Martha and MacInnes, Ian and Bauer, Johannes M.} } @conference {2018, title = {Theorizing human and bot co - production effects on information quality}, booktitle = {Thirty - n inth International Conference on Information Systems,}, year = {2018}, url = {https://icis2018postergallery.weebly.com/416-social-media-and-digital-collaboration.html}, author = {Amber G. Young and Amber G. Young and Gerald C. Kane} } @article {2018, title = {Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So}, journal = {The NewYork Times}, year = {2018}, url = {https://www.nytimes.com/2018/06/20/technology/deep-learning-artificial-intelligence.html}, author = {Steve Lohr} } @article {2018, title = {This time it might be different: Analysis of the impact of digitalization on the labour market}, journal = {European Scientific Journal ESJ}, volume = {14}, year = {2018}, month = {Jul-12-2020}, issn = {18577881}, doi = {10.19044/esj.2018.v14n36p68}, author = {Lovergine, Saverio and Pellero, Alberto} } @conference {2018, title = {Towards a Sociological Conception of Artificial Intelligence}, booktitle = {Artificial General Intelligence (AGI)}, year = {2018}, publisher = {Springer}, organization = {Springer}, abstract = {Social sciences have been always formed and influenced by the development of society, adjusting the conceptual, methodological, and theoretical frameworks to emerging social phenomena. In recent years, with the leap in the advancement of Artificial Intelligence (AI) and the proliferation of its everyday applications, "non-human intelligent actors" are increasingly becoming part of the society. This is manifested in the evolving realms of smart home systems, autonomous vehicles, chatbots, intelligent public displays, etc. In this paper, we present a prospective research project that takes one of the pioneering steps towards establishing a "distinctively sociological" conception of AI. Its first objective is to extract the existing conceptions of AI as perceived by its technological developers and (possibly differently) by its users. In the second part, capitalizing on a set of interviews with experts from social science domains, we will explore the new imaginable conceptions of AI that do not originate from its technological possibilities but rather from societal necessities. The current formal ways of defining AI are grounded in the technological possibilities, namely, machine learning methods and neural network models. Buy what exactly is AI as a social phenomenon, which may act on its own, can be blamed responsible for ethically problematic behavior, or even endanger people{\textquoteright}s employment? We argue that such conceptual investigation is a crucial step for further empirical studies of phenomena related to AI{\textquoteright}s position in current societies, but also will open up ways for critiques of new technological advancements with social consequences in mind from the outset.}, keywords = {artificial intelligence, Social sciences, Sociology}, doi = {10.1007/978-3-319-97676-1_13}, author = {Jakub Mlynar and Hamed S. Alavi and Himanshu Verma and Lorenzo Cantoni} } @conference {2018, title = {Towards an understanding of how chatbots create value}, booktitle = {Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences}, year = {2018}, publisher = {Hawaii International Conference on System Sciences}, organization = {Hawaii International Conference on System Sciences}, doi = {10.24251/HICSS.2018.255}, author = {Stoeckli, Emanuel and Uebernickel, Falk and Brenner, Walter} } @article {2018, title = {Transparency and fairness in machine learning applications}, journal = {Texas A\&M Journal of Property Law}, volume = {4}, year = {2018}, url = {https://scholarship.law.tamu.edu/cgi/viewcontent.cgi?article=1079\&context=journal-of-property-law}, author = {Jim Shook and Robyn Smith and Alex Antonio} } @article {2018, title = {An Uber ethical dilemma: examining the social issues at stake}, journal = {Journal of Information, Communication and Ethics in Society}, volume = {16}, year = {2018}, month = {Jan-08-2019}, pages = {261 - 274}, issn = {1477-996X}, doi = {10.1108/JICES-03-2018-0024}, url = {https://www.emerald.com/insight/content/doi/10.1108/JICES-03-2018-0024/full/htmlhttps://www.emeraldinsight.com/doi/full/10.1108/JICES-03-2018-0024https://www.emeraldinsight.com/doi/full-xml/10.1108/JICES-03-2018-0024}, author = {Chee, Florence M.} } @conference {2018, title = {Understanding Chatbot-mediated Task Management}, booktitle = {the 2018 CHI ConferenceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI {\textquoteright}18}, year = {2018}, pages = {1 - 6}, publisher = {ACM Press}, organization = {ACM Press}, address = {Montreal QC, CanadaNew York, New York, USA}, isbn = {9781450356206}, doi = {10.1145/317357410.1145/3173574.3173632}, author = {Toxtli, Carlos and Monroy-Hern{\'a}ndez, Andr{\'e}s and Cranshaw, Justin} } @book {2018, title = {Understanding tasks, automation, and the national health service}, volume = {10766}, year = {2018}, pages = {544 - 549}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-78104-4}, issn = {0302-9743}, doi = {10.1007/978-3-319-78105-1_60}, author = {Willis, Matt and Meyer, Eric T.}, editor = {Chowdhury, Gobinda and McLeod, Julie and Gillet, Val and Willett, Peter} } @article {2018, title = {The value of work: Addressing the future of work through the lens of solidarity}, journal = {Bioethics}, volume = {32}, year = {2018}, month = {Jan-11-2018}, pages = {585 - 592}, doi = { 10.1111/bioe.12507}, author = {Prainsack, Barbara and Buyx, Alena}, editor = {Buyx, Alena and Prainsack, Barbara} } @article {2018, title = {When Will AI Exceed Human Performance? Evidence from AI Experts}, year = {2018}, url = {https://jair.org/index.php/jair/article/download/11222/26431/}, author = {Katja Grace and John Salvatier and Allan Dafoe and Baobao Zhang and Owain Evans} } @article {2018, title = {Will artificial intelligence solve the human resource crisis in healthcare?}, journal = {BMC Health Services Research}, volume = {18}, year = {2018}, month = {Jan-12-2018}, doi = {10.1186/s12913-018-3359-4}, author = {Mesk{\'o}, Bertalan and Het{\'e}nyi, Gergely and Gy{\H o}rffy, Zsuzsanna} } @article {2018, title = {Work and organizational psychology looks at the fourth industrial revolution: How to support workers and organizations? }, journal = {Frontiers in Psychology}, volume = {9}, year = {2018}, month = {Apr-11-2020}, doi = {10.3389/fpsyg.2018.02365}, author = {Ghislieri, Chiara and Molino, Monica and Cortese, Claudio G.} } @conference {2018, title = {Work that Enables Care: Understanding Tasks, Automation, and the National Health Service}, booktitle = {iConference}, year = {2018}, publisher = {Springer}, organization = {Springer}, abstract = {Automation of jobs is discussed as a threat to many job occupations, but in the UK healthcare sector many view technology and automation as a way to save a threatened system. However, existing quantitative models that rely on occupation-level measures of the likelihood of automation suggest that few healthcare occupations are susceptible to automation. In order to improve these quantitative models, we focus on the potential impacts of task-level automation on health work, using qualitative ethnographic research to understand the mundane information work in general practices. By understanding the detailed tasks and variations of information work, we are building a more complete and accurate understanding of how healthcare staff work and interact with technology and with each other, often mediated by technology.}, keywords = {automation, Ethnography, Primary care, Sociotechnical}, doi = {10.1007/978-3-319-78105-1_60}, author = {Matt WIllis and Eric T. Meyer} } @article {2018, title = {Working and organizing in the age of the learning algorithm}, journal = {Information and Organization}, volume = {28}, year = {2018}, publisher = {Elsevier}, chapter = {62-70}, abstract = {Learning algorithms, technologies that generate responses, classifications, or dynamic predictions that resemble those of a knowledge worker, raise important research questions for organizational scholars related to work and organizing. We suggest that such algorithms are distinguished by four consequential aspects: black-boxed performance, comprehensive digitization, anticipatory quantification, and hidden politics. These aspects are likely to alter work and organizing in qualitatively different ways beyond simply signaling an acceleration of long-term technology trends. Our analysis indicates that learning algorithms will transform expertise in organizations, reshape work and occupational boundaries, and offer novel forms of coordination and control. Thus, learning algorithms can be considered performative due to the extent to which their use can shape and alter work and organizational realities. Their rapid deployment requires scholarly attention to societal issues such as extent to which the algorithm is authorized to make decisions, the need to incorporate morality in the technology, and their digital iron-cage potential.}, doi = {10.1016/j.inforandorg.2018.02.005}, author = {Samer Faraj and Stella Pachidi and Karla Sayegh} } @article {2018, title = {Working and organizing in the age of the learning algorithm}, journal = {Information and Organization}, volume = {28}, year = {2018}, month = {Jan-03-2018}, pages = {62 - 70}, issn = {14717727}, doi = {10.1016/j.infoandorg.2018.02.005}, author = {Faraj, Samer and Pachidi, Stella and Sayegh, Karla} } @article {2017, title = {6 areas of AI and machine learning to watch closely}, year = {2017}, url = {https://medium.com/@NathanBenaich/6-areas-of-artificial-intelligence-to-watch-closely-673d590aa8aa}, author = {Nathan Benaich} } @article {2017, title = {9 IT projects primed for machine learning}, year = {2017}, note = {

With AI quickly becoming strategic, look for projects that can give you some quick business wins andhelp you gain the skills to apply machine learning more broadly.

}, month = {10/2017}, url = {https://www.cio.com/article/3231650/9-it-projects-primed-for-machine-learning.html}, author = {Mary Branscombe} } @inbook {2017, title = {Agents as collaborating team members}, year = {2017}, month = {09/2017}, publisher = {EBSCO}, organization = {EBSCO}, keywords = {bots}, url = {https://www.taylorfrancis.com/books/e/9781315593166/chapters/10.1201/9781315593166-7}, author = {Abhijit V. Deshmukh and Sara A.McComb and Christian Wernz} } @article {2017, title = {AI AND THE GHOST IN THE MACHINE}, year = {2017}, url = {http://hackaday.com/2017/02/06/ai-and-the-ghost-in-the-machine/}, author = {Cameron Coward} } @article {2017, title = {AI can take over our mundane tasks}, year = {2017}, month = {10/2017}, abstract = {

Here{\textquoteright}s how human workers can learn new, more stimulating skills

}, url = {https://www.vox.com/2017/10/18/16492156/coaching-cloud-future-work-jobs-artificial-intelligence-ai-enterprise-employee-training}, author = {Gordon Ritter} } @article {2017, title = {The AI detectives}, volume = {357}, year = {2017}, month = {Jul-07-2017}, pages = {22 - 27}, issn = {0036-8075}, doi = {10.1126/science.357.6346.22}, author = {Voosen, Paul} } @article {2017, title = {AI has become so popular in picking stocks that it{\textquoteright}s become ineffective}, year = {2017}, note = {

Everyone mining the similar data, neutralizing its alpha

}, month = {10/2017}, url = {https://www.marketwatch.com/story/ai-has-become-so-popular-in-picking-stocks-that-its-become-ineffective-2017-10-06}, author = {Ryan Vlastelica} } @article {2017, title = {AI in Action: Combing the genome for the roots of autism}, journal = {Science}, volume = {357}, year = {2017}, month = {Jul-07-2017}, pages = {25 - 25}, issn = {0036-8075}, doi = {10.1126/science.357.6346.25}, author = {Pennisi, Elizabeth} } @article {2017, title = {AI in Action: Machines that make sense of the sky}, journal = {Science}, volume = {357}, year = {2017}, month = {Jul-07-2017}, pages = {26 - 26}, issn = {0036-8075}, doi = {10.1126/science.357.6346.26}, author = {Sokol, Joshua} } @article {2017, title = {AI in contact centers}, journal = {Communications of the ACM}, volume = {60}, year = {2017}, month = {Dec-07-2018}, pages = {18 - 19}, issn = {00010782}, doi = {10.1145/312734310.1145/3105442}, author = {Kirkpatrick, Keith} } @article {2017, title = {AI will create 800,000 jobs and $1.1 trillion revenue by 2021: Salesforce}, journal = {salesforce}, year = {2017}, month = {06/2017}, type = {AI}, url = {https://www.salesforce.com/company/news-press/press-releases/2017/06/170614/}, author = {Tas Bindi} } @article {2017, title = {Algorithmic IF {\textellipsis} THEN rules and the conditions and consequences of power}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {45 - 62}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1156141}, author = {Neyland, Daniel and M{\"o}llers, Norma} } @article {2017, title = {The algorithmic imaginary: Exploring the ordinary affects of Facebook algorithms}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {30 - 44}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1154086}, author = {Bucher, Taina} } @article {2017, title = {Algorithmically recognizable: Santorum{\textquoteright}s google problem, and google{\textquoteright}s santorum problem}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {63 - 80}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1199721}, author = {Gillespie, Tarleton} } @article {2017, title = {Algorithms (and the) everyday}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {137 - 150}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1200645}, author = {Willson, Michele} } @article {2017, title = {Anxiety about automation and jobs: Will we see anti-tech laws?}, journal = {AEIdeas}, year = {2017}, month = {07/2017}, type = {economics}, url = {https://www.aei.org/economics/anxiety-about-automation-and-jobs-will-we-see-anti-tech-laws/}, author = {James Pethokoukis} } @conference {2017, title = {Are We Safe Enough in the Future of Artificial Intelligence? A Discussion on Machine Ethics and Artificial Intelligence Safety}, booktitle = {Scientific Methods in Academic Research and Teaching International Conference}, year = {2017}, pages = {184-197}, abstract = {Nowadays, there is a serious anxiety on the existence of dangerous intelligent systems and it is not just a science-fiction idea of evil machines like the ones in well-known Terminator movie or any other movies including intelligent robots - machines threatening the existence of humankind. So, there is a great interest in some alternative research works under the topics of Machine Ethics, and Existential Risks. The objective of this study is to provide a general discussion about the expressed research topics and try to find some answers to the question of {\textquoteright}Are we safe enough in the future of Artificial Intelligence?{\textquoteright}. In detail, the discussion includes a comprehensive focus on {\textquoteright}dystopic{\textquoteright} scenarios, enables interested researchers to think about some {\textquoteright}moral dilemmas{\textquoteright} and family have some ethical outputs that are considerable for developing good intelligent systems. From a general perspective, the discussion taken here is a good opportunity to improve awareness on the mentioned, remarkable research topics associated with not only Artificial Intelligence but also many other natural and social sciences taking role in the humankind}, keywords = {artificial intelligence, artificial intelligence safety, future of artificial intelligence, machine ethics, machine learning}, author = {Utku K{\"o}se} } @article {2017, title = {Artificial intelligence and the modern productivity paradox: a clash of expectations and statistics}, number = {24001}, year = {2017}, month = {11/2017}, keywords = {economics of automation}, url = {http://www.nber.org/papers/w24001}, author = {Erik Brynjolfsson and Daniel Rock and Chad Syverson} } @book {2017, title = {Artificial Intelligence and the two singularities}, series = {A Chapman \& Hall Book}, year = {2017}, month = {08/2018}, publisher = {EBSCO}, organization = {EBSCO}, edition = {1st}, url = {https://www.amazon.com/Artificial-Intelligence-Singularities-Chapman-Robotics/dp/0815368534}, author = {Calum Chace} } @article {2017, title = {Artificial Intelligence For Social Good}, year = {2017}, note = {Sponsored by the Computing Community Consortium (CCC)}, url = {https://cra.org/ccc/wp-content/uploads/sites/2/2016/04/AI-for-Social-Good-Workshop-Report.pdf}, author = {Gregory D. Hager and Ann Drobnis and Fei Fang and Rayid Ghani and Amy Greenwald and Terah Lyons and David C. Parkes and Jason Schultz and Suchi Saria and Stephen F. Smith and Milind Tambe} } @article {2017, title = {Artificial intelligence in healthcare: past, present and future}, journal = {Stroke and Vascular Neurology}, volume = {2}, year = {2017}, month = {Aug-12-2018}, pages = {230 - 243}, issn = {2059-8688}, doi = {10.1136/svn-2017-000101}, author = {Jiang, Fei and Jiang, Yong and Zhi, Hui and Dong, Yi and Li, Hao and Ma, Sufeng and Wang, Yilong and Dong, Qiang and Shen, Haipeng and Wang, Yongjun} } @article {2017, title = {Artificial intelligence in research}, journal = {Science}, volume = {357}, year = {2017}, month = {Jul-07-2017}, pages = {28 - 30}, issn = {0036-8075}, doi = {10.1126/science.357.6346.28}, author = {Musib, Mrinal and Wang, Feng and Tarselli, Michael A. and Yoho, Rachel and Yu, Kun-Hsing and Andr{\'e}s, Rigoberto Medina and Greenwald, Noah F. and Pan, Xubin and Lee, Chien-Hsiu and Zhang, Jian and Dutton-Regester, Ken and Johnston, Jake Wyatt and Sharafeldin, Icell Mahmoud} } @article {2017, title = {Artificial Intelligence Index}, year = {2017}, url = {https://aiindex.org/2017-report.pdf}, author = {Yoav Shoham and Raymond Perrault and Erik Brynjolfsson and Jack Clark} } @article {2017, title = {Artificial Intelligence: The next digital frontier}, year = {2017}, url = {https://www.mckinsey.com/~/media/McKinsey/Industries/Advanced\%20Electronics/Our\%20Insights/How\%20artificial\%20intelligence\%20can\%20deliver\%20real\%20value\%20to\%20companies/MGI-Artificial-Intelligence-Discussion-paper.ashx}, author = {Jaccques Bughin and Eric Hazan and Sree Ramaswamy and Michael Chui and Tera Allas and Peter Dahlstrom and Nicolaus Henke and Monica Trench} } @article {2017, title = {As amazon pushes forward with robots, workers find new roles}, year = {2017}, month = {10/2017}, url = {https://www.nytimes.com/2017/09/10/technology/amazon-robots-workers.html}, author = {Nick Wingfield} } @article {2017, title = {Assessing drivers{\textquoteright} response during automated driver support system failures with non-driving tasks}, journal = {Journal of Safety Research}, volume = {61}, year = {2017}, month = {Jan-06-2017}, pages = {149 - 155}, issn = {00224375}, doi = {10.1016/j.jsr.2017.02.009}, author = {Shen, Sijun and Neyens, David M.} } @article {2017, title = {Automation, computerisation and future employment in Singapore}, journal = {Journal of Southeast Asian Economies}, volume = {34}, year = {2017}, keywords = {economics of automation}, url = {https://mpra.ub.uni-muenchen.de/79961/}, author = {King Fuei Lee} } @article {2017, title = {Automation, computerization and future employment in Singapore}, journal = {Southeast Asian Economies}, volume = {34}, year = {2017}, month = {Jul-08-2019}, pages = {388 - 399}, issn = {2339-5095}, doi = {10.1355/ae34-2h}, author = {Fuei, Lee King} } @proceedings {2017, title = {Automation of a Business Process Using Robotic Process Automation (RPA): A Case Study}, volume = {742}, year = {2017}, pages = {65 - 71}, publisher = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-66962-5}, issn = {1865-0929}, doi = {10.1007/978-3-319-66963-2_7}, author = {Aguirre, Santiago and Rodriguez, Alejandro}, editor = {Figueroa-Garc{\'\i}a, Juan Carlos and L{\'o}pez-Santana, Eduyn Ramiro and Villa-Ram{\'\i}rez, Jos{\'e} Luis and Ferro-Escobar, Roberto} } @article {2017, title = {Big data and organizational design {\textendash} the brave new world of algorithmic management and computer augmented transparency}, journal = {Innovation}, volume = {19}, year = {2017}, month = {Feb-01-2017}, pages = {23 - 30}, issn = {1447-9338}, doi = {10.1080/14479338.2016.1252043}, author = {Schildt, Henri} } @book {2017, title = {Big Data in Organizations and the Role of Human Resource Management}, year = {2017}, url = {https://www.jstor.org/stable/j.ctv9hj9z6.1}, author = {Peter Lang} } @proceedings {9999, title = {Blending machine and human learning processes}, year = {2017}, abstract = {

Citizen science projects rely on contributions from volunteers to achieve their scientific goals and so face a dilemma: providing volunteers with explicit training might increase the quality of contributions, but at the cost of losing the work done by newcomers during the training period, which for many is the only work they will contribute to the project. Based on research in cognitive science on how humans learn to classify images, we have designed an approach to use machine learning to guide the presentation of tasks to newcomers that help them more quickly learn how to do the image classification task while still contributing to the work of the project. A Bayesian model for tracking this learning is presented.

}, doi = {10.24251/HICSS.2017.009}, url = {http://hdl.handle.net/10125/41159}, attachments = {https://waim.network/sites/crowston.syr.edu/files/training\%20v3\%20to\%20share_0.pdf}, author = {Kevin Crowston and Carsten {\O}sterlund and Lee, Tae Kyoung} } @article {2017, title = {Can ford turn itself find a tech company}, year = {2017}, url = {https://www.nytimes.com/interactive/2017/11/09/magazine/tech-design-autonomous-future-cars-detroit-ford.html}, author = {Kevin Roose} } @article {2017, title = {The changing nature of work: Careers, identities, and work lives in the 21 century}, journal = {Academy of Management Discoveries}, volume = {3}, year = {2017}, month = {Jan-06-2017}, pages = {111 - 115}, doi = {10.5465/amd.2017.0034}, author = {Barley, Stephen R. and Bechky, Beth A. and Milliken, Frances J.} } @proceedings {2017, title = {Chatbots as assistants, an architectural framework}, year = {2017}, url = {https://dl.acm.org/citation.cfm?id=3172805}, author = {Adam Di Prospera and Nojan norouzi and Morios Fokaefs and Marin Litoiu} } @article {2017, title = {Comparing the initial human-human and human-AI social interactions}, journal = {Computers in Human Behavior}, volume = {72}, year = {2017}, month = {Jan-07-2017}, pages = {432 - 440}, issn = {07475632}, doi = {10.1016/j.chb.2017.02.067}, author = {Mou, Yi and Xu, Kun} } @article {2017, title = {Computer technology and probable job destructions in Japan: An evaluation}, journal = {Journal of the Japanese and International Economies}, volume = {43}, year = {2017}, month = {Jan-03-2017}, pages = {77 - 87}, issn = {08891583}, doi = {10.1016/j.jjie.2017.01.001}, author = {David, Benjamin} } @article {2017, title = {Computing brains: Learning algorithms and neurocomputation in the smart city}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {81 - 99}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1181194}, author = {Williamson, Ben} } @article {2017, title = {The cyberscientist}, journal = {Science}, volume = {357}, year = {2017}, month = {Jul-07-2017}, pages = {18 - 21}, issn = {0036-8075}, doi = {10.1126/science.357.6346.18}, author = {Bohannon, John} } @conference {2017, title = {Data tracking in search of workflows}, booktitle = {the 2017 ACM ConferenceProceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW {\textquoteright}17}, year = {2017}, pages = {2153 - 2165}, publisher = {ACM Press}, organization = {ACM Press}, address = {Portland, Oregon, USANew York, New York, USA}, isbn = {9781450343350}, doi = {10.1145/2998181.2998296}, author = {Holten M{\o}ller, Naja L. and Bj{\o}rn, Pernille and Villumsen, Jonas Christoffer and Hancock, Tine C. Hansen and Aritake, Toshimitsu and Tani, Shigeyuki} } @article {2017, title = {Datification, organizational strategy, and is research: What{\textquoteright}s the score? }, journal = {The Journal of Strategic Information Systems}, volume = {26}, year = {2017}, month = {Jan-09-2017}, pages = {233 - 241}, issn = {09638687}, doi = {10.1016/j.jsis.2017.08.003}, author = {Markus, M. Lynne} } @article {2017, title = {Debating big data: A literature review on realizing value from big data}, journal = {The Journal of Strategic Information Systems}, volume = {26}, year = {2017}, month = {Jan-09-2017}, pages = {191 - 209}, issn = {09638687}, doi = {10.1016/j.jsis.2017.07.003}, author = {G{\"u}nther, Wendy Arianne and Rezazade Mehrizi, Mohammad H. and Huysman, Marleen and Feldberg, Frans} } @article {2017, title = {A deep learning approach for quantifying tumor extent}, journal = {Scientific Reports}, volume = {7}, year = {2017}, month = {Jan-06-2017}, doi = {10.1038/srep46450}, author = {Cruz-Roa, Angel and Gilmore, Hannah and Basavanhally, Ajay and Feldman, Michael and Ganesan, Shridar and Shih, Natalie N.C. and Tomaszewski, John and Gonz{\'a}lez, Fabio A. and Madabhushi, Anant} } @article {2017, title = {Deep learning for healthcare: review, opportunities and challenges}, journal = {Briefings in Bioinformatics}, volume = {19}, year = {2017}, month = {Jun-05-2017}, pages = {1236 - 1246}, issn = {1467-5463}, doi = {10.1093/bib/bbx044}, author = {Miotto, Riccardo and Wang, Fei and Wang, Shuang and Jiang, Xiaoqian and Joel T. Dudley} } @article {2017, title = {DeepMind just published a mind blowing paper: PathNet}, year = {2017}, url = {https://medium.com/mcgill-artificial-intelligence-review/deepmind-just-published-a-mind-blowing-paper-pathnet-f72b1ed38d46}, author = {Th{\'e}o Szymkowiak} } @article {RN30632, title = {Dermatologist-level classification of skin cancer with deep neural networks}, journal = {Nature}, volume = {542}, number = {7639}, year = {2017}, pages = {115{\textendash}118}, type = {Journal Article}, issn = {0028-0836}, author = {Esteva, Andre and Kuprel, Brett and Novoa, Roberto A and Ko, Justin and Swetter, Susan M and Blau, Helen M and Thrun, Sebastian} } @article {2017, title = {Digital technologies and artificial intelligence{\textquoteright}s present and foreseeable impact on lawyering, judging, policing and law enforcement}, journal = {AI \& SOCIETY}, volume = {32}, year = {2017}, month = {Jan-08-2017}, pages = {441 - 464}, issn = {0951-5666}, doi = {10.1007/s00146-015-0596-5}, author = {Nissan, Ephraim} } @article {2017, title = {Do technological innovations affect unemployment? Some empirical evidence from European countries}, journal = {Economies}, volume = {5}, year = {2017}, month = {Jan-12-2017}, pages = {48}, doi = {10.3390/economies5040048}, author = {Matuzeviciute, Kristina and Butkus, Mindaugas and Karaliute, Akvile} } @article {2017, title = {Elon Musk Lays Out Worst-Case Scenario for AI Threat}, year = {2017}, url = {https://www.wsj.com/articles/elon-musk-warns-nations-governors-of-looming-ai-threat-calls-for-regulations-1500154345}, author = {Tim Higgins} } @mastersthesis {2017, title = {An empirical analysis of the impacts of robotization on employment in the Norwegian manufacturing industry}, year = {2017}, type = {master thesis}, abstract = {Rapid advances in robotics, artificial intelligence, and digital technologies have introduced renewed concern that labor will become redundant. The aim of this thesis is to assess whether there exists a relationship between robotization and employment in the time periods 1996-2005 and 2008-2015 in Norwegian manufacturing industries. We exploit data on operational robots from the International Federation of Robotics and individual level data from the Norwegian Labour Force Survey, to assess a potential relationship between increased robotization and the probability of being employed within the manufacturing industries. Utilizing linear probability models, we find no negative relationship between increased robotization and the probability of being employed in Norwegian manufacturing industries. Further, we find indications of a relationship between increased robotization and skill-biases. However, the relationships are of no economic significance. Our findings are consistent with previous research on the impacts of robotization on employment outcomes. Further, we find that robotization is distinct and weakly correlated to import density and capital density.}, url = {https://www.semanticscholar.org/paper/Will-robots-replace-us-\%3A-an-Empirical-analysis-of-Gr\%C3\%B8ndahl-Eriksen/e4e22bf2498e42d6308d81cc7483b5a0b8ba48e7}, author = {Fredrik Gr{\o}ndahl and Gina Hegland Eriksen} } @article {2017, title = {Employment, inequality and ethics in the digital age}, journal = {The IPPR Commission on Economic Justice}, year = {2017}, month = {12/2017}, url = {https://www.ippr.org/publications/managing-automation}, author = {Mathew Lawrence and Carys Roberts and Loren King} } @article {2017, title = {Empowerment As Replacement for the Three Laws of Robotics}, journal = {Frontiers in Robotics and AI}, volume = {4}, year = {2017}, month = {May-06-2019}, doi = {10.3389/frobt.2017.00025}, author = {Salge, Christoph and Polani, Daniel} } @article {2017, title = {Evaluating Assessments in the Age of Big Data and AI}, year = {2017}, url = {https://www.ibm.com/downloads/cas/D5GQD70R}, author = {Nigel Guenole and Sheri Feinzig} } @mastersthesis {2017, title = {Evaluating the effects of industrial robots on the European labour market}, volume = {Bergen, Fall, 2017}, year = {2017}, keywords = {economics of automation}, url = {https://pdfs.semanticscholar.org/4e19/3a0a02315803d799520b094cce36a1888a94.pdf}, author = {Elena Natalie and Cagnol Hveem} } @conference {RN30645, title = {Examining crowd work and gig work through the historical lens of piecework}, booktitle = {Proceedings of the CHI Conference on Human Factors in Computing Systems}, year = {2017}, pages = {4599-4616}, publisher = {ACM}, organization = {ACM}, type = {Conference Proceedings}, isbn = {1450346553}, author = {Alkhatib, Ali and Michael S. Bernstein and Levi, Margaret} } @article {2017, title = {An experimental comparison of Chatbot and Human task partners}, journal = {Computers in Human Behavior}, volume = {75}, year = {2017}, month = {Jan-10-2017}, pages = {461 - 468}, issn = {07475632}, doi = {10.1016/j.chb.2017.05.045}, author = {Fryer, Luke K. and Ainley, Mary and Thompson, Andrew and Gibson, Aaron and Sherlock, Zelinda} } @article {2017, title = {Exploring the tension between transparency and datification effects of open government IS through the lens of Complex Adaptive Systems}, journal = {The Journal of Strategic Information Systems}, volume = {26}, year = {2017}, month = {Jan-09-2017}, pages = {210 - 232}, issn = {09638687}, doi = {10.1016/j.jsis.2017.07.001}, author = {Marjanovic, Olivera and Cecez-Kecmanovic, Dubravka} } @article {2017, title = {The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms}, journal = {Futures}, volume = {90}, year = {2017}, month = {Jan-06-2017}, pages = {46 - 60}, issn = {00163287}, doi = {10.1016/j.futures.2017.03.006}, author = {Makridakis, Spyros} } @book {2017, title = {The Frontiers of MACHINE LEARNING}, year = {2017}, url = {https://www.nap.edu/read/25021/chapter/5}, author = {Lisa Casola} } @article {2017, title = {The future of employment: How susceptible are jobs to computerisation?}, journal = {Technological Forecasting and Social Change}, volume = {114}, year = {2017}, month = {Jan-01-2017}, pages = {254 - 280}, issn = {00401625}, doi = {10.1016/j.techfore.2016.08.019}, author = {Frey, Carl Benedikt and Osborne, Michael A.} } @article {2017, title = {The future of skills employment in 2030}, year = {2017}, keywords = {consulting reports}, url = {https://futureskills.pearson.com/research/assets/pdfs/technical-report.pdf} } @article {2017, title = {A future that works: Automation, employment and productivity}, year = {2017}, url = {https://www.mckinsey.com/mgi/overview}, author = {James Manyika and Michael Chui and Mehdi Miremadi and Jaccques Bughin and Katy George and Paul Willmott and Martin Dewhurst} } @article {2017, title = {Google DeepMind and healthcare in an age of algorithms}, journal = {Health and Technology}, volume = {7}, year = {2017}, month = {Jan-12-2017}, pages = {351 - 367}, issn = {2190-7188}, doi = {10.1007/s12553-017-0179-1}, author = {Powles, Julia and Hodson, Hal} } @article {657, title = {Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science}, journal = {Classical and Quantum Gravity}, volume = {34}, year = {2017}, pages = {064003}, type = {Journal Article}, doi = {10.1088/1361-6382/aa5cea}, author = {Michael Zevin and Scott Coughlin and Sara Bahaadini and Emre Besler and Neda Rohani and Sarah Allen and Miriam Cabero and Kevin Crowston and Aggelos Katsaggelos and Shane Larson and Tae Kyoung Lee and Chris Lintott and Tyson Littenberg and Andrew Lundgren and Carsten Oesterlund and Joshua Smith and Laura Trouille and Vicky Kalogera} } @article {2017, title = {A History of Deep Learning}, year = {2017}, url = {https://www.import.io/post/history-of-deep-learning/}, author = {Andrew Fogg} } @article {2017, title = {House gets serious about driverless cars}, year = {2017}, url = {https://thehill.com/policy/transportation/344141-driverless-car-bill-speeds-through-house}, author = {Melanie Zanona} } @article {2017, title = {How AI is streamlining marketing and sales}, year = {2017}, month = {06/2017}, keywords = {AI use cases}, url = {https://hbr.org/2017/06/how-ai-is-streamlining-marketing-and-sales}, author = {Brad Power} } @article {2017, title = { How automation is changing auditing}, journal = {Journal of Emerging Technologies in Accounting}, volume = {14}, year = {2017}, month = {Jan-03-2017}, pages = {115 - 122}, issn = {1554-1908}, doi = {10.2308/jeta-51730}, author = {Kokina, Julia and Davenport, Thomas H.} } @article {2017, title = {How big data is empowering AI and machine learning at scale}, year = {2017}, month = {05/2017}, keywords = {data and analytics}, url = {https://sloanreview.mit.edu/article/how-big-data-is-empowering-ai-and-machine-learning-at-scale/}, author = {Randy Bean} } @article {2017, title = {How can architects adapt to the coming age of AI?}, year = {2017}, url = {https://archpaper.com/2017/11/architects-adapt-coming-ai/}, author = {Phil Bernstein} } @article {2017, title = {How computers will replace your doctor?}, year = {2017}, url = {https://theweek.com/articles/441528/how-computers-replace-doctor}, author = {Pascal-Emmanuel Gobry} } @article {2017, title = {How fortune 500 firms are adopting online freelancing platforms}, year = {2017}, institution = {University of Oxford}, url = {https://www.oii.ox.ac.uk/publications/platform-sourcing.pdf}, author = {Greetje F. Corporaal and Vili Lehdonvirta} } @article {2017, title = {How is new technology changing job design?}, journal = {IZA World of Labor}, year = {2017}, month = {Jan-01-2017}, doi = {10.15185/izawol.344}, author = {Gibbs, Michael} } @article {2017, title = {How the internet of people will change the future of work}, journal = {Gale Academic Onefile}, volume = {40}, year = {2017}, publisher = {Human Resource Planning Society}, type = {People \& Strategy}, author = {Anna Tavis} } @conference {RN30639, title = {Huddler: Convening stable and familiar crowd teams despite unpredictable availability}, booktitle = {Proceedings of the Conference on Computer supported Cooperative Work and Social Media}, year = {2017}, type = {Conference Proceedings}, author = {Salehi, Niloufar and McCabe, Andrew and Valentine, Melissa and Michael S. Bernstein} } @article {2017, title = {{\textquoteleft}Hypernudge{\textquoteright}: Big Data as a mode of regulation by design}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {118 - 136}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1186713}, author = {Yeung, Karen} } @article {2017, title = {Imagining the thinking machine}, journal = {Convergence: The International Journal of Research into New Media Technologies}, year = {2017}, month = {Aug-06-2018}, pages = {135485651771516}, issn = {1354-8565}, doi = {10.1177/1354856517715164}, author = {Natale, Simone and Ballatore, Andrea} } @article {2017, title = {Impact of robotics, RPA and AI on the insurance industry }, journal = {The Journal of Financial Perspectives: Insurance}, year = {2017}, url = {https://www.ey.com/Publication/vwLUAssets/ey-impact-of-robotics-rpa-and-ai-on-the-insurance-industry-challenges-and-opportunities/\%24File/ey-impact-of-robotics-rpa-and-ai-on-the-insurance-industry-challenges-and-opportunities.pdf}, author = {Chris Lamberton and Damiano Brigo and Dave Hoy} } @book {2017, title = {Information Technology and the U.S. Workforce}, year = {2017}, publisher = {National Academies Press}, organization = {National Academies Press}, address = {Washington, D.C.}, isbn = {978-0-309-45402-5}, doi = {10.17226/24649}, url = {https://www.nap.edu/catalog/24649} } @article {2017, title = {Jobs lost, jobs gained: Workforce transactions in a time of automation}, year = {2017}, keywords = {consulting reports}, url = {https://www.mckinsey.com/~/media/mckinsey/featured\%20insights/future\%20of\%20organizations/what\%20the\%20future\%20of\%20work\%20will\%20mean\%20for\%20jobs\%20skills\%20and\%20wages/mgi-jobs-lost-jobs-gained-report-december-6-2017.ashx}, author = {James Manyika and Susan Lund and Michael Chui and Jonathan Woetzel and Ryan Ko and Saurabh Sanghvi and Parul Batra and Jacques Bughin} } @article {2017, title = {Machine Learning to Detect Anomalies from Application Logs}, year = {2017}, url = {https://www.druva.com/blog/machine-learning-detect-anomalies-application-logs/}, author = {Adwait Bhave} } @article {2017, title = {Meet the people who train the robots to do their own jobs}, year = {2017}, url = {https://nyti.ms/2paCS5X}, author = {Daisuke Wakabayashi} } @article {2017, title = {A new chart conclusively proves that automation is a serious threat}, year = {2017}, month = {11/2017}, type = {Robots \& Machines}, url = {https://futurism.com/new-chart-proves-automation-serious-threat}, author = {Scott Santens} } @article {2017, title = {Of robots, Artificial Intelligence, and work}, journal = {Academy of Management Perspectives}, volume = {31}, year = {2017}, month = {Jan-11-2017}, pages = {253 - 255}, issn = {1558-9080}, doi = {10.5465/amp.2017.0199}, author = {Phan, Phillip and Wright, Michael and Lee, Soo-Hoon} } @article {2017, title = {One hundred years of work design research: Looking back and looking forward}, journal = {Journal of Applied Psychology}, volume = {102}, year = {2017}, month = {Jan-01-2017}, pages = {403 - 420}, issn = {0021-9010}, doi = {10.1037/apl0000106}, author = {Parker, Sharon K. and Morgeson, Frederick P. and Johns, Gary} } @book {2017, title = {Oxford research encyclopedia of psychology }, year = {2017}, publisher = {Oxford University Press}, organization = {Oxford University Press}, doi = {10.1093/acrefore/9780190236557.013.15}, url = {\}, author = {Van den Broeck, Anja and Parker, Sharon K. and Van den Broeck, Anja and Parker, Sharon K.} } @conference {Malone:2017:PPB:2998181.2998343, title = {Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving}, booktitle = {Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing}, year = {2017}, pages = {1661{\textendash}1674}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {climate change, collective intelligence, contest webs, contests, Coordination, incentives, knowledge reuse}, isbn = {978-1-4503-4335-0}, doi = {10.1145/2998181.2998343}, url = {http://doi.acm.org/10.1145/2998181.2998343}, author = {Malone, Thomas W. and Jeffrey V Nickerson and Laubacher, Robert J. and Fisher, Laur Hesse and de Boer, Patrick and Han, Yue and Towne, W. Ben} } @article {2017, title = {Rapid Evidence Review: Impact of artificial intelligence, robotics and automation technologies on work}, year = {2017}, institution = {Chartered Institute of Personnel and Development}, address = {London, United Kingdom}, abstract = {The CIPD and Loughborough University{\textquoteright}s report gathers the evidence and insights on emerging technology at work and explores the ethical implications of how we{\textquoteright}re currently adopting new technology. This report creates a foundation for delving deeper into how we can ensure that people remain at the heart of work. The report, Impact of artificial intelligence, robotics and automation technologies on work, focuses on the academic literature published since 2011 and evaluates the state of contemporary knowledge. It focuses on four key questions: What should the technological and occupations focus of the review be? What are the work-related outcomes and mediators from the utilisation of artificial intelligence (AI), robotics and automation technologies (considering both the impact for workers and organisations)? What are the impacts of AI, robotics and automation technologies on professions and society more generally? What are the ethical issues related to the contemporary utilisation of AI, robotics and automation technologies?}, url = {https://www.cipd.co.uk/knowledge/work/technology/artificial-intelligence-workplace-impact}, author = {Donald Hislop and Crispin Coombs and Stanimira Taneva and Sarah Barnard} } @book {2017, title = {Refining the concept of scientific inference when working with big data}, year = {2017}, publisher = {National Academies Press}, organization = {National Academies Press}, address = {Washington, D.C.}, isbn = {978-0-309-45444-5}, doi = {10.17226/24654}, editor = {Wender, Ben A.} } @article {2017, title = {A review and synthesis of the individual work performance literature}, journal = {Academy of Management Annals}, volume = {11}, year = {2017}, month = {Jan-06-2017}, pages = {825 - 885}, issn = {1941-6520}, doi = {10.5465/annals.2015.0151}, author = {Carpini, Joseph A. and Parker, Sharon K. and Griffin, Mark A.} } @article {2017, title = {Revisiting the risk of automation}, journal = {Economics Letters}, volume = {159}, year = {2017}, month = {Jan-10-2017}, pages = {157 - 160}, issn = {01651765}, doi = {10.1016/j.econlet.2017.07.001}, author = {Arntz, Melanie and Gregory, Terry and Zierahn, Ulrich} } @article {2017, title = {The rise of technological unemployment and its implications on the future macroeconomic landscape}, journal = {Futures}, volume = {87}, year = {2017}, month = {Jan-03-2017}, pages = {1 - 9}, issn = {00163287}, doi = {10.1016/j.futures.2017.01.003}, author = {Kim, Young Joon and Kim, Kyungsoo and Lee, SuKyoung} } @conference {2017, title = {Robots, ai, and the question of {\textquoteright}e-persons{\textquoteright}}, booktitle = {Journal of science communication}, year = {2017}, month = {07/2017}, keywords = {bots, Public perception of science and technology, Public understanding of science and technology, Science and policy-making}, url = {http://eprints.whiterose.ac.uk/124830/}, author = {Michael zollosy} } @article {2017, title = {Scrutinizing an algorithmic technique: the Bayes classifier as interested reading of reality}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {100 - 117}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1181195}, author = {Rieder, Bernhard} } @article {2017, title = {Seeing Like a Tesla: How Can We Anticipate Self-Driving Worlds?}, journal = {Glocalism}, volume = {3}, year = {2017}, abstract = {In the last five years, investment and innovation in self-driving cars has accelerated dramatically. Automotive autonomy, once seen as impossible, is now sold as inevitable. Much of the governance discussion has centred on risk: will the cars be safer than their human-controlled counterparts? As with conventional cars, harder long-term questions relate to the future worlds that self-driving technologies might enable or even demand. The vision of an autonomous vehicle {\textendash} able to navigate the world{\textquoteright}s complexity using only its sensors and processors {\textendash} on offer from companies like Tesla is intentionally misleading. So-called {\textquotedblleft}autonomous{\textquotedblright} vehicles will depend upon webs of social and technical connectivity. For their purported benefits to be realised, infrastructures that were designed around humans will need to be upgraded in order to become machine-readable. It is vital to anticipate the politics of self-driving worlds in order to avoid exacerbating the inequalities that have emerged around conventional cars. Rather than being dazzled by the Tesla view, policymakers should start seeing like a city, from multiple perspectives. Good governance for self-driving cars means democratising experimentation and creating genuine collaboration between companies and local governments. }, keywords = {automotive autonomy, governance, risk, self-driving cars, Tesla}, doi = {10.12893/gjcpi.2017.3.2}, author = {Jack Stilgoe} } @article {2017, title = { A self-driving shuttle in Las Vegas got into an accident on its first day of service}, year = {2017}, month = {11/2017}, keywords = {autonomous vehicles}, url = {https://www.theverge.com/2017/11/8/16626224/las-vegas-self-driving-shuttle-crash-accident-first-day}, author = {Nick Statt} } @article {2017, title = {Service Robotics and Human Labor: A first technology assessment of substitution and cooperation}, journal = {Robotics and Autonomous Systems}, volume = {87}, year = {2017}, month = {Jan-01-2017}, pages = {348 - 354}, issn = {09218890}, doi = {10.1016/j.robot.2016.09.017}, author = {Decker, Michael and Fischer, Martin and Ott, Ingrid} } @article {2017, title = {Situated redesign in creative occupations {\textendash} An ethnography of architects}, journal = {Academy of Management Discoveries}, volume = {3}, year = {2017}, month = {Jan-12-2017}, pages = {404 - 424}, doi = {10.5465/amd.2016.0039}, author = {Rahman, Hatim A. and Barley, Stephen R.} } @article {2017, title = {Situational awareness, workload, and workflow preferences}, journal = {The International Journal of Robotics Research}, volume = {36}, year = {2017}, month = {Sep-06-2017}, pages = {597 - 617}, issn = {0278-3649}, doi = {10.1177/0278364916688255}, author = {Gombolay, Matthew and Bair, Anna and Huang, Cindy and Shah, Julie} } @article {2017, title = {The skeptic{\textquoteright}s guide to artificial intelligence artificial intelligence}, year = {2017}, url = {https://www.ciodive.com/news/the-skeptics-guide-to-artificial-intelligence/441674/}, author = {By Catherine O{\textquoteright}Connor} } @article {2017, title = {The social power of algorithms}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {1 - 13}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1216147}, author = {Beer, David} } @article {2017, title = {Speculations and concerns on robots status in society}, journal = {Journal of science communication}, year = {2017}, keywords = {bots, Participation and science governance, Public engagement with science and technology, Science and policy-making}, url = {https://jcom.sissa.it/sites/default/files/documents/JCOM_1604_2017_C06.pdf}, author = {Erik Stengler and Jimena Escudero Perez} } @conference {2017, title = {SPIE ProceedingsBuilding a framework to manage trust in automation}, booktitle = {SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications IX}, volume = {10194}, year = {2017}, pages = {101941U}, publisher = {SPIE}, organization = {SPIE}, address = {Anaheim, California, United States}, doi = {10.1117/12.2264245}, author = {Metcalfe, J. S. and Amar R. Marathe and Haynes, B. and Paul, V. J. and Gremillion, G. M. and Drnec, K. and Atwater, C. and Estepp, J. R. and Lukos, J. R. and Carter, E. C. and W. D. Nothwang}, editor = {George, Thomas and Dutta, Achyut K. and Islam, M. Saif} } @article {2017, title = {Stewardship in the age of algorithms}, journal = {Peer-reviewed journal on the internet}, year = {2017}, url = {https://firstmonday.org/article/view/8097/6583}, author = {Clifford Lynch} } @article {2017, title = {The strategic opportunities and challenges of algorithmic decision-making}, journal = {The Journal of Strategic Information Systems}, volume = {26}, year = {2017}, month = {Jan-09-2017}, pages = {185 - 190}, issn = {09638687}, doi = {10.1016/j.jsis.2017.08.002}, author = {Galliers, R.D. and Newell, S. and Shanks, G. and Topi, H.} } @article {2017, title = {A systematic framework for multilevel theorizing in information systems research}, journal = {Information Systems Research}, volume = {28}, year = {2017}, month = {Jan-06-2017}, pages = {203 - 224}, issn = {1047-7047}, doi = {10.1287/isre.2017.0690}, author = {Zhang, Meng and Gable, Guy G.} } @article {2017, title = {Thinking critically about and researching algorithms}, journal = {Information, Communication \& Society}, volume = {20}, year = {2017}, month = {Feb-01-2017}, pages = {14 - 29}, keywords = {Algorithmic management}, issn = {1369-118X}, doi = {10.1080/1369118X.2016.1154087}, author = {Kitchin, Rob} } @article {2017, title = {Understanding human-machine networks}, journal = {ACM Computing Surveys}, volume = {50}, year = {2017}, month = {Jan-04-2018}, pages = {1 - 35}, issn = {03600300}, doi = {10.1145/3039868}, author = {Tsvetkova, Milena and Yasseri, Taha and Meyer, Eric T. and Pickering, J. Brian and Engen, Vegard and Walland, Paul and L{\"u}ders, Marika and F{\o}lstad, Asbj{\o}rn and Bravos, George} } @article {2017, title = {What to expect from artificial intelligence}, journal = { MIT SLOAN MANAGEMENT REVIEW }, volume = {58}, year = {2017}, note = {To understand how advances in artificial intelligence are likely to change the workplace {\textemdash} and the work of managers {\textemdash} you need to know where AI delivers the most value.}, url = {http://ilp.mit.edu/media/news_articles/smr/2017/58311.pdf}, author = {Ajay Agrawal and Joshua S. Gans and Avi Goldfarb} } @article {2017, title = {When you{\textquoteright}re not quite sure if your teacher is human}, year = {2017}, month = {05/2017}, url = {https://www.npr.org/sections/ed/2017/05/08/524550295/when-youre-not-quite-sure-if-your-teacher-is-human}, author = {Tasnim Shamma} } @article {2017, title = {Where is technology taking the economy}, year = {2017}, month = {10/2017}, url = {mckinsey.com/business-functions/mckinsey-analytics/our-insights/where-is-technology-taking-the-economy}, author = {W. Brian Arthur} } @article {2017, title = {Will Life Be Worth Living in a World Without Work? Technological Unemployment and the Meaning of Life}, journal = {Science and Engineering Ethics}, volume = {23}, year = {2017}, publisher = {Springer}, chapter = {41-64}, abstract = {Suppose we are about to enter an era of increasing technological unemployment. What implications does this have for society? Two distinct ethical/social issues would seem to arise. The first is one of distributive justice: how will the (presumed) efficiency gains from automated labour be distributed through society? The second is one of personal fulfillment and meaning: if people no longer have to work, what will they do with their lives? In this article, I set aside the first issue and focus on the second. In doing so, I make three arguments. First I argue that there are good reasons to embrace non-work and that these reasons become more compelling in an era of technological unemployment. Second, I argue that the technological advances that make widespread technological unemployment possible could still threaten or undermine human flourishing and meaning, especially if (as is to be expected) they do not remain confined to the economic sphere. And third, I argue that this threat could be contained if we adopt an integrative approach to our relationship with technology. In advancing these arguments, I draw on three distinct literatures: (1) the literature on technological unemployment and workplace automation; (2) the antiwork critique - which I argue gives reasons to embrace technological unemployment; and (3) the philosophical debate about the conditions for meaning in life - which I argue gives reasons for concern.}, keywords = {Antiwork, automation, Egalitarianism, Freedom, Meaning of life, Technological unemployment, Transhumanism}, doi = {10.1007s/11948-016-9770-5}, author = {John Danaher} } @article {2017, title = {Will Life Be Worth Living in a World Without Work? Technological Unemployment and the Meaning of Life}, journal = {Science and Engineering Ethics}, volume = {23}, year = {2017}, month = {Jan-02-2017}, pages = {41 - 64}, issn = {1353-3452}, doi = {10.1007/s11948-016-9770-5}, author = {Danaher, John} } @article {2017, title = {Workforce of the future: The competing forces shaping 2030}, year = {2017}, url = {https://www.pwc.co.uk/economic-services/ukeo/pwc-uk-economic-outlook-full-report-march-2017-v2.pdf}, author = {Carol Stubbings Stubbings and Jon Williams} } @article {2017, title = {Working algorithms: Software automation and the future of work}, journal = {Work and Occupations}, volume = {44}, year = {2017}, month = {Nov-11-2018}, pages = {376 - 423}, issn = {0730-8884}, doi = {10.1177/0730888417726119}, author = {Shestakofsky, Benjamin} } @article {2017, title = {The zombie robot argument lurches on}, year = {2017}, month = {m5/2017}, publisher = {Economic policy institute}, url = {http://epi.org/126750}, author = {Lawrence Mishel and Josh Bivens} } @article {2016, title = {AI can show us the ravages of climate change}, year = {2016}, keywords = {AI use cases}, url = {https://www.technologyreview.com/f/613547/ai-can-show-us-the-ravages-of-climate-change/}, author = {Will Knight} } @article {2016, title = {Algorithms, governance, and governmentality}, journal = {Science, Technology, \& Human Values}, volume = {41}, year = {2016}, month = {Jun-01-2018}, pages = {17 - 49}, issn = {0162-2439}, doi = {10.1177/0162243915587360}, author = {Introna, Lucas D.} } @article {2016, title = {AP Sports is using robot reporters to cover Minor League Baseball }, year = {2016}, url = {https://techcrunch.com/2016/07/03/ap-sports-is-using-robot-reporters-to-cover-minor-league-baseball/}, author = {Lora Kolodny} } @article {2016, title = {AP{\textquoteright}s robot journalists are writing about Minor League Baseball now}, year = {2016}, url = {https://www.theverge.com/2016/7/4/12092768/ap-robot-journalists-automated-insights-minor-league-baseball}, author = {Rich McCormick} } @article {2016, title = {ARTIFICIAL INTELLIGENCE AND LIFE IN 2030}, year = {2016}, url = {https://ai100.stanford.edu/sites/g/files/sbiybj9861/f/ai_100_report_0831fnl.pdf} } @article {2016, title = {Citizen science on a smartphone: Participants{\textquoteright} motivations and learning}, journal = {Public Understanding of Science}, volume = {25}, year = {2016}, month = {Mar-01-2017}, pages = {45 - 60}, issn = {0963-6625}, doi = {10.1177/0963662515602406}, author = {Land-Zandstra, Anne M. and Devilee, Jeroen L. A. and Snik, Frans and Buurmeijer, Franka and van den Broek, Jos M.} } @conference {2016, title = {Degree of Automation in Command and Control Decision Support Systems}, booktitle = {IEEE International Conference on Systems, Man and Cybernetics}, year = {2016}, url = {https://ieeexplore.ieee.org/document/7844402}, author = {Ryan M. Robinson and Michael J. McCount and Amar R. Marathe and W. D. Nothwang and Emily A. Doucette} } @article {2016, title = {Did the Computer Revolution shift the fortunes of U.S. cities? Technology shocks and the geography of new jobs}, journal = {Regional Science and Urban Economics}, volume = {57}, year = {2016}, month = {Jan-03-2016}, pages = {38 - 45}, issn = {01660462}, doi = {10.1016/j.regsciurbeco.2015.11.003}, author = {Berger, Thor and Frey, Carl Benedikt} } @article {2016, title = {Differences in perceptions of communication quality between a Twitterbot and human agent for information seeking and learning}, journal = {Computers in Human Behavior}, volume = {65}, year = {2016}, month = {Jan-12-2016}, pages = {666 - 671}, issn = {07475632}, doi = {10.1016/j.chb.2016.07.003}, author = {Edwards, Chad and Beattie, Austin J. and Edwards, Autumn and Spence, Patric R.} } @article {2016, title = {The digital workforce and the workplace of the future}, journal = {Academy of Management Journal}, volume = {59}, year = {2016}, month = {Jan-06-2016}, pages = {731 - 739}, issn = {0001-4273}, doi = {10.5465/amj.2016.4003}, author = {Colbert, Amy and Yee, Nick and George, Gerard} } @conference {2016, title = {Disrupting developer productivity one bot at a time}, booktitle = {the 2016 24th ACM SIGSOFT International SymposiumProceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2016}, year = {2016}, pages = {928 - 931}, publisher = {ACM Press}, organization = {ACM Press}, address = {Seattle, WA, USANew York, New York, USA}, isbn = {9781450342186}, doi = {10.1145/2950290.2983989}, author = {Storey, Margaret-Anne and Zagalsky, Alexey} } @mastersthesis {2016, title = {Exploring design principles for human-machine symbiosis: Insights from constructing an air transportation logistics artifact}, year = {2016}, keywords = {air transportation logistics, design science research, heuristic theorizing, huma n - machine symbiosis}, url = {https://www.semanticscholar.org/paper/Artificial-Intelligence-and-its-Role-in-Near-Future-Shabbir-Anwer/b93d9995f9ce3b15f4c4855ae62f0bf6f9bc041f}, author = {Daniel A. D{\"o}ppner and Detlef Schoder and Robert Wayne Gregory and Honorata Siejka} } @article {2016, title = {The Future of Artificial Intelligence}, journal = {Big Data}, volume = {4}, year = {2016}, month = {Jan-03-2016}, pages = {5 - 9}, issn = {2167-6461}, doi = {10.1089/big.2016.29004.vda}, author = {Dhar, Vasant} } @booklet {RN30611, title = {The Future of Jobs: Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution}, year = {2016}, publisher = {World Economic Forum}, type = {Report}, author = {The World Economic Forum} } @book {2016, title = {Handbook of Science and Technology ConvergenceConvergence-Divergence Process}, year = {2016}, pages = {79 - 93}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-07051-3}, doi = {10.1007/978-3-319-07052-0_11}, author = {Roco, Mihail C.}, editor = {Bainbridge, William Sims and Roco, Mihail C.} } @article {2016, title = {Hire a UR robot - pay for it by the hour}, year = {2016}, month = {07/2016}, keywords = {bots}, url = {https://blog.universal-robots.com/hire-a-ur-robot-pay-for-it-by-the-hour}, author = {Mahew Bush} } @article {2016, title = {How artificial intelligence will redefine management}, year = {2016}, month = {11/2016}, url = {https://hbr.org/2016/11/how-artificial-intelligence-will-redefine-management}, author = {Vegard Kolbjornsrud and Richard Amico and Robert J. Thomas} } @article {2016, title = {How technology is changing work and organizations}, journal = {Annual Review of Organizational Psychology and Organizational Behavior}, volume = {3}, year = {2016}, month = {Sep-03-2017}, pages = {349 - 375}, issn = {2327-0608}, doi = {10.1146/annurev-orgpsych-041015-062352}, author = {Cascio, Wayne F. and Montealegre, Ramiro} } @article {2016, title = {How the machine {\textquoteleft}thinks{\textquoteright}: Understanding opacity in machine learning algorithms}, journal = {Big Data \& Society}, volume = {3}, year = {2016}, month = {May-01-2016}, pages = {205395171562251}, issn = {2053-9517}, doi = {10.1177/2053951715622512}, author = {Burrell, Jenna} } @article {2016, title = {Human Interaction With Robot Swarms: A Survey}, journal = {Transaction on human-machine systems}, volume = {46}, year = {2016}, month = {02/2016}, pages = {9-26}, publisher = {IEEE}, abstract = {Recent advances in technology are delivering robots of reduced size and cost. A natural outgrowth of these advances are systems comprised of large numbers of robots that collaborate autonomously in diverse applications. Research on effective autonomous control of such systems, commonly called swarms, has increased dramatically in recent years and received attention from many domains, such as bioinspired robotics and control theory. These kinds of distributed systems present novel challenges for the effective integration of human supervisors, operators, and teammates that are only beginning to be addressed. This paper is the first survey of human-swarm interaction (HSI) and identifies the core concepts needed to design a human-swarm system. We first present the basics of swarm robotics. Then, we introduce HSI from the perspective of a human operator by discussing the cognitive complexity of solving tasks with swarm systems. Next, we introduce the interface between swarm and operator and identify challenges and solutions relating to human-swarm communication, state estimation and visualization, and human control of swarm. For the latter, we develop a taxonomy of control methods that enable operators to control swarms effectively. Finally, we synthesize the results to highlight remaining challenges, unanswered questions, and open problems for HSI, as well as how to address them in future works.}, keywords = {Human-robot interaction (HRI), human-swarm interaction (HSI), multi-robot systems, swarm robotics} } @article {2016, title = {Humans, robots and values}, journal = {Technology in Society}, volume = {45}, year = {2016}, month = {Jan-05-2016}, pages = {19 - 28}, issn = {0160791X}, doi = {10.1016/j.techsoc.2016.01.002}, author = {Cockshott, Paul and Renaud, Karen} } @article {2016, title = {If you{\textquoteright}re not collecting productivity data, you{\textquoteright}ll never succeed at work}, year = {2016}, month = {02/2016}, url = {https://hbr.org/2016/02/if-youre-not-collecting-productivity-data-youll-never-succeed-at-work}, author = {Michael Schrage} } @article {2016, title = {Implications of technology for growth, factor shares and employment}, year = {2016}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w22252}, url = {http://www.nber.org/papers/w22252.pdf}, author = {Acemoglu, Daron and Restrepo, Pascual} } @article {2016, title = {IT drinking its own automation champagne}, journal = {Data Informed }, year = {2016}, month = {11/2016}, url = {https://www.linkedin.com/pulse/drinking-its-own-automation-champagne-tom-davenport/}, author = {Thomas H. Davenport} } @article {2016, title = {Job design research and theory: Past, present and future}, journal = {Organizational Behavior and Human Decision Processes}, volume = {136}, year = {2016}, month = {Jan-09-2016}, pages = {20 - 35}, issn = {07495978}, doi = {10.1016/j.obhdp.2016.05.002}, author = {Oldham, Greg R. and Fried, Yitzhak} } @article {2016, title = {Machine learning and decision support in critical care}, journal = {Proceedings of the IEEE}, volume = {104}, year = {2016}, month = {Jan-02-2016}, pages = {444 - 466}, issn = {0018-9219}, doi = {10.1109/JPROC.2015.2501978}, author = {Johnson, Alistair E. W. and Ghassemi, Mohammad M. and Nemati, Shamim and Niehaus, Katherine E. and Clifton, David and Clifford, Gari D.} } @article {2016, title = {Models and people: An alternative view of the emergent properties of computational models}, journal = {Complexity}, volume = {21}, year = {2016}, month = {Jan-07-2016}, pages = {202 - 213}, doi = {10.1002/cplx.21680}, author = {Boschetti, Fabio} } @article {RN30392, title = {The moral imperative of artificial intelligence}, journal = {Communications of the ACM}, volume = {59}, year = {2016}, pages = {5}, type = {Journal Article}, issn = {0001-0782}, doi = {10.1145/2903530}, author = {Vardi, Moshe Y.} } @article {2016, title = {Predicting the Future {\textemdash} Big Data, Machine Learning, and Clinical Medicine}, journal = {New England Journal of Medicine}, volume = {375}, year = {2016}, month = {May-09-2018}, pages = {1216 - 1219}, issn = {0028-4793}, doi = {10.1056/NEJMp1606181}, author = {Obermeyer, Ziad and Emanuel, Ezekiel J.} } @article {2016, title = {Preparing for the future of Artificial intelligence}, year = {2016}, month = {10/2016}, institution = {Executive Office of the President National Science and Technology Council Committee on Technology}, url = {https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.pdf} } @article {2016, title = {Real-life examples of artificial intelligence}, year = {2016}, month = {07/2016}, url = {https://letzgro.net/blog/real-life-examples-of-artificial-intelligence/} } @article {2016, title = {Regional Diversity in Autonomy and Work: A Case Study from Uber and Lyft Drivers}, year = {2016}, chapter = {Data And Society}, url = {https://datasociety.net/pubs/ia/Rosenblat-Hwang_Regional_Diversity-10-13.pdf}, author = {Alex Rosenblat and Tim Hwang} } @article {2016, title = {The return of the chatbots}, journal = {Natural Language Engineering}, volume = {22}, year = {2016}, month = {Jan-09-2016}, pages = {811 - 817}, issn = {1351-3249}, doi = {10.1017/S1351324916000243}, url = {https://www.cambridge.org/core/product/identifier/S1351324916000243/type/journal_articlehttps://www.cambridge.org/core/services/aop-cambridge-core/content/view/S1351324916000243}, author = {Robert Dale} } @article {2016, title = {The rise of social bots}, journal = {Communications of the ACM}, volume = {59}, year = {2016}, month = {Dec-06-2017}, pages = {96 - 104}, issn = {00010782}, doi = {10.1145/2818717}, author = {Ferrara, Emilio and Varol, Onur and Davis, Clayton and Menczer, Filippo and Flammini, Alessandro} } @article {2016, title = {Robots and humans {\textendash} complements or substitutes?}, journal = {Journal of Macroeconomics}, volume = {49}, year = {2016}, month = {Jan-09-2016}, pages = {280 - 291}, issn = {01640704}, doi = {10.1016/j.jmacro.2016.08.003}, author = {DeCanio, Stephen J.} } @article {2016, title = {Robots working with humans or humans working with robots?}, journal = {Societies}, volume = {6}, year = {2016}, month = {Jan-09-2016}, pages = {23}, doi = {10.3390/soc6030023}, author = {Moniz, Ant{\'o}nio and Krings, Bettina-Johanna} } @conference {2016, title = {SPIE ProceedingsAn efficient fusion approach for combining human and machine decisions}, booktitle = {SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications VIII}, volume = {9836}, year = {2016}, pages = {983621}, publisher = {SPIE}, organization = {SPIE}, address = {Baltimore, Maryland, United States}, doi = {10.1117/12.2220788}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2220788}, author = {Lee, Hyungtae and Kwon, Heesung and Ryan M. Robinson and W. D. Nothwang and Amar R. Marathe}, editor = {George, Thomas and Dutta, Achyut K. and Islam, M. Saif} } @article {2016, title = {Structural transformation in the OECD}, volume = {193}, year = {2016}, doi = {10.1787/5jlr068802f7-en}, author = {Thor Berger and Carl Benedikt Frey} } @article {2016, title = {Will computers put us out of work? }, journal = {Computer}, volume = {49}, year = {2016}, month = {Jan-05-2016}, pages = {82 - 85}, issn = {0018-9162}, doi = {10.1109/MC.2016.126}, author = {King, John Leslie and Grudin, Jonathan} } @article {2016, title = {A world where everyone has a robot: Why 2040 could blow your mind}, journal = {International weekly journal of science}, year = {2016}, url = {https://www.nature.com/news/a-world-where-everyone-has-a-robot-why-2040-could-blow-your-mind-1.19431}, author = {Declan Butler} } @article {2015, title = {Artificial Intelligence and its Role in Near Future}, volume = {JOURNAL OF L A T E X CLASS FILES, VOL. 14, NO. 8, AUGUST 2015}, year = {2015}, url = {https://www.semanticscholar.org/paper/Artificial-Intelligence-and-its-Role-in-Near-Future-Shabbir-Anwer/b93d9995f9ce3b15f4c4855ae62f0bf6f9bc041f}, author = {Jahanzaib Shabbir and Tarique Anwer} } @article {2015, title = {Artificial intelligence for the real world: Don{\textquoteright}t start with moon shots}, year = {2015}, keywords = {consulting reports}, url = {https://hbr.org/2018/01/artificial-intelligence-for-the-real-world}, author = {Thomas H. Davenport and Rajeev Ronanki} } @book {2015, title = {The big move toward big data in employment}, series = {Employment\& Labor Law Solutions Worldwide}, year = {2015}, publisher = {Littler Mendelson, P.C.}, organization = {Littler Mendelson, P.C.}, url = {https://www.littler.com/files/wp_big_data_8-04-15.pdf}, author = {Aaron Crews} } @article {2015, title = {Is a Cambrian Explosion Coming for Robotics?}, journal = {Journal of Economic Perspectives}, volume = {29}, year = {2015}, month = {Jan-08-2015}, pages = {51 - 60}, issn = {0895-3309}, doi = {10.1257/jep.29.3.51}, url = {http://pubs.aeaweb.org/doi/10.1257/jep.29.3.51http://pubs.aeaweb.org/doi/pdf/10.1257/jep.29.3.51}, author = {Pratt, Gill A.} } @article {2015, title = {A comparison between human{\textendash}human online conversations and human{\textendash}chatbot conversations}, journal = {Computers in Human Behavior}, volume = {49}, year = {2015}, month = {Jan-08-2015}, pages = {245 - 250}, issn = {07475632}, doi = {10.1016/j.chb.2015.02.026}, author = {Hill, Jennifer and Randolph Ford, W. and Farreras, Ingrid G.} } @article {2015, title = {Decision-making authority, team efficiency and human worker satisfaction in mixed human{\textendash}robot teams}, journal = {Autonomous Robots}, volume = {39}, year = {2015}, month = {Jan-10-2015}, pages = {293 - 312}, issn = {0929-5593}, doi = {10.1007/s10514-015-9457-9}, author = {Gombolay, Matthew C. and Gutierrez, Reymundo A. and Clarke, Shanelle G. and Sturla, Giancarlo F. and Shah, Julie A.} } @book {2015, title = {Deep Learning Tutorial}, series = {Release 0.1}, year = {2015}, url = {http://deeplearning.net/tutorial/deeplearning.pdf}, author = {LISA lab, University of Montreal} } @article {2015, title = {An executive{\textquoteright}s guide to machine learning}, journal = {McKinsey Quarterly}, year = {2015}, type = {Technology, Media \& Telecommunications}, url = {https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/an-executives-guide-to-machine-learning}, author = {Dorian Pyle and Cristina San Jose} } @article {2015, title = {Facebook launches M, its bold answer to Siri and Cortana}, year = {2015}, url = {https://www.wired.com/2015/08/facebook-launches-m-new-kind-virtual-assistant/}, author = {Jessi Hempel} } @article {RN30610, title = {Four fundamentals of workplace automation}, journal = {McKinsey Quarterly}, year = {2015}, month = {November}, pages = {1{\textendash}9}, type = {Magazine Article}, author = {Chui, Michael and Manyika, James and Miremadi, Mehdi} } @booklet {RN30629, title = {The growing importance of social skills in the labor market}, year = {2015}, publisher = {National Bureau of Economic Research}, type = {Report}, author = {Deming, David J} } @article {2015, title = {The history of technological anxiety and the future of economic growth: Is this time different? }, journal = {Journal of Economic Perspectives}, volume = {29}, year = {2015}, month = {Jan-08-2015}, pages = {31 - 50}, issn = {0895-3309}, doi = {10.1257/jep.29.3.31}, author = {Mokyr, Joel and Vickers, Chris and Ziebarth, Nicolas L.} } @article {2015, title = {How new digital technologies are making smart people and businesses smarter by automating rote work}, year = {2015}, month = {01/2015}, institution = {Keep Challenging}, url = {https://www.cognizant.com/whitepapers/the-robot-and-I-how-new-digital-technologies-are-making-smart-people-and-businesses-smarter-codex1193.pdf} } @article {RN30644, title = {Human-level control through deep reinforcement learning}, journal = {Nature}, volume = {518}, number = {7540}, year = {2015}, pages = {529-533}, type = {Journal Article}, issn = {0028-0836}, author = {Mnih, Volodymyr and Kavukcuoglu, Koray and Silver, David and Rusu, Andrei A and Veness, Joel and Bellemare, Marc G and Graves, Alex and Riedmiller, Martin and Fidjeland, Andreas K and Ostrovski, Georg} } @article {2015, title = {Hybrid human{\textendash}machine information systems: Challenges and opportunities}, journal = {Computer Networks}, volume = {90}, year = {2015}, month = {Jan-10-2015}, pages = {5 - 13}, issn = {13891286}, doi = {10.1016/j.comnet.2015.05.018}, author = {Demartini, Gianluca} } @conference {2015, title = {Intelligible Models for HealthCare}, booktitle = {the 21th ACM SIGKDD International ConferenceProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD {\textquoteright}15}, year = {2015}, pages = {1721 - 1730}, publisher = {ACM Press}, organization = {ACM Press}, address = {Sydney, NSW, AustraliaNew York, New York, USA}, isbn = {9781450336642}, doi = {10.1145/278325810.1145/2783258.2788613}, author = {Caruana, Rich and Lou, Yin and Gehrke, Johannes and Koch, Paul and Sturm, Marc and Elhadad, Noemie} } @book {2015, title = {Mining programming activity to promote help}, year = {2015}, pages = {23 - 42}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-20498-7}, doi = {10.1007/978-3-319-20499-4_2}, author = {Carter, Jason and Dewan, Prasun}, editor = {Boulus-R{\o}dje, Nina and Ellingsen, Gunnar and Bratteteig, Tone and Aanestad, Margunn and Bj{\o}rn, Pernille} } @article {2015, title = {Norms, institutions and robots}, journal = {Journal of latex class files}, volume = {14}, year = {2015}, month = {08/2015}, url = {https://arxiv.org/abs/1807.11456}, author = {Stevan Tomic and Federico Pecora and Alessandro Saffotti} } @article {2015, title = {Research Priorities for Robust and Beneficial Artificial Intelligence}, journal = {Association for the Advancement of Artificial Intelligence}, volume = {4}, year = {2015}, pages = {105-114}, abstract = {

Artificial intelligence (AI) research has explored a variety of problems and approaches since its inception, but for the last 20 years or so has been focused on the problems surrounding the construction of intelligent agents - systems that perceive and act in some environment. In this context, the criterion for intelligence is related to statistical and economic notions of rationality - colloquially, the ability to make good decisions, plans, or inferences. The adoption of probabilistic representations and statistical learning methods can led to a large degree of integration and crossfertilization between AI, machine learning, control theory, neuroscience, and other fields. The establishment of shared theoretical frameworks, combined with the availability of data and processing power, has yielded remarkable successes in various component tasks such as speech recognition, image classification, autonomous vehicles, machine translation, legged locomotion, and question-answering systems.

}, url = {https://futureoflife.org/data/documents/research_priorities.pdf}, author = {Stuart Russell and Daniel Dewey and Max Tegmark} } @conference {2015, title = {Science bot: a model for the future computation}, booktitle = {the 24th International ConferenceProceedings of the 24th International Conference on World Wide Web - WWW {\textquoteright}15 Companion}, year = {2015}, pages = {1061 - 1062}, publisher = {ACM Press}, organization = {ACM Press}, address = {Florence, ItalyNew York, New York, USA}, isbn = {9781450334730}, doi = {10.1145/2740908.2742014}, author = {Kuhn, Tobias} } @article {2015, title = {Toward a computational hermeneutics}, journal = {Big Data \& Society}, volume = {2}, year = {2015}, month = {Mar-12-2017}, pages = {205395171561380}, issn = {2053-9517}, doi = {10.1177/2053951715613809}, author = {Mohr, John W and Wagner-Pacifici, Robin and Breiger, Ronald L} } @article {2015, title = { Users{\textquoteright} reactions to actions of automated programs in Wikipedia}, journal = {Computers in Human Behavior}, volume = {50}, year = {2015}, month = {Jan-09-2015}, pages = {66 - 75}, issn = {07475632}, doi = {10.1016/j.chb.2015.03.078}, author = {Cl{\'e}ment, Maxime and Guitton, Matthieu J.} } @article {2015, title = {Who owns the robots rules the world}, journal = {IZA World of Labor}, year = {2015}, month = {Jan-01-2015}, doi = {10.15185/izawol.5}, author = {Freeman, Richard} } @article {2015, title = {Why Are There Still So Many Jobs? The History and Future of Workplace Automation}, journal = {Journal of Economic Perspectives}, volume = {29}, year = {2015}, pages = {3-30}, issn = {0895-3309}, doi = {10.1257/jep.29.3.3}, url = {http://pubs.aeaweb.org/doi/10.1257/jep.29.3.3}, author = {Autor, David H.} } @article {RN30621, title = {Will humans go the way of horses}, journal = {Foreign Affairs}, volume = {94}, year = {2015}, pages = {8}, type = {Journal Article}, author = {Erik Brynjolfsson and McAfee, Andrew} } @article {2014, title = {Beyond motivation: Job and work design for development, health, ambidexterity, and more}, journal = {Annual Review of Psychology}, volume = {65}, year = {2014}, month = {Mar-01-2014}, pages = {661 - 691}, issn = {0066-4308}, doi = {10.1146/annurev-psych-010213-115208}, author = {Parker, Sharon K.} } @article {2014, title = {Four scenarios exploring the future of youth employment}, year = {2014}, month = {12/2014}, url = {https://assets.rockefellerfoundation.org/app/uploads/20141201215005/FutureofYouthEmployment.pdf}, author = {Caroline Budhan and Abigail Carlton and Evan O{\textquoteright}Donnel} } @article {2014, title = {The global decline of the labor share}, journal = {The Quarterly Journal of Economics}, volume = {129}, year = {2014}, month = {Jan-02-2014}, pages = {61 - 103}, issn = {0033-5533}, doi = {10.1093/qje/qjt032}, author = {Karabarbounis, L. and Neiman, B.} } @article {2014, title = {Human-agent collectives}, journal = {Communications of the ACM}, volume = {57}, year = {2014}, month = {Feb-11-2016}, pages = {80 - 88}, issn = {00010782}, doi = {10.1145/269296510.1145/2629559}, author = {Jennings, N. R. and Moreau, L. and Nicholson, D. and Ramchurn, S. and Roberts, S. and Rodden, T. and Rogers, A.} } @article {2014, title = {The impact of robotics on employment and motivation of employees in the service sector, with special reference to health care}, journal = {Safety and Health at Work}, volume = {5}, year = {2014}, month = {Jan-12-2014}, pages = {198 - 202}, issn = {20937911}, doi = {10.1016/j.shaw.2014.07.003}, author = {Qureshi, Mohammed Owais and Syed, Rumaiya Sajjad} } @conference {2014, title = {Leveraging the cross-cultural capacities of artificial agents as leaders of human virtual teams}, booktitle = {European 10th Conference on Management Leadership and Governance}, year = {2014}, url = {https://www.researchgate.net/publication/268982256_Leveraging_the_Cross-Cultural_Capacities_of_Artificial_Agents_as_Leaders_of_Human_Virtual_Teams}, author = {Matthew Gladden} } @article {2014, title = {Occupational identity, technological change, and the librarian/internet-search relationship}, journal = {Academy of Management Journal}, volume = {57}, year = {2014}, month = {Jan-06-2014}, pages = {892 - 928}, issn = {0001-4273}, doi = {10.5465/amj.2012.0201}, author = {Nelson, Andrew J. and Irwin, Jennifer} } @article {2014, title = {Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter}, journal = {Computers in Human Behavior}, volume = {33}, year = {2014}, month = {Jan-04-2014}, pages = {372 - 376}, issn = {07475632}, doi = {10.1016/j.chb.2013.08.013}, author = {Edwards, Chad and Edwards, Autumn and Spence, Patric R. and Shelton, Ashleigh K.} } @article {2014, title = {Toward a Framework for Levels of Robot Autonomy in Human-Robot Interaction}, journal = {Journal of Human-Robot Interaction}, volume = {3}, year = {2014}, month = {Jan-06-2014}, pages = {74}, doi = {10.5898/JHRI.3.2.Beer}, url = {http://dl.acm.org/citation.cfm?id=3109833http://dl.acm.org/ft_gateway.cfm?id=3109833\&ftid=1883786\&dwn=1}, author = {Beer, Jenay M and Fisk, Arthur D and Rogers, Wendy A} } @article {2014, title = {A transdisciplinary perspective on hedonomic sustainability design}, year = {2014}, keywords = {environmental efficacy, environmental sustainability, hedonomics, sustainable design, transdisciplinary research}, doi = {10.1177\%2F1064804613516762}, url = {https://journals.sagepub.com/doi/abs/10.1177/1064804613516762?journalCode=erga}, author = {Stephen M. Fiore and Elizabeth Philips and Brittany C. Sellers} } @article {918, title = {Beyond Big Data}, year = {2013}, url = {http://people.ischool.berkeley.edu/~hal/Papers/2013/BeyondBigDataPaperFINAL.pdf}, author = {Hal R. Varian} } @article {2013, title = {Beyond convergence of Nano-Bio-Info-Cognitive technologies}, year = {2013}, month = {07/2013}, url = {http://www.wtec.org/NBIC2/Docs/FinalReport/Pdf-secured/NBIC2-FinalReport-WEB.pdf}, author = {Mihail C. Roco and William S. Bainbridge and Bruce Tonn and George Whitesides} } @article {2013, title = {A Comprehensive Survey of Data Mining-based Fraud Detection Research}, year = {2013}, keywords = {adversarial detection, automated fraud detection, Data mining applications}, url = {https://arxiv.org/ftp/arxiv/papers/1009/1009.6119.pdf}, author = {Clifton Phua and Vincent Lee and Kate Smith and Ross Gayler} } @article {2013, title = {The convergence of engineering and the life sciences}, journal = {National Academy of Engineering}, volume = {43}, year = {2013}, month = {10/2013}, url = {https://www.nae.edu/88364/The-Convergence-of-Engineering-and-the-Life-Sciences}, author = {Pjilip A. Sharp and Robert Langer} } @article {2013, title = {Ethical algorithms}, year = {2013}, url = {https://www.sharrockandanderson.co.uk/wp-content/uploads/2017/04/Ethical-Algorithms.pdf}, author = {R.J. Anderson and W.W. Sharrock} } @conference {kittur2013future, title = {The future of crowd work}, booktitle = {Proceedings of the 2013 conference on Computer supported cooperative work}, year = {2013}, pages = {1301{\textendash}1318}, publisher = {ACM}, organization = {ACM}, author = {Kittur, Aniket and Jeffrey V Nickerson and Michael S. Bernstein and Gerber, Elizabeth and Shaw, Aaron and Zimmerman, John and Lease, Matt and Horton, John} } @article {2013, title = {The great reversal in the demand for skill and cognitive tasks}, year = {2013}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w18901}, author = {Beaudry, Paul and Green, David and Sand, Benjamin} } @book {2013, title = {Integration and implementation sciences for researching complex real-world problems}, year = {2013}, note = {Includes bibliographical references}, isbn = {9781922144270}, url = {https://www.jstor.org/stable/j.ctt2jbkj5}, author = {Bammer and Gabriele} } @article {2013, title = {The new world of discovery, invention, and innovation: convergence of knowledge, technology, and society}, journal = {Journal of Nanoparticle Research}, volume = {15}, year = {2013}, month = {Jan-09-2013}, issn = {1388-0764}, doi = {10.1007/s11051-013-1946-1}, url = {http://link.springer.com/10.1007/s11051-013-1946-1http://link.springer.com/content/pdf/10.1007/s11051-013-1946-1http://link.springer.com/content/pdf/10.1007/s11051-013-1946-1.pdfhttp://link.springer.com/article/10.1007/s11051-013-1946-1/fulltext.html}, author = {Roco, Mihail C. and Bainbridge, William S.} } @article {2013, title = {Quantifying the interdisciplinarity of scientific journals and fields}, journal = {Journal of Informetrics}, volume = {7}, year = {2013}, month = {Jan-04-2013}, pages = {469 - 477}, issn = {17511577}, doi = {10.1016/j.joi.2013.01.007}, url = {https://linkinghub.elsevier.com/retrieve/pii/S1751157713000096https://api.elsevier.com/content/article/PII:S1751157713000096?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S1751157713000096?httpAccept=text/plain}, author = {Silva, F.N. and Rodrigues, F.A. and Oliveira, O.N. and da F. Costa, L.} } @article {2013, title = {The rise and fall of interdisciplinary research: The case of open source innovation}, journal = {Research Policy}, volume = {42}, year = {2013}, month = {Jan-06-2013}, pages = {1138 - 1151}, issn = {00487333}, doi = {10.1016/j.respol.2013.01.010}, author = {Raasch, Christina and Lee, Viktor and Spaeth, Sebastian and Herstatt, Cornelius} } @conference {2013, title = {Survey of metrics for human-robot interaction}, booktitle = {IEEE International Conference}, year = {2013}, keywords = {bots}, url = {https://ieeexplore.ieee.org/document/6483569}, author = {Robin R. Murphy and Debra Schreckenghost} } @article {2012, title = {A few useful things to know about machine learning}, journal = {Communications of the ACM}, volume = {55}, year = {2012}, month = {Jan-10-2012}, pages = {78}, issn = {00010782}, doi = {:10.1145/2347736.2347755}, author = {Domingos, Pedro} } @article {2011, title = {Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature}, journal = {Journal of Informetrics}, volume = {5}, year = {2011}, month = {Jan-01-2011}, pages = {14 - 26}, issn = {17511577}, doi = {10.1016/j.joi.2010.06.004}, author = {Wagner, Caroline S. and Roessner, J. David and Bobb, Kamau and Klein, Julie Thompson and Boyack, Kevin W. and Keyton, Joann and Rafols, Ismael and B{\"o}rner, Katy} } @conference {2011, title = {No sense of distance}, booktitle = {the 2011 iConferenceProceedings of the 2011 iConference on - iConference {\textquoteright}11}, year = {2011}, pages = {159 - 165}, publisher = {ACM Press}, organization = {ACM Press}, address = {Seattle, WashingtonNew York, New York, USA}, isbn = {9781450301213}, doi = {10.1145/1940761.1940783}, author = {Aragon, Cecilia R. and Poon, Sarah} } @article {2011, title = {Is there an ethics of algorithms?}, journal = {Ethics and Information Technology}, volume = {13}, year = {2011}, month = {Jan-09-2011}, pages = {251 - 260}, issn = {1388-1957}, doi = {10.1007/s10676-010-9233-7}, author = {Kraemer, Felicitas and van Overveld, Kees and Peterson, Martin} } @article {2010, title = {Not what it was and not what it will be: The future of job design research}, journal = {Journal of Organizational Behavior}, volume = {31}, year = {2010}, month = {Jan-02-2010}, pages = {463 - 479}, issn = {08943796}, doi = {10.1002/job.v31:2/310.1002/job.678}, author = {Oldham, Greg R. and Hackman, J. Richard}, editor = {Grant, Adam and Fried, Yitzhak and Parker, Sharon and Frese, Michael} } @article {2010, title = {Prediction modeling using EHR data: Challenges, strategies, and a comparison of machine learning approaches}, journal = {Medical Care}, volume = {48}, year = {2010}, publisher = {Lippincott Williams \& Wilkins}, type = {Emerging Methods and Policy Applications}, url = {https://www.jstor.org/stable/20720782}, author = {Jionglin Wu and Jason Ray and Walter F. Stewart} } @article {2010, title = {Understanding the role of occupational and organizational context}, journal = {Journal of Organizational Behavior}, volume = {31}, year = {2010}, month = {Jan-02-2010}, pages = {351 - 360}, issn = {08943796}, doi = {10.1002/job.642}, author = {Morgeson, Frederick P. and Dierdorff, Erich C. and Hmurovic, Jillian L.}, editor = {Grant, Adam and Fried, Yitzhak and Parker, Sharon and Frese, Michael} } @conference {2010, title = {Using machine learning for network intrusion detection}, year = {2010}, note = {Proceedings of the IEEE Symposium on Security and Privacy 2010, Oakland, California, pp. 305-316}, url = {http://www.icsi.berkeley.edu/pubs/networking/outsidethe10.pdf}, author = {R. Sommer and V. Paxson} } @conference {2009, title = {The changing face of digital science}, booktitle = {the 27th international conference extended abstractsProceedings of the 27th international conference extended abstracts on Human factors in computing systems - CHI EA {\textquoteright}09}, year = {2009}, pages = {4819}, publisher = {ACM Press}, organization = {ACM Press}, address = {Boston, MA, USANew York, New York, USA}, isbn = {9781605582474}, doi = {10.1145/1520340.1520749}, author = {Aragon, Cecilia R. and Poon, Sarah and Silva, Claudio T.} } @article {2009, title = {Deploying embodied AI into virtual worlds}, journal = {Knowledge-Based Systems}, volume = {22}, year = {2009}, month = {Jan-10-2009}, pages = {540 - 544}, issn = {09507051}, doi = {10.1016/j.knosys.2008.10.001}, author = {Burden, David J.H.} } @article {2009, title = {Redesigning work design theories: The rise of relational and proactive perspectives}, journal = {The Academy of Management Annals}, volume = {3}, year = {2009}, month = {Jan-01-2009}, pages = {317 - 375}, issn = {1941-6520}, doi = {10.1080/19416520903047327}, author = {Grant, Adam M. and Parker, Sharon K.} } @article {2009, title = {Under diagnosis and referral bias of autism in ethnic minorities}, journal = {Journal of Autism and Developmental Disorders}, volume = {39}, year = {2009}, month = {Jan-01-2009}, pages = {142 - 148}, issn = {0162-3257}, doi = {10.1007/s10803-008-0611-5}, author = {Begeer, Sander and Bouk, Saloua El and Boussaid, Wafaa and Terwogt, Mark Meerum and Koot, Hans M.} } @conference {2008, title = {Context-linked virtual assistants for distributed teams}, booktitle = {the ACM 2008 conferenceProceedings of the ACM 2008 conference on Computer supported cooperative work - CSCW {\textquoteright}08}, year = {2008}, pages = {361}, publisher = {ACM Press}, organization = {ACM Press}, address = {San Diego, CA, USANew York, New York, USA}, isbn = {9781605580074}, doi = {10.1145/1460563.1460623}, author = {Poon, Sarah S. and Thomas, Rollin C. and Aragon, Cecilia R. and Lee, Brian} } @conference {RN30259, title = {Context-linked virtual assistants for distributed teams: an astrophysics case study}, booktitle = {Proceedings of the ACM Conference on Computer Supported Cooperative Work}, year = {2008}, pages = {361{\textendash}370}, type = {Conference Proceedings}, isbn = {1605580074}, author = {Poon, Sarah S and Thomas, Rollin C and Cecilia Aragon and Lee, Brian} } @book {2008, title = {Handbook of transdisciplinary research}, year = {2008}, pages = {427 - 432}, publisher = {Springer Netherlands}, organization = {Springer Netherlands}, address = {Dordrecht}, isbn = {978-1-4020-6698-6}, doi = {10.1007/978-1-4020-6699-3_28}, editor = {Hadorn, Gertrude Hirsch and Hoffmann-Riem, Holger and Biber-Klemm, Susette and Grossenbacher-Mansuy, Walter and Joye, Dominique and Pohl, Christian} } @booklet {2008, title = {How life imitates chess: Making the right moves-from the board to the boardroom}, year = {2008}, publisher = {Random House}, address = {New York, NY}, isbn = {0363-0277}, author = {Kasparov, Garry} } @article {2008, title = {Job and team design: Toward a more integrative conceptualization of work design}, journal = {Research in Personnel and Human Resources ManagementResearch in Personnel and Human Resources Management}, volume = {27}, year = {2008}, pages = {39{\textendash}91}, author = {Frederick P. Morgeson and Stephen E. Humphrey} } @article {2007, title = {Automation-induced complacency for monitoring highly reliable systems: the role of task complexity, system experience, and operator trust}, journal = {Theoretical Issues in Ergonomics Science}, volume = {8}, year = {2007}, month = {Jan-07-2007}, pages = {321 - 348}, issn = {1463-922X}, doi = {10.1080/14639220500535301}, author = {Bailey, N. R. and Scerbo, M. W.} } @article {2007, title = {Towards a theory for multiparty proactive communication in agent teams}, journal = {International Journal of Cooperative Information Systems}, volume = {16}, year = {2007}, month = {Jan-06-2009}, pages = {271 - 298}, issn = {0218-8430}, doi = {10.1142/S0218843007001640}, author = {Kaivan Kamali and Xiaocong Fan and John Yen, JOHN} } @book {2006, title = { Analysis of the automation and the human worker, connection between the levels of automation and different automation concept}, series = {Factory in a box}, year = {2006}, url = {https://www.diva-portal.org/smash/get/diva2:228706/FULLTEXT01.pdf}, author = {Grigor Mishev} } @article {2006, title = {Literature review of teamwork models}, number = {CMU-RI-TR-06-50}, year = {2006}, institution = {Robotics Institute, Carnegie Mellon University}, url = {https://www.researchgate.net/publication/246704657_Literature_Review_of_Teamwork_Models}, author = {Katia Sycara and Gita Sukthankar} } @article {2006, title = {The story of socio-technical design: Reflections on its successes, failures and potential}, journal = {Information Systems JournalInformation Systems Journal}, volume = {16}, number = {4}, year = {2006}, pages = {317-342}, isbn = {1365-2575}, author = {Mumford, Enid} } @article {2006, title = {Technical change, job tasks, and rising educational demands: looking outside the wage structure}, journal = {Journal of Labor Economics}, volume = {24}, year = {2006}, month = {Jan-04-2006}, pages = {235 - 270}, issn = {0734-306X}, doi = {10.1086/499972}, author = {Spitz-Oener, Alexandra} } @article {2006, title = {The Work Design Questionnaire (WDQ): Developing and validating a comprehensive measure for assessing job design and the nature of work.}, journal = {Journal of Applied Psychology}, volume = {91}, year = {2006}, month = {Jan-01-2006}, pages = {1321 - 1339}, issn = {0021-9010}, doi = {10.1037/0021-9010.91.6.1321}, author = {Morgeson, Frederick P. and Humphrey, Stephen E.} } @conference {2005, title = {A dialogue agent with adaptive and proactive capabilities}, booktitle = {IEEE/WIC/ACM International Conference on Intelligent Agent TechnologyIEEE/WIC/ACM International Conference on Intelligent Agent Technology}, year = {2005}, month = {09/2005}, pages = {293 - 296}, publisher = {IEEE}, organization = {IEEE}, address = {Compiegne Codex, France}, doi = {10.1109/IAT.2005.8}, author = {Baudoin, F. and Bretier, P. and Corruble, V.} } @article {2004, title = {Handoff strategies in settings with high consequences for failure: lessons for health care operations}, journal = {International Journal for Quality in Health Care}, volume = {16}, year = {2004}, month = {Jan-04-2004}, pages = {125 - 132}, issn = {1353-4505}, doi = {10.1093/intqhc/mzh026}, author = {Patterson, E. S.} } @book {2003, title = {Handbook of psychology work design}, year = {2003}, publisher = {John Wiley \& Sons, Inc.}, organization = {John Wiley \& Sons, Inc.}, address = {Hoboken, NJ, USA}, doi = {10.1002/0471264385.wei1217}, author = {Morgeson, Frederick P. and Campion, Michael A.}, editor = {Weiner, Irving B.} } @article {2003, title = {A Preliminary Analysis of Occupational Task Statements from the O*NET Data Collection Program}, year = {2003}, institution = {National Center for O*NET Development}, isbn = {FR-02-52}, author = {Van Iddekinge, Chad and Suzanne Tsacoumis and Jamie Donsbach} } @article {RN30479, title = {The skill content of recent technological change: An empirical exploration}, journal = {Quarterly Journal of Economics}, volume = {118}, number = {4}, year = {2003}, pages = {1279{\textendash}1333}, type = {Journal Article}, issn = {0033-5533}, doi = {10.1162/003355303322552801}, url = {http://apps.isiknowledge.com/InboundService.do?Func=Frame\&product=WOS\&action=retrieve\&SrcApp=EndNote\&Init=Yes\&SrcAuth=ResearchSoft\&mode=FullRecord\&UT=WOS:000186624900004}, author = {Autor, D. H. and Levy, F. and Murnane, R. J.} } @inbook {2003, title = {Work design}, booktitle = {Handbook of Psychology: Industrial and Organizational Psychology}, volume = {12}, year = {2003}, pages = {423{\textendash}452}, publisher = {Wiley}, organization = {Wiley}, address = {Hoboken, NY}, author = {Frederick P. Morgeson and Campion, Michael A.}, editor = {W. Borman and Ilgen, D. and Klimoski, R.} } @article {2002, title = {Can we ever escape from data overload? A cognitive systems diagnosis}, journal = {Cognition, Technology \& Work}, volume = {4}, year = {2002}, month = {Jan-04-2002}, pages = {22 - 36}, issn = {1435-5558}, doi = {10.1007/s101110200002}, author = {Woods, D. D. and Patterson, E. S. and Roth, E. M.} } @article {2002, title = {Converging technologies for improving human performance: Integrating from the nanoscale}, journal = {Journal of Nanoparticle Research}, volume = {4}, year = {2002}, month = {07/2002}, pages = {281-295}, url = {https://link.springer.com/article/10.1023/A:1021152023349}, author = {M. C. Roco and W. S. Bainbridge} } @article {RN2496, title = {Bringing work back in}, journal = {Organization Science}, volume = {12}, number = {1}, year = {2001}, pages = {76{\textendash}95}, type = {Journal Article}, doi = {10.1287/orsc.12.1.76.10122}, author = {Stephen R. Barley and Kunda, Gideon} } @article {2001, title = {Desperately seeking "IT" in IT research: A call to theorizing the IT artifact}, journal = {Information Systems ResearchInformation Systems Research}, volume = {12}, number = {2}, year = {2001}, pages = {121{\textendash}134}, author = {Wanda J. Orlikowski and C. Suzanne Iacono} } @article {2001, title = {Shift changes, updates, and the on-call architecture in space shuttle mission control}, journal = {Computer Supported Cooperative Work (CSCW)}, volume = {10}, year = {2001}, month = {Jan-09-2001}, pages = {317 - 346}, issn = {0925-9724}, doi = {10.1023/A:1012705926828}, author = {Patterson, Emily S. and Woods, David D.} } @article {2000, title = {From human {\textendash} machine interaction to human {\textendash} machine cooperation}, journal = {Ergonomics}, volume = {43}, year = {2000}, month = {Oct-07-2000}, pages = {833 - 843}, issn = {0014-0139}, doi = {10.1080/001401300409044}, author = {Hoc, Jean-Michel} } @article {2000, title = {Technical change, inequality, and the labor market}, year = {2000}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w7800}, author = {Acemoglu, Daron} } @article {1999, title = {Information technology, workplace organization and the demand for skilled labor}, year = {1999}, institution = {National Bureau of Economic Research}, address = {Cambridge, MA}, doi = {10.3386/w7136}, author = {Bresnahan, Timothy and Brynjolfsson, Erik and Hitt, Lorin} } @inbook {RN30398, title = {Automation surprises}, booktitle = {Handbook of Human Factors and Ergonomics}, volume = {2}, year = {1997}, pages = {1926{\textendash}1943}, type = {Book Section}, author = {Sarter, Nadine B. and Woods, David D. and Billings, Charles E.} } @book {1997, title = { Computer Science and Artificial Intelligence}, year = {1997}, url = {https://www.nap.edu/read/5812/chapter/1}, author = {Panel on Computer Science and Artificial Intelligence} } @article {1996, title = {Distributed cognition in an airline cockpit}, journal = {Cognition and Communication at WorkCognition and communication at work}, year = {1996}, pages = {15{\textendash}34}, author = {Hutchins, Edwin and Klausen, Tove} } @article {1995, title = {Application of Machine Learning and Rule Induction}, year = {1995}, url = {https://dl.acm.org/citation.cfm?id=219768}, author = {Pat Langley} } @proceedings {1995, title = {Complementary allocation of functions in automated work systems}, volume = {20}, year = {1995}, pages = {989-994}, publisher = {Elsevier}, author = {G. Grote and S. Weik and T. Wafler and M. Zolch} } @proceedings {1995, title = {Integration of people, technology and organization: the european approach}, volume = {20}, year = {1995}, pages = {957-961}, publisher = {Elsevier}, address = {Tokyo, Japan}, abstract = {This paper presents the general outline of new method, HITOP-D, considering the integration and joint optimization of people, technology, and organization. This method is based on the existing american methods HITOP and ACTION. It takes in account the specific european industrial context. In an iterating process the preliminary design of a project is assessed according a list of criteria of the four aspects people, technology, organization, and task design. Incongruencies are solved through a fit analysis and redesigning the original project. The performance of HITOP-D will be empirically evaluated.}, author = {Christina Kirsch and Peter Troxier and Eberhard Ulich} } @article {1994, title = {Design concepts of computer-aided integrated manufacturing systems: Work-psychological concepts and empirical findings}, journal = {International Journal of Industrial Ergonomics}, volume = {17}, year = {1994}, publisher = {Elsevier}, chapter = {11-19}, abstract = {The research project "GRIPS" is investigating the design of computer-aided integrated manufacturing systems from a work psychological perspective. The goal is to develop and empirically support adequate design concepts. The project consists of three phases. Evidence from a broad questionnaire survey indicates that most CIM implementations fail to meet expectations associated therewith. Based on the assumption that only the joint optimization of social and technical system results in humane working conditions and economic efficiency, implementations and use of CIM systems has been investigated in 60 companies in Switzerland. THe conceptual framework distinguishes technically-oriented and work-oriented design concepts on four levels; the enterprise, the organizational unit, the group and the individual. Work-oriented manufacturing systems - as opposed to technically-oriented ones - are characterized by decentralization, functional integration, work in self-regulated groups and complete and challenging tasks. The findings support the hypothesis that work-oriented design concepts are related to higher efficiency and better achievement of goals and pursued with the use of new technologies. In the third phase 12 companies have been selected for detailed case studies: The companies are comparable concerning product range and manufacturing conditions but different on the level of work-orientation.}, keywords = {Computer-Integrated-Manufacturing CIM, Organizational design, Production design concepts, Socio-technical system approach, Work psychology, Work-orientation}, author = {C. Kirsh and O. Strohm and E. Ulich} } @article {1991, title = {Development and test of a task level model of motivational job design}, journal = {Journal of Applied Psychology}, volume = {76}, number = {6}, year = {1991}, pages = {825{\textendash}837}, author = {Wong, Chi-sum and Campion, Michael A.} } @article {RN30630, title = {The alignment of technology and structure through roles and networks}, journal = {Administrative science quarterly}, year = {1990}, pages = {61-103}, type = {Journal Article}, issn = {0001-8392}, author = {Stephen R. Barley} } @article {1989, title = {Expert systems for configuration at digital: xcon and beyond}, volume = {32}, year = {1989}, chapter = {298-318}, doi = {10.1145/62065.62067}, author = {Virginia E. Barker and Dennis E. O{\textquoteright}Connor} } @article {RN30476, title = {New technologies, new skills}, journal = {California Management Review}, volume = {29}, number = {1}, year = {1986}, pages = {9{\textendash}28}, type = {Journal Article}, author = {Adler, Paul} } @article {1982, title = {Office automation: A progress report}, journal = {Office Technology and People}, volume = {1}, year = {1982}, month = {Jan-01-1982}, pages = {107 - 121}, issn = {0167-5710}, doi = {10.1108/eb022608}, author = {Dean Meyer, N.} } @inbook {1981, title = {The socio-technical perspective: The evolution of socio-technical systems as a conceptual framework and action research program}, booktitle = {Perspectives in Organization Design and Behavior}, year = {1981}, pages = {32{\textendash}47}, publisher = {John Wiley}, organization = {John Wiley}, address = {London}, author = {Trist, E.}, editor = {van de Ven, A.H. and Joyce, W. F.} } @book {1980, title = {Work Redesign}, year = {1980}, publisher = {Addison-Wesley}, organization = {Addison-Wesley}, address = {Reading, MA}, author = {J. Richard Hackman and Oldham, G. R.} } @article {1966, title = {{\textquotedblleft}Algorithm{\textquotedblright} and {\textquotedblleft}formula{\textquotedblright}}, journal = {Communications of the ACM}, volume = {9}, year = {1966}, month = {Jan-04-1966}, pages = {243}, issn = {00010782}, doi = {10.1145/365278.365286}, author = {Wangsness, T. and Franklin, J.} } @article {1965, title = {Automation and the Division of Labor}, journal = {Social Problems}, volume = {13}, year = {1965}, month = {Jan-10-1965}, pages = {149 - 160}, issn = {00377791}, doi = {10.2307/798900}, author = {Faunce, William A.} } @article {1951, title = {Some social and psychological consequences of the Longwall Method of coal-getting: An examination of the psychological situation and defences of a work group in relation to the social structure and technological content of the work system}, journal = {Human relationsHuman Relations}, volume = {4}, number = {1}, year = {1951}, pages = {3-38}, isbn = {0018-7267}, author = {Trist, Eric Lansdowne and Bamforth, Ken W} } @book {1911, title = {The Principles of Scientific Management}, year = {1911}, publisher = {Norton \& Company}, organization = {Norton \& Company}, address = {New York}, keywords = {Productionmanagement}, author = {Taylor, F. W.} }