%0 Journal Article %J Information, Technology & People %D In Press %T Technological Frames: Interpretations about the Futures of Work and Intelligent Machines on Social Media %A Ayşe Öcal %A Kevin Crowston %X 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’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’ or workers’ 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. %B Information, Technology & People %G eng %> https://waim.network/sites/crowston.syr.edu/files/frames%20to%20share.pdf %0 Journal Article %J IEEE Transactions on Software Engineering %D 2024 %T Making sense of AI systems development %A Mateusz Dolata %A Kevin Crowston %X 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’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. %B IEEE Transactions on Software Engineering %V 50 %P 123–140 %8 12/2023 %G eng %N 1 %R 10.1109/TSE.2023.3338857 %> https://waim.network/sites/crowston.syr.edu/files/sensemaking_tse_to_share.pdf %0 Conference Proceedings %B CHI Conference on Human Factors in Computing Systems %D 2024 %T ReelFramer: Human-AI Co-Creation for News-to-Video Translation %A Sitong Wang %A Samia Menon %A Tao Long %A Keren Henderson %A Dingzeyu Li %A Kevin Crowston %A Mark Hansen %A Jeffrey V. Nickerson %A Lydia B. Chilton %X

Short videos on social media are the dominant way young people consume content. News outlets aim to reach audiences through news reels -- short videos conveying news -- but struggle to translate traditional journalistic formats into short, entertaining videos. To translate news into social media reels, we support journalists in reframing the narrative. In literature, narrative framing is a high-level structure that shapes the overall presentation of a story. We identified three narrative framings for reels that adapt social media norms but preserve news value, each with a different balance of information and entertainment. We introduce ReelFramer, a human-AI co-creative system that helps journalists translate print articles into scripts and storyboards. ReelFramer supports exploring multiple narrative framings to find one appropriate to the story. AI suggests foundational narrative details, including characters, plot, setting, and key information. ReelFramer also supports visual framing; AI suggests character and visual detail designs before generating a full storyboard. Our studies show that narrative framing introduces the necessary diversity to translate various articles into reels, and establishing foundational details helps generate scripts that are more relevant and coherent. We also discuss the benefits of using narrative framing and foundational details in content retargeting.

%B CHI Conference on Human Factors in Computing Systems %C Honolulu, Hawai'i %G eng %U https://arxiv.org/abs/2304.09653 %0 Conference Proceedings %B Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems %D 2023 %T AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models %A Petridis, Savvas %A Diakopoulos, Nicholas %A Crowston, Kevin %A Hansen, Mark %A Henderson, Keren %A Jastrzebski, Stan %A Nickerson, Jefrey V %A Chilton, Lydia B %B Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems %G eng %U https://savvaspetridis.github.io/papers/anglekindling.pdf %R 10.1145/3544548.3580907 %0 Journal Article %J Communications of the Association for Information Systems (CAIS) %D 2022 %T Artificial intelligence in information systems: State of the art and research roadmap %A Pär J. Ågerfalk %A Kieran Conboy %A Kevin Crowston %A Sirkka L. Jarvenpaa %A Jenny Eriksson Lundström %A Patrick Mikalef %A Sudha Ram %X

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.

%B Communications of the Association for Information Systems (CAIS) %V 50 %G eng %R 10.17705/1CAIS.05017 %> https://waim.network/sites/crowston.syr.edu/files/Artificial%20Intelligence%20in%20Information%20Systems%20State%20of%20the%20Art.pdf %0 Conference Paper %B International Conference on Information Systems (ICIS) %D 2022 %T Project archetypes: A blessing and a curse for AI development %A Mateusz Dolata %A Kevin Crowston %A Gerhard Schwabe %X

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.

%B International Conference on Information Systems (ICIS) %C Copenhagen, Denmark %G eng %U https://aisel.aisnet.org/icis2022/is_design/is_design/6 %> https://waim.network/sites/crowston.syr.edu/files/icis_archetypes_rev1_v20_zora.pdf %0 Journal Article %J Electronic Markets %D 2021 %T Hybrid intelligence in business networks %A Ebel, Philipp %A Söllner, Matthias %A Leimeister, Jan Marco %A Crowston, Kevin %A de Vreede, Gert-Jan %B Electronic Markets %8 Nov-06-2021 %G eng %R 10.1007/s12525-021-00481-4 %> https://waim.network/sites/crowston.syr.edu/files/Ebel2021_Article_HybridIntelligenceInBusinessNe.pdf %0 Journal Article %J 2020 22nd International Conference on Advanced Communication Technology (ICACT) %D 2020 %T The Adoption of Artificial Intelligence for Financial Investment Service %A Noonpakdee, Wasinee %K AI %K artificial intelligence %K data %K financial %K fintech %K investment service %K Technology Adoption %K to investment companies %K to offer customers accessibility %B 2020 22nd International Conference on Advanced Communication Technology (ICACT) %I Global IT Research Institute - GIRI %P 396–400 %@ 9791188428045 %G eng %0 Journal Article %J Journal of Service Management %D 2020 %T AI feel you: customer experience assessment via chatbot interviews %A Sidaoui, Karim %A Jaakkola, Matti %A Burton, Jamie %K artificial intelligence %K chatbot %K Customer experience %K Customer feelings %K Sentiment analysis %K Storytelling %X 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'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. %B Journal of Service Management %G eng %R 10.1108/JOSM-11-2019-0341 %0 Journal Article %J Telecommunications Policy %D 2020 %T AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings %A Kuziemski, Maciej %A Misuraca, Gianluca %K Algorithmic accountability %K artificial intelligence %K Automated decision making %K Public sector innovation %X 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'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' 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; “optimising” the employment services” 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 – or undermine - trust in governance systems and democracy. %B Telecommunications Policy %I Elsevier Ltd %V 44 %P 101976 %G eng %U https://doi.org/10.1016/j.telpol.2020.101976 %R 10.1016/j.telpol.2020.101976 %0 Journal Article %J Journal of Data, Information and Management %D 2020 %T AI in operations management: applications, challenges and opportunities %A Dogru, Ali K %A Keskin, Burcu B %K AI %K artificial intelligence %K Artificial Intelligence (AI) %K automation %K machine learning %K machine learning (ML) %K ml %K om %K operations management %K Operations Management (OM) %K Robotics %K scm %K supply chain management %K Supply Chain Management (SCM) %X 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. %B Journal of Data, Information and Management %I Journal of Data, Information and Management %V 2 %P 67–74 %G eng %R 10.1007/s42488-020-00023-1 %0 Journal Article %J Business Horizons %D 2020 %T AI-enabled recruiting: What is it and how should a manager use it? %A Black, J Stewart %A van Esch, Patrick %K AI-enabled recruiting %K artificial intelligence %K Digital recruiting technology %K Human resources %X 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. %B Business Horizons %I Elsevier Ltd %V 63 %P 215–226 %G eng %U https://doi.org/10.1016/j.bushor.2019.12.001 %R 10.1016/j.bushor.2019.12.001 %0 Conference Paper %B Computation + Journalism Symposium %D 2020 %T Algorithmic Journalism and Its Impacts on Work %A Ayse Dalgali %A Kevin Crowston %X

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.

%B Computation + Journalism Symposium %7 (cancelled due to COVID; presented in 2021) %G eng %U https://cpb-us-w2.wpmucdn.com/express.northeastern.edu/dist/d/53/files/2020/02/CJ_2020_paper_26.pdf %> https://waim.network/sites/crowston.syr.edu/files/CJ_2020_paper_26.pdf %0 Journal Article %J Academy of Management Annals %D 2020 %T Algorithms at work: The new contested terrain of control %A Kellogg, Katherine C. %A Valentine, Melissa A. %A Christin, Angéle %B Academy of Management Annals %V 14 %P 366 - 410 %8 Jan-01-2020 %G eng %N 1 %R 10.5465/annals.2018.0174 %0 Journal Article %J Cambridge Journal of Regions, Economy and Society %D 2020 %T Are machines stealing our jobs? %A Gentili, Andrea %A Compagnucci, Fabiano %A Gallegati, Mauro %A Valentini, Enzo %K cluster analysis %K e24 %K e66 %K j24 %K jel classifications %K labour dislocation %K robotisation %X 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. %B Cambridge Journal of Regions, Economy and Society %V 13 %P 153–173 %G eng %R 10.1093/cjres/rsz025 %0 Book %D 2020 %T Artificial Intelligence and Judicial Modernization %A Cui, Yadong %I Springer Singapore %C Singapore %@ 978-981-32-9879-8 %G eng %R 10.1007/978-981-32-9880-4 %0 Journal Article %J Journal of the Association for Information Science and Technology %D 2020 %T Artificial intelligence and the world of work, a co-constitutive relationship %A Østerlund, Carsten %A Jarrahi, Mohammad Hossein %A Willis, Matthew %A Boyd, Karen %A Wolf, Christine %X

The use of intelligent machines—digital technologies that feature data- driven forms of customization, learning, and autonomous action—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).

%B Journal of the Association for Information Science and Technology %G eng %R 10.1002/asi.24388 %0 Conference Paper %B Proceedings of the 6th International Conference on Social, economic, and academic leadership (ICSEAL-6-2019) %D 2020 %T Artificial Intelligence in the Criminal Justice System: Leading Trends and Possibilities %A Sushina, Tatyana %A Sobenin, Andrew %K artificial intelligence %K criminal justice system %K digital technologies %K Leadership %B Proceedings of the 6th International Conference on Social, economic, and academic leadership (ICSEAL-6-2019) %I Atlantis Press %C Paris, France %V 441 %P 432–437 %@ 978-94-6252-974-8 %G eng %U https://www.atlantis-press.com/article/125940991 %R 10.2991/assehr.k.200526.062 %0 Conference Paper %B Proceedings of the 53rd Hawaii International Conference on System Sciences %D 2020 %T Assessing the Business Impact of Artificial Intelligence %A Dietzmann, Christian %A Alt, Rainer %X El autor propone la creación de una agencia que certificque los procesos de IA. El no certificado RCO. Tambien habla de las características 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 evalución en el mercado. %B Proceedings of the 53rd Hawaii International Conference on System Sciences %V 3 %P 5170–5179 %@ 9780998133133 %G eng %R 10.24251/hicss.2020.635 %0 Report %D 2020 %T Automation: A Guide for Policymakers %A Bessen, James %A Goos, Maarten %A Salomons, Anna %A van den Berge, Wiljan %X

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

%I Brookings Institute %G eng %U https://www.brookings.edu/research/automation-a-guide-for-policymakers/ %0 Generic %D 2020 %T Automation and Radiology—Part 1 %A Jha, Saurabh %B Academic Radiology %I Elsevier Inc. %V 27 %P 147–149 %G eng %U https://doi.org/10.1016/j.acra.2019.10.026 %R 10.1016/j.acra.2019.10.026 %0 Generic %D 2020 %T Automation Technologies and Employment at Risk : The Case of Mexico %A Cebreros, Alfonso %A Heffner-Rodríguez, Aldo %A Livas, René %A Puggioni, Daniela %I Banco de México %G eng %0 Journal Article %J Journal of Tourism Futures %D 2020 %T The benefits of eHRM and AI for talent acquisition %A Johnson, Richard D %A Stone, Dianna L %A Lukaszewski, Kimberly M %K artificial intelligence %K e-HRM %K e-recruiting %K e-selection %K eHRM %K Electronic human resource management %K Employee selection %K Recruitment %K Selection %X 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. %B Journal of Tourism Futures %G eng %R 10.1108/JTF-02-2020-0013 %0 Journal Article %J Mobile Networks and Applications %D 2020 %T A Cautionary Tale for Machine Learning Design: why we Still Need Human-Assisted Big Data Analysis %A Roccetti, Marco %A Delnevo, Giovanni %A Casini, Luca %A Salomoni, Paola %K Human-in-the-loop methods %K Human-machine-Bigdata interaction loop %K Machine learning design %K Smart data %K Water metering and consumption %X 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. %B Mobile Networks and Applications %I Mobile Networks and Applications %V 25 %P 1075–1083 %G eng %R 10.1007/s11036-020-01530-6 %0 Journal Article %J AI %D 2020 %T Cities of the Future? The Potential Impact of Artificial Intelligence %A Kassens-Noor, Eva %A Hintze, Arend %K artificial intelligence %K autonomous vehicle %K future %K smart cities %K work %X 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. %B AI %V 1 %P 192–197 %G eng %R 10.3390/ai1020012 %0 Journal Article %J AEA Papers and Proceedings %D 2020 %T Competing with Robots: Firm-Level Evidence from France %A Acemoglu, Daron %A Lelarge, Claire %A Restrepo, Pascual %K automation %K competition %K j23 %K j24 %K jel codes %K l11 %K labor share %K manufacturing %K productivity %K reallocation %K robots %K tasks %X 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. %B AEA Papers and Proceedings %V 110 %P 383–388 %G eng %R 10.1257/pandp.20201003 %0 Conference Paper %B Proceedings of the 53rd Hawaii International Conference on System Sciences %D 2020 %T Conceptualization of the Human-Machine Symbiosis – A Literature Review %A Gerber, Alina %A Derckx, Patrick %A Döppner, Daniel A %A Schoder, Detlef %X 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. %B Proceedings of the 53rd Hawaii International Conference on System Sciences %V 3 %P 289–298 %@ 9780998133133 %G eng %R 10.24251/hicss.2020.036 %0 Journal Article %J ERA Forum %D 2020 %T Criminal justice, artificial intelligence systems, and human rights %A Završnik, Aleš %K Algorithms %K artificial intelligence %K automation %K Criminal justice %K Fair trial %K Human rights %X 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. %B ERA Forum %I The Author(s) %V 20 %P 567–583 %@ 1202702000602 %G eng %U http://dx.doi.org/10.1007/s12027-020-00602-0 %R 10.1007/s12027-020-00602-0 %0 Conference Paper %B AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society %D 2020 %T Does AI qualify for the job? A bidirectional model mapping labour and AI intensities %A Mart'nez-Plumed, Fernando %A Tolan, Song'l %A Pesole, Annarosa %A Hern'ndez-Orallo, José %A Fern'ndez-Mac'as, Enrique %A G'mez, Emilia %K AI benchmarks %K AI impact %K AI intensity %K Labour market %K Simulation %K tasks %X 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. %B AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society %P 94–100 %@ 9781450371100 %G eng %R 10.1145/3375627.3375831 %0 Manuscript %D 2020 %T Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance %A Bansal, Gagan %A Wu, Tongshuang %A Zhou, Joyce %A Fok, Raymond %A Nushi, Besmira %A Kamar, Ece %A Ribeiro, Marco Tulio %A Weld, Daniel S. %X

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's confidence. We show that explanations increase the chance that humans will accept the AI'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?

%G eng %U http://arxiv.org/abs/2006.14779 %0 Journal Article %J Journal of Service Research %D 2020 %T Engaged to a Robot? The Role of AI in Service %A Huang, Ming Hui %A Rust, Roland T %K artificial intelligence %K augmentation %K automation %K engagement %K feeling AI %K human intelligence %K mechanical AI %K personalization %K relationalization %K replacement %K robots %K service process %K service strategy %K standardization %K thinking AI %X 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. %B Journal of Service Research %G eng %R 10.1177/1094670520902266 %0 Journal Article %J Telecommunications Policy %D 2020 %T Ethics of autonomous weapons systems and its applicability to any AI systems %A Gómez de Ágreda, Ángel %K AI ethics %K Autonomous weapons %K CCW %K Dual-use AI %K Explainability %K Meaningful human control %X 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. %B Telecommunications Policy %I Elsevier Ltd %V 5 %P 101953 %G eng %U https://doi.org/10.1016/j.telpol.2020.101953 %R 10.1016/j.telpol.2020.101953 %0 Journal Article %J Artificial Intelligence and Law %D 2020 %T Explainable AI under contract and tort law: legal incentives and technical challenges %A Hacker, Philipp %A Krestel, Ralf %A Grundmann, Stefan %A Naumann, Felix %K Contract law %K Corporate takeovers %K Explainability %K Explainability-accuracy trade-off %K Explainable AI %K Interpretable machine learning %K Medical malpractice %K Tort law %X 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. %B Artificial Intelligence and Law %I Springer Netherlands %@ 0123456789 %G eng %U https://doi.org/10.1007/s10506-020-09260-6 %R 10.1007/s10506-020-09260-6 %0 Conference Proceedings %B Hawai'i International Conference on System Science %D 2020 %T Factors Influencing Approval of Wikipedia Bots %A Ayse Dalgali %A Kevin Crowston %X

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’ project pages. The results suggest that usefulness, value-based decision making and the bot’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.

%B Hawai'i International Conference on System Science %C Wailea, HI %G eng %R 10.24251/HICSS.2020.018 %> https://waim.network/sites/crowston.syr.edu/files/HICSS_WikipediaPaper_3.9.new%20kc%20%282%29.pdf %0 Journal Article %J EPA: Economy and Space %D 2020 %T Feminist economic geography and the future of work %A Reid-musson, Emily %A Cockayne, Daniel %A Frederiksen, Lia %A Worth, Nancy %K corresponding author %K department of geography %K emily reid-musson %K feminist economic geography %K memorial university of newfoundland %K newfoundland and labrador a1c %K social reproduction %K subjectivity %K technology %K work %B EPA: Economy and Space %P 1–12 %G eng %R 10.1177/0308518X20947101 %0 Generic %D 2020 %T Frameworks for collective intelligence: A systematic literature review %A Suran, Shweta %A Pattanaik, Vishwajeet %A Draheim, Dirk %K collective intelligence %K Crowdsourcing %K Human computer interaction %K Systematic literature review %K Web 2.0 %K Wisdom of crowds %X 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. %B ACM Computing Surveys %V 53 %P 1–36 %G eng %R 10.1145/3368986 %0 Journal Article %J IZA Discussion Paper Series %D 2020 %T The Future of Work: Challenges for Job Creation Due to Global Demographic Change and Automation %A Abeliansky, Ana %A Algur, Eda %A Bloom, David E %A Prettner, Klaus %K demography %K labor %K unemployment %B IZA Discussion Paper Series %G eng %U www.iza.org %0 Journal Article %J MIT Sloan Management Review %D 2020 %T The Future of Work in Developing Economies %A Egana del Sol, Pablo %A Joyce, Connor %A Del Sol, Pablo Egaña %A Joyce, Connor %K Armenia %K Asia %K Austria %K automation %K Bolivia %K Business And Economics–Management %K China %K Developing countries–LDCs %K Employment %K future %K Georgia (country) %K Ghana %K Impact analysis %K Kenya %K Kuala Lumpur Malaysia %K Laos %K Republic of North Macedonia %K South Korea %K Sri Lanka %K United States–US %K Vietnam %K Workers %X

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.

%B MIT Sloan Management Review %V 61 %P 1–3 %G eng %0 Journal Article %J International Labour Review %D 2020 %T The Future of Work: Meeting the Global Challenge of Demographic Change and Automation %A Abeliansky, Ana L. %A Algur, Eda %A Bloom, David E %A Prettner, Klaus %X We explore future job creation needs under conditions of demographic, economic, and technological change. First, we estimate the implications for job creation in 2020–2030 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 2020–2030. %B International Labour Review %P 1–28 %G eng %R 10.1111/ilr.12168 %0 Conference Proceedings %B Hawai'i International Conference on System Science %D 2020 %T The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning %A Mahboobeh Harandi %A Kevin Crowston %A Corey Jackson %A Carsten Østerlund %X

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.

%B Hawai'i International Conference on System Science %C Wailea, HI %G eng %9 Working paper %R 10.24251/HICSS.2020.719 %> https://waim.network/sites/crowston.syr.edu/files/Social_Construction_of_ML_in_GS_HICCS2020.pdf %0 Journal Article %J Academic Radiology %D 2020 %T How the FDA regulates AI %A Harvey, H. Benjamin %A Gowda, Vrushab %B Academic Radiology %V 27 %P 58 - 61 %8 Jan-01-2020 %G eng %N 1 %R 10.1016/j.acra.2019.09.017 %0 Journal Article %J Bulletin of the World Health Organization %D 2020 %T How to achieve trustworthy artificial intelligence for health %A Bærøe, Kristine %A Miyata-Sturm, Ainar %A Henden, Edmund %X 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'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. %B Bulletin of the World Health Organization %V 98 %P 257–262 %G eng %R 10.2471/BLT.19.237289 %0 Journal Article %J Science, Technology, & Human Values %D 2020 %T Humanly Extended Automation or the Future of Work Seen through Amazon Patents %A Delfanti, Alessandro %A Frey, Bronwyn %X

Amazon'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' activities into machinery to rationalize the labor process in an ever more pervasive form of digital Taylorism. Patents materialize the company'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.

%B Science, Technology, & Human Values %P 016224392094366 %G eng %U http://journals.sagepub.com/doi/10.1177/0162243920943665 %R 10.1177/0162243920943665 %0 Conference Proceedings %B 8th International Conference on Human-Agent Interaction %D 2020 %T Impacts of the Use of Machine Learning on Work Design %A Kevin Crowston %A Bolici, Francesco %K artificial intelligence %K automation %K Coordination %K machine learning %K work design %X

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—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.

%B 8th International Conference on Human-Agent Interaction %I ACM %C Virtual Event, NSW, Australia %8 11/2020 %@ 978-1-4503-8054-6/20/11 %G eng %R 10.1145/3406499.3415070 %> https://waim.network/sites/crowston.syr.edu/files/Impacts_of_ML_for_HAI_2020.pdf %0 Journal Article %J AI %D 2020 %T Implementation of Artificial Intelligence (AI): A Roadmap for Business Model Innovation %A Reim, Wiebke %A Åström, Josef %A Eriksson, Oliver %K artificial intelligence %K business model innovation %K business models %K implementation %X 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'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'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. %B AI %V 1 %P 180–191 %G eng %R 10.3390/ai1020011 %0 Journal Article %J Technological Forecasting and Social Change %D 2020 %T Industrial robots, employment growth, and labor cost: A simultaneous equation analysis %A Jung, Jin Hwa %A Lim, Dong Geon %K Compensation level %K Employment growth %K Industrial robots %K Labor cost %K Simultaneous equation analysis %X 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. %B Technological Forecasting and Social Change %I Elsevier %V 159 %P 120202 %G eng %U https://doi.org/10.1016/j.techfore.2020.120202 %R 10.1016/j.techfore.2020.120202 %0 Generic %D 2020 %T International organisations and the future of work: How new technologies and inequality shaped the narratives in 2019 %A Grimshaw, Damian %K future of work %K Inequality %K International Labour Organization %K international organisations %K labour income share %K new technologies %X In a critical review of seven prominent flagship reports from five international organisations – 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 – 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. %B Journal of Industrial Relations %V 62 %P 477–507 %G eng %R 10.1177/0022185620913129 %0 Conference Paper %B Proceedings of the 2020 IEEE Communication Strategies in Digital Society Seminar, ComSDS 2020 %D 2020 %T Key Advantages and Risks of Implementing Artificial Intelligence in the Activities of Professional Communicators %A Azarova, Liudmila %A Kudryavtseva, Maria %A Sharakhina, Larisa %K AI technologies risks %K artificial intelligence %K digital technologies %K professional communicators %X 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. %B Proceedings of the 2020 IEEE Communication Strategies in Digital Society Seminar, ComSDS 2020 %P 82–86 %@ 9781728164410 %G eng %R 10.1109/ComSDS49898.2020.9101238 %0 Conference Paper %B AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society %D 2020 %T Learning occupational task-shares dynamics for the future of work %A Das, Subhro %A Steffen, Sebastian %A Clarke, Wyatt %A Reddy, Prabhat %A Brynjolfsson, Erik %A Fleming, Martin %K AI %K automation %K future of work %K Occupational Task Demands %X 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' 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. %B AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society %P 36–42 %@ 9781450371100 %G eng %R 10.1145/3375627.3375826 %0 Conference Paper %B Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual %D 2020 %T Lessons for Supporting Data Science from the Everyday Automation Experience of Spell-Checkers %A Kevin Crowston %X

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.

%B Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual %C Virtual workshop %8 4/2020 %G eng %> https://waim.network/sites/crowston.syr.edu/files/Everyday_automation%20camera%20ready.pdf %0 Journal Article %J Artificial Intelligence in Precision Health %D 2020 %T Machine learning-based clinical prediction modeling – A practical guide for clinicians %A Kernbach, Julius M. %A Staartjes, Victor E. %K Alzheimers disease detection %K artificial intelligence %K Convolutional neural networks %K Deep neural networks %K Ensemble machine learning methods %B Artificial Intelligence in Precision Health %I Elsevier Inc. %P 257–278 %@ 9780128171332 %G eng %U https://arxiv.org/abs/2006.15069v1 http://dx.doi.org/10.1016/B978-0-12-817133-2.00011-2 %R 10.1016/b978-0-12-817133-2.00011-2 %0 Journal Article %J Information and Management %D 2020 %T Machines as teammates: A research agenda on AI in team collaboration %A Seeber, Isabella %A Bittner, Eva %A Briggs, Robert O %A de Vreede, Triparna %A de Vreede, Gert Jan %A Elkins, Aaron %A Maier, Ronald %A Merz, Alexander B %A Oeste-Reiß, Sarah %A Randrup, Nils %A Schwabe, Gerhard %A Söllner, Matthias %K artificial intelligence %K Design %K Duality %K Research agenda %K Team collaboration %X 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 – Machine artifact, Collaboration, and Institution – and 17 dualities – 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. %B Information and Management %I Elsevier %V 57 %P 103174 %G eng %U https://doi.org/10.1016/j.im.2019.103174 %R 10.1016/j.im.2019.103174 %0 Journal Article %J Technological Forecasting and Social Change %D 2020 %T Matching the future capabilities of an artificial intelligence-based software for social media marketing with potential users' expectations %A Capatina, Alexandru %A Kachour, Maher %A Lichy, Jessica %A Micu, Adrian %A Micu, Angela Eliza %A Codignola, Federica %K artificial intelligence %K Audience analysis %K Image analysis %K machine learning %K Sentiment analysis %K Social media marketing %X 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' 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' intention to test and use the software, based on an fsQCA approach. %B Technological Forecasting and Social Change %I Elsevier %V 151 %P 119794 %G eng %U https://doi.org/10.1016/j.techfore.2019.119794 %R 10.1016/j.techfore.2019.119794 %0 Journal Article %J Telecommunications Policy %D 2020 %T The nature of the Artificially Intelligent Firm - An economic investigation into changes that AI brings to the firm %A Wagner, Dirk Nicolas %K artificial intelligence %K Asymmetric information %K machine learning %K Principal-agent problem %K Theory of the firm %X 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). %B Telecommunications Policy %I Elsevier Ltd %V 44 %P 101954 %G eng %U https://doi.org/10.1016/j.telpol.2020.101954 %R 10.1016/j.telpol.2020.101954 %0 Journal Article %J Cambridge Journal of Regions, Economy and Society %D 2020 %T No automation please, we're British: Technology and the prospects for work %A Spencer, David %A Slater, Gary %K automation %K investment %K robots %K technology %K work %X 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. %B Cambridge Journal of Regions, Economy and Society %V 13 %P 117–134 %G eng %R 10.1093/cjres/rsaa003 %0 Conference Paper %B Proceedings of the 53rd Hawaii International Conference on System Sciences %D 2020 %T Predicting Automation of Professional Jobs in Healthcare %A Sampson, Scott %B Proceedings of the 53rd Hawaii International Conference on System Sciences %V 3 %P 3529–3537 %@ 9780998133133 %G eng %R 10.24251/hicss.2020.433 %0 Journal Article %J Journal of Service Research %D 2020 %T Replaced by a Robot: Service Implications in the Age of the Machine %A McLeay, Fraser %A Osburg, Victoria Sophie %A Yoganathan, Vignesh %A Patterson, Anthony %K brand usage intent %K ethical/societal reputation %K service experience %K service innovativeness %K service robots %X 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'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' 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. %B Journal of Service Research %G eng %R 10.1177/1094670520933354 %0 Generic %D 2020 %T Robo-Apocalypse cancelled? Reframing the automation and future of work debate %A Willcocks, Leslie %K AI %K automation %K cognitive automation %K future of work %K Information Technology %K Jobs %K robotic process automation %K skills %X 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'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. %B Journal of Information Technology %@ 0268396220925 %G eng %R 10.1177/0268396220925830 %0 Generic %D 2020 %T The robo-apocalypse plays out in the quality, not in the quantity of work %A Riemer, Kai %A Peter, Sandra %B Journal of Information Technology %G eng %R 10.1177/0268396220923677 %0 Journal Article %J International Journal of Social Robotics %D 2020 %T The Robot Economy : Here It Comes %A Arduengo, Miguel %A Sentis, Luis %K blockchain %K Cloud robotics %K Intelligent robots %K IoRT %K Robot economy %B International Journal of Social Robotics %I Springer Netherlands %G eng %U https://doi.org/10.1007/s12369-020-00686-1 %R 10.1007/s12369-020-00686-1 %0 Generic %D 2020 %T Robots and employment: evidence from Italy %A Dottori, Davide %X 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). %B Questioni di Economia e Finanza %I Banca d'Italia %G eng %0 Journal Article %J Computer Supported Cooperative Work: CSCW: An International Journal %D 2020 %T The Role of Discretion in the Age of Automation %A Petersen, Anette C.M. %A Christensen, Lars Rune %A Hildebrandt, Thomas T. %K Administrative work %K automation %K Casework %K Decision-Making %K Digital-ready legislation %K Digitisation %K Discretion %K Rules in action %K Social work %X 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. %B Computer Supported Cooperative Work: CSCW: An International Journal %V 29 %P 303–333 %G eng %R 10.1007/s10606-020-09371-3 %0 Conference Paper %B Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2020 %D 2020 %T Similarity Learning Networks for Animal Individual Re-Identification-Beyond the Capabilities of a Human Observer %A Schneider, Stefan %A Taylor, Graham W. %A Kremer, Stefan C. %X 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. %B Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2020 %V 479 %P 44–52 %@ 9781728171623 %G eng %R 10.1109/WACVW50321.2020.9096925 %0 Journal Article %J The TQM Journal %D 2020 %T Think with me, or think for me? On the future role of artificial intelligence in marketing strategy formulation %A Theresa, Eriksson %A Alessandro, Bigi %A Michelle, Bonera %A Eriksson, Theresa %A Bigi, Alessandro %A Bonera, Michelle %A Theresa, Eriksson %A Alessandro, Bigi %A Michelle, Bonera %K AI %K artificial intelligence %K creativity %K marketing strategy %K marketing synergy %K paper type research paper %K rationality %K tqm %X 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' organizational model. A key consideration is a “creative-possibility perspective,” 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 “creative-possibility perspective.”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. %B The TQM Journal %V ahead-of-p %8 jan %@ 1754-2731 %G eng %U https://doi.org/10.1108/TQM-12-2019-0303 %R 10.1108/TQM-12-2019-0303 %0 Journal Article %D 2020 %T Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims %A Brundage, Miles %A Avin, Shahar %A Wang, Jasmine %A Belfield, Haydn %A Krueger, Gretchen %A Hadfield, Gillian %A Khlaaf, Heidy %A Yang, Jingying %A Toner, Helen %A Fong, Ruth %A Maharaj, Tegan %A Koh, Pang Wei %A Hooker, Sara %A Leung, Jade %A Trask, Andrew %A Bluemke, Emma %A Lebensold, Jonathan %A O'Keefe, Cullen %A Koren, Mark %A Ryffel, Théo %A Rubinovitz, JB %A Besiroglu, Tamay %A Carugati, Federica %A Clark, Jack %A Eckersley, Peter %A de Haas, Sarah %A Johnson, Maritza %A Laurie, Ben %A Ingerman, Alex %A Krawczuk, Igor %A Askell, Amanda %A Cammarota, Rosario %A Lohn, Andrew %A Krueger, David %A Stix, Charlotte %A Henderson, Peter %A Graham, Logan %A Prunkl, Carina %A Martin, Bianca %A Seger, Elizabeth %A Zilberman, Noa %A HÉigeartaigh, Seán Ó %A Kroeger, Frens %A Sastry, Girish %A Kagan, Rebecca %A Weller, Adrian %A Tse, Brian %A Barnes, Elizabeth %A Dafoe, Allan %A Scharre, Paul %A Herbert-Voss, Ariel %A Rasser, Martijn %A Sodhani, Shagun %A Flynn, Carrick %A Gilbert, Thomas Krendl %A Dyer, Lisa %A Khan, Saif %A Bengio, Yoshua %A Anderljung, Markus %X 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–spanning institutions, software, and hardware–and make recommendations aimed at implementing, exploring, or improving those mechanisms. %P 1–9 %G eng %U http://arxiv.org/abs/2004.07213 %0 Conference Paper %B International Conference on Exploring Services Science %D 2020 %T Understanding the Impact of Artificial Intelligence on Services %A Ferreira, Pedro %A Teixeira, Jorge Grenha %A Teixeira, Luís F. %E Nóvoa, Henriqueta %E Drăgoicea, Monica %E Kühl, Niklas %K á servitization á design %K science research %K service design %X 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: %B International Conference on Exploring Services Science %S Lecture Notes in Business Information Processing %I Springer International Publishing %C Cham %V 1 %P 202–213 %@ 9783030387242 %G eng %U http://link.springer.com/10.1007/978-3-030-38724-2 %R 10.1007/978-3-030-38724-2 %0 Journal Article %J Computer Law & Security Review: The International Journal of Technology Law and Practice %D 2020 %T A vulnerability analysis : Theorising the impact of artificial intelligence decision-making processes on individuals , society and human diversity from a social justice perspective %A Krupiy, Tetyana Tanya %K artificial intelligence %K data science %K Decision-maki %B Computer Law & Security Review: The International Journal of Technology Law and Practice %I Elsevier Ltd %V 38 %P 105429 %G eng %U https://doi.org/10.1016/j.clsr.2020.105429 %R 10.1016/j.clsr.2020.105429 %0 Journal Article %J Cambridge Journal of Regions, Economy and Society %D 2020 %T When machines think for us: The consequences for work and place %A Clifton, Judith %A Clifton, Judith %A Glasmeier, Amy %A Gray, Mia %K artificial intelligence %K automation %K bias in machine learning %K geography of technology %K job displacement and growth %X 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. %B Cambridge Journal of Regions, Economy and Society %V 13 %P 3–23 %G eng %R 10.1093/cjres/rsaa004 %0 Generic %D 2020 %T White Paper on Artificial Intelligence - A European approach to excellence and trust %A Commission, European %X 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 Å 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. %B COM(2020) 65 final %G eng %U https://www.cambridge.org/core/product/identifier/CBO9781107415324A009/type/book_part %0 Generic %D 2019 %T AI, robots and jobs: Estimation and implications %A Eduardo Araral %G eng %U https://ehelf.nu.edu.kz/wp-content/uploads/2019/06/1-Eduardo-Araral-GSPP.pdf %0 Journal Article %J Digital Policy, Regulation and Governance %D 2019 %T AI’s path to the present and the painful transitions along the way %A Garcia-Murillo, Martha %A MacInnes, Ian %B Digital Policy, Regulation and Governance %V 21 %P 305 - 321 %8 Jan-05-2020 %G eng %N 3 %R 10.1108/DPRG-09-2018-0051 %0 Journal Article %J FlavorBot %D 2019 %T AI trained on decades of food research can concoct better recipes %B FlavorBot %G eng %U https://futurism.com/ai-food-research-better-recipes %0 Journal Article %J Asian Bioethics Review %D 2019 %T AI-Assisted Decision-making in Healthcare %A Lysaght, Tamra %A Lim, Hannah Yeefen %A Xafis, Vicki %A Ngiam, Kee Yuan %B Asian Bioethics Review %V 11 %P 299 - 314 %8 Jan-09-2019 %G eng %N 3 %R 10.1007/s41649-019-00096-0 %0 Journal Article %J Business & Information Systems Engineering %D 2019 %T AI-Based Digital Assistants %A Maedche, Alexander %A Legner, Christine %A Benlian, Alexander %A Berger, Benedikt %A Gimpel, Henner %A Hess, Thomas %A Hinz, Oliver %A Morana, Stefan %A Söllner, Matthias %B Business & Information Systems Engineering %V 61 %P 535 - 544 %8 Jan-08-2019 %G eng %N 4 %R 10.1007/s12599-019-00600-8 %0 Journal Article %J Transfer: European Review of Labour and Research %D 2019 %T Algorithms, artificial intelligence and automated decisions concerning workers and the risks of discrimination: the necessary collective governance of data protection %A Todolí-Signes, Adrián %B Transfer: European Review of Labour and Research %V 25 %P 465 - 481 %8 Jan-11-2019 %G eng %N 4 %R 10.1177/1024258919876416 %0 Journal Article %J International Studies Review %D 2019 %T Algorithms at War: The Promise, Peril, and Limits of Artificial Intelligence %A Jensen, Benjamin M %A Whyte, Christopher %A Cuomo, Scott %B International Studies Review %8 Dec-06-2020 %G eng %R 10.1093/isr/viz025 %0 Journal Article %J AI Daily %D 2019 %T Amazon's AI expansion %A Parth Mahendra %B AI Daily %8 06/2019 %G eng %U https://www.aidaily.co.uk/articles/amazons-ai-expansion %9 AI %0 Report %D 2019 %T The ambiguous labor market impact of automating prediction %A Agrawal, Ajay %A Gans, Joshua %A Goldfarb, Avi %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w25619 %0 Journal Article %J Forbes %D 2019 %T Apple reminds us that behind the AI revolution lies an army of humans seeing our data %A Kalev Leetaru %B Forbes %G eng %U 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 %0 Journal Article %J Biophysical Reviews %D 2019 %T Applications of artificial intelligence to imaging and diagnosis %A Nichols, James A. %A Herbert Chan, Hsien W. %A Baker, Matthew A. B. %B Biophysical Reviews %V 11 %P 111 - 118 %8 Jan-02-2019 %G eng %N 1 %R 10.1007/s12551-018-0449-9 %0 Journal Article %J Gizmodo %D 2019 %T Applying for your next job may be an automated nightmare %A Brian Merchant %K automation %K job %B Gizmodo %8 04/2019 %G eng %U https://gizmodo.com/applying-for-your-next-job-may-be-an-automated-nightmar-1834275825 %9 Automation %0 Journal Article %J The New Yorker %D 2019 %T Are robots competing for your job? %A Jill Lepore %B The New Yorker %8 03/2019 %G eng %U https://www.newyorker.com/magazine/2019/03/04/are-robots-competing-for-your-job %9 Annals of Technology %0 Journal Article %J Socius: Sociological Research for a Dynamic World %D 2019 %T Are robots stealing our jobs? %A Dahlin, Eric %B Socius: Sociological Research for a Dynamic World %V 5 %P 237802311984624 %8 Oct-01-2019 %G eng %R 10.1177/2378023119846249 %0 Journal Article %J IZA – Institute of Labor Economics %D 2019 %T Is an army of robots marching on Chinese jobs? %A Osea Giuntella %A Tianyi Wang %B IZA – Institute of Labor Economics %8 04/2019 %G eng %U https://www.iza.org/publications/dp/12281/is-an-army-of-robots-marching-on-chinese-jobs %N IZA DP No. 12281 %0 Journal Article %J Small Business Economics %D 2019 %T Artificial intelligence and big data in entrepreneurship: a new era has begun %A Obschonka, Martin %A Audretsch, David B. %B Small Business Economics %8 Jun-06-2019 %G eng %R 10.1007/s11187-019-00202-4 %0 Journal Article %J Journal of The Association of Physicians of India ■ Vol. 67 %D 2019 %T Artificial Intelligence and Deep Learning: The Future of Medicine and Medical Practice %A Madhusudana Girija Sanal %A Kolin Paul %A Senthil Kumar %A Nirmal Kumar Gangul %B Journal of The Association of Physicians of India ■ Vol. 67 %8 05/2019 %G eng %U https://www.semanticscholar.org/paper/Artificial-Intelligence-and-Deep-Learning%3A-The-of-Sanal-Paul/795dc72decfb12389bbf7076d82fef70421b9933 %0 Report %D 2019 %T Artificial intelligence and the future of labor demand %A Acemoglu, Daron %A Restrepo, Pascual %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w25682 %0 Journal Article %J Drug Safety %D 2019 %T Artificial Intelligence and the Future of the Drug Safety Professional %A Danysz, Karolina %A Cicirello, Salvatore %A Mingle, Edward %A Assuncao, Bruno %A Tetarenko, Niki %A Mockute, Ruta %A Abatemarco, Danielle %A Widdowson, Mark %A Desai, Sameen %B Drug Safety %V 42 %P 491 - 497 %8 Jan-04-2019 %G eng %N 4 %R 10.1007/s40264-018-0746-z %0 Journal Article %J Independent %D 2019 %T Artificial intelligence conquers starcraft II in 'unimaginably unusual' AI breakthrough %A Anthony Cuthbertson %B Independent %G eng %U https://www.independent.co.uk/life-style/gadgets-and-tech/gaming/artificial-intelligence-starcraft-2-ai-deepmind-a9176601.html %0 Journal Article %J Industrial Management & Data Systems %D 2019 %T Artificial Intelligence in FinTech: understanding robo-advisors adoption among customers %A Belanche, Daniel %A Casaló, Luis V. %A Flavián, Carlos %B Industrial Management & Data Systems %V 119 %P 1411 - 1430 %8 Dec-08-2019 %G eng %N 7 %R 10.1108/IMDS-08-2018-0368 %0 Journal Article %J Health Policy and Technology %D 2019 %T Artificial intelligence in medicine: What is it doing for us today? %A Becker, Aliza %B Health Policy and Technology %V 8 %P 198 - 205 %8 Jan-06-2019 %G eng %N 2 %R 10.1016/j.hlpt.2019.03.004 %0 Journal Article %J Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference %D 2019 %T Artificial intelligence in workplaces and how it will affect employment in Latvia %A Šukjurovs, Ilmārs %A Zvirgzdiņa, Rosita %A Jeromanova-Maura, Silva %B Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference %V 2 %P 154 %8 Aug-06-2020 %G eng %R 10.17770/etr2019vol2.4151 %0 Magazine Article %D 2019 %T As Walmart turns to robots, it’s the human workers who feel like machines %A Drew Harwell %B The Washington Post %8 06/2019 %G eng %U https://www.washingtonpost.com/technology/2019/06/06/walmart-turns-robots-its-human-workers-who-feel-like-machines/ %9 Technology %0 Report %D 2019 %T Automation and new tasks: How technology displaces and reinstates labor %A Acemoglu, Daron %A Restrepo, Pascual %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w25684 %0 Journal Article %J Journal of Management Inquiry %D 2019 %T Automation as Part of the Solution %A Levine, David I. %B Journal of Management Inquiry %V 28 %P 316 - 318 %8 Jun-07-2021 %G eng %N 3 %R 10.1177/1056492619827375 %0 Journal Article %J International Review of Economics & Finance %D 2019 %T Automation, wage inequality and implications of a robot tax %A Zhang, Pengqing %B International Review of Economics & Finance %V 59 %P 500 - 509 %8 Jan-01-2019 %G eng %R 10.1016/j.iref.2018.10.013 %0 Journal Article %J AI & SOCIETY %D 2019 %T Behavioural artificial intelligence: An agenda for systematic empirical studies of artificial inference %A Pedersen, Tore %A Johansen, Christian %B AI & SOCIETY %8 Jun-12-2020 %G eng %R 10.1007/s00146-019-00928-5 %0 Book %D 2019 %T Benefits and risks of artificial intelligence tools in workplaces %A Moore, Phoebe V. %E Duffy, Vincent G. %I Springer International Publishing %C Cham %V 11581 %P 292 - 315 %@ 978-3-030-22215-4 %G eng %R 10.1007/978-3-030-22216-1_22 %0 Conference Paper %B Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19 %D 2019 %T Beyond Dyadic Interactions: Considering Chatbots as Community Members %A Seering, Joseph %A Luria, Michal %A Kaufman, Geoff %A Hammer, Jessica %Y Brewster, Stephen %Y Fitzpatrick, Geraldine %Y Cox, Anna %Y Kostakos, Vassilis %B Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19 %I ACM Press %C Glasgow, Scotland UK %P 1-13 %@ 9781450359702 %G eng %R 10.1145/3290605 %0 Journal Article %J New Labor Forum %D 2019 %T Blame the boss, not the robot %A Smith, Zachary %B New Labor Forum %V 28 %P 66 - 69 %8 Oct-05-2020 %G eng %N 2 %R 10.1177/1095796019837947 %0 Journal Article %J Computer %D 2019 %T Bots Coordinating Work in Open Source Software Projects %A Hukal, Philipp %A Berente, Nicholas %A Germonprez, Matt %A Schecter, Aaron %B Computer %V 52 %P 52 - 60 %8 Jan-09-2019 %G eng %N 9 %R 10.1109/MC.2018.2885970 %0 Journal Article %J California Management Review %D 2019 %T A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence %A Haenlein, Michael %A Kaplan, Andreas %B California Management Review %V 61 %P 5 - 14 %8 Sep-08-2019 %G eng %N 4 %R 10.1177/0008125619864925 %0 Journal Article %J International Journal of Nursing Sciences %D 2019 %T Can nurses remain relevant in a technologically advanced future? %A Pepito, Joseph Andrew %A Locsin, Rozzano %B International Journal of Nursing Sciences %V 6 %P 106 - 110 %8 Jan-01-2019 %G eng %N 1 %R 10.1016/j.ijnss.2018.09.013 %0 Conference Paper %B Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences %D 2019 %T A chatbot for supporting teams in the empathy map method %A Bittner, Eva %A Shoury, Omid %Y Bui, Tung %B Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences %I Hawaii International Conference on System Sciences %G eng %R 10.24251/HICSS.2019.029 %0 Journal Article %J Futures %D 2019 %T Citizen attitudes about job replacement by robotic automation %A Nam, Taewoo %B Futures %V 109 %P 39 - 49 %8 Jan-05-2019 %G eng %R 10.1016/j.futures.2019.04.005 %0 Journal Article %J Economics, Management, and Financial Markets %D 2019 %T Cognitively enhanced products, output growth, and labor market changes: Will artificial intelligence replace workers by automating their jobs? %B Economics, Management, and Financial Markets %V 14 %P 38 %8 Jan-01-2019 %G eng %N 1 %R 10.22381/EMFM14120194 %0 Journal Article %J SSRN Electronic Journal %D 2019 %T Collaboration and delegation between humans and AI: An experimental investigation of the future of work %A Fügener, Andreas %A Grahl, Jörn %A Gupta, Alok %A Ketter, Wolfgang %B SSRN Electronic Journal %8 Jan-01-2019 %G eng %R 10.2139/ssrn.3368813 %0 Journal Article %J European Journal of Cancer %D 2019 %T Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark %A Brinker, Titus J. %A Hekler, Achim %A Hauschild, Axel %A Berking, Carola %A Schilling, Bastian %A Alexander Enk %A Haferkamp, Sebastian %A Karoglan, Ante %A von Kalle, Christof %A Weichenthal, Michael %A Sattler, Elke %A Schadendorf, Dirk %A Gaiser, Maria R. %A Klode, Joachim %A Jochen Sven Utikal %B European Journal of Cancer %V 111 %P 30 - 37 %8 Jan-04-2019 %G eng %R 10.1016/j.ejca.2018.12.016 %0 Conference Paper %B 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) %D 2019 %T Consider the human work experience when integrating robotics in the workplace %A Welfare, Katherine S. %A Hallowell, Matthew R. %A Shah, Julie A. %A Riek, Laurel D. %B 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) %I IEEE %C Daegu, Korea (South) %P 75 - 84 %G eng %U https://ieeexplore.ieee.org/document/8673139/http://xplorestaging.ieee.org/ielx7/8666012/8673065/08673139.pdf?arnumber=8673139 %R 10.1109/HRI.2019.8673139 %0 Journal Article %J European Journal of Cancer %D 2019 %T A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task %A Brinker, Titus J. %A Hekler, Achim %A Alexander Enk %A Klode, Joachim %A Hauschild, Axel %A Berking, Carola %A Schilling, Bastian %A Haferkamp, Sebastian %A Schadendorf, Dirk %A Fröhling, Stefan %A Jochen Sven Utikal %A von Kalle, Christof %A Ludwig-Peitsch, Wiebke %A Sirokay, Judith %A Heinzerling, Lucie %A Albrecht, Magarete %A Baratella, Katharina %A Bischof, Lena %A Chorti, Eleftheria %A Dith, Anna %A Drusio, Christina %A Giese, Nina %A Gratsias, Emmanouil %A Griewank, Klaus %A Hallasch, Sandra %A Hanhart, Zdenka %A Herz, Saskia %A Hohaus, Katja %A Jansen, Philipp %A Jockenhöfer, Finja %A Kanaki, Theodora %A Knispel, Sarah %A Leonhard, Katja %A Martaki, Anna %A Matei, Liliana %A Matull, Johanna %A Olischewski, Alexandra %A Petri, Maximilian %A Placke, Jan-Malte %A Raub, Simon %A Salva, Katrin %A Schlott, Swantje %A Sody, Elsa %A Steingrube, Nadine %A Stoffels, Ingo %A Ugurel, Selma %A Sondermann, Wiebke %A Zaremba, Anne %A Gebhardt, Christoffer %A Booken, Nina %A Christolouka, Maria %A Buder-Bakhaya, Kristina %A Bokor-Billmann, Therezia %A Alexander Enk %A Gholam, Patrick %A Hänßle, Holger %A Salzmann, Martin %A Schäfer, Sarah %A Schäkel, Knut %A Schank, Timo %A Bohne, Ann-Sophie %A Deffaa, Sophia %A Drerup, Katharina %A Egberts, Friederike %A Erkens, Anna-Sophie %A Ewald, Benjamin %A Falkvoll, Sandra %A Gerdes, Sascha %A Harde, Viola %A Hauschild, Axel %A Jost, Marion %A Kosova, Katja %A Messinger, Laetitia %A Metzner, Malte %A Morrison, Kirsten %A Motamedi, Rogina %A Pinczker, Anja %A Rosenthal, Anne %A Scheller, Natalie %A Schwarz, Thomas %A Stölzl, Dora %A Thielking, Federieke %A Tomaschewski, Elena %A Wehkamp, Ulrike %A Weichenthal, Michael %A Wiedow, Oliver %A Bär, Claudia Maria %A Bender-Säbelkampf, Sophia %A Horbrügger, Marc %A Karoglan, Ante %A Kraas, Luise %A Faulhaber, Jörg %A Geraud, Cyrill %A Guo, Ze %A Koch, Philipp %A Linke, Miriam %A Maurier, Nolwenn %A Müller, Verena %A Thomas, Benjamin %A Jochen Sven Utikal %A Alamri, Ali Saeed M. %A Baczako, Andrea %A Berking, Carola %A Betke, Matthias %A Haas, Carolin %A Hartmann, Daniela %A Heppt, Markus V. %A Kilian, Katharina %A Krammer, Sebastian %A Lapczynski, Natalie Lidia %A Mastnik, Sebastian %A Nasifoglu, Suzan %A Ruini, Cristel %A Sattler, Elke %A Schlaak, Max %A Wolff, Hans %A Achatz, Birgit %A Bergbreiter, Astrid %A Drexler, Konstantin %A Ettinger, Monika %A Haferkamp, Sebastian %A Halupczok, Anna %A Hegemann, Marie %A Dinauer, Verena %A Maagk, Maria %A Mickler, Marion %A Philipp, Biance %A Wilm, Anna %A Wittmann, Constanze %A Gesierich, Anja %A Glutsch, Valerie %A Kahlert, Katrin %A Kerstan, Andreas %A Schilling, Bastian %A Schrüfer, Philipp %B European Journal of Cancer %V 111 %P 148 - 154 %8 Jan-04-2019 %G eng %R 10.1016/j.ejca.2019.02.005 %0 Journal Article %J European Journal of Cancer %D 2019 %T Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task %A Brinker, Titus J. %A Hekler, Achim %A Alexander Enk %A Klode, Joachim %A Hauschild, Axel %A Berking, Carola %A Schilling, Bastian %A Haferkamp, Sebastian %A Schadendorf, Dirk %A Holland-Letz, Tim %A Jochen Sven Utikal %A von Kalle, Christof %A Ludwig-Peitsch, Wiebke %A Sirokay, Judith %A Heinzerling, Lucie %A Albrecht, Magarete %A Baratella, Katharina %A Bischof, Lena %A Chorti, Eleftheria %A Dith, Anna %A Drusio, Christina %A Giese, Nina %A Gratsias, Emmanouil %A Griewank, Klaus %A Hallasch, Sandra %A Hanhart, Zdenka %A Herz, Saskia %A Hohaus, Katja %A Jansen, Philipp %A Jockenhöfer, Finja %A Kanaki, Theodora %A Knispel, Sarah %A Leonhard, Katja %A Martaki, Anna %A Matei, Liliana %A Matull, Johanna %A Olischewski, Alexandra %A Petri, Maximilian %A Placke, Jan-Malte %A Raub, Simon %A Salva, Katrin %A Schlott, Swantje %A Sody, Elsa %A Steingrube, Nadine %A Stoffels, Ingo %A Ugurel, Selma %A Zaremba, Anne %A Gebhardt, Christoffer %A Booken, Nina %A Christolouka, Maria %A Buder-Bakhaya, Kristina %A Bokor-Billmann, Therezia %A Alexander Enk %A Gholam, Patrick %A Hänßle, Holger %A Salzmann, Martin %A Schäfer, Sarah %A Schäkel, Knut %A Schank, Timo %A Bohne, Ann-Sophie %A Deffaa, Sophia %A Drerup, Katharina %A Egberts, Friederike %A Erkens, Anna-Sophie %A Ewald, Benjamin %A Falkvoll, Sandra %A Gerdes, Sascha %A Harde, Viola %A Hauschild, Axel %A Jost, Marion %A Kosova, Katja %A Messinger, Laetitia %A Metzner, Malte %A Morrison, Kirsten %A Motamedi, Rogina %A Pinczker, Anja %A Rosenthal, Anne %A Scheller, Natalie %A Schwarz, Thomas %A Stölzl, Dora %A Thielking, Federieke %A Tomaschewski, Elena %A Wehkamp, Ulrike %A Weichenthal, Michael %A Wiedow, Oliver %A Bär, Claudia Maria %A Bender-Säbelkampf, Sophia %A Horbrügger, Marc %A Karoglan, Ante %A Kraas, Luise %A Faulhaber, Jörg %A Geraud, Cyrill %A Guo, Ze %A Koch, Philipp %A Linke, Miriam %A Maurier, Nolwenn %A Müller, Verena %A Thomas, Benjamin %A Jochen Sven Utikal %A Alamri, Ali Saeed M. %A Baczako, Andrea %A Berking, Carola %A Betke, Matthias %A Haas, Carolin %A Hartmann, Daniela %A Heppt, Markus V. %A Kilian, Katharina %A Krammer, Sebastian %A Lapczynski, Natalie Lidia %A Mastnik, Sebastian %A Nasifoglu, Suzan %A Ruini, Cristel %A Sattler, Elke %A Schlaak, Max %A Wolff, Hans %A Achatz, Birgit %A Bergbreiter, Astrid %A Drexler, Konstantin %A Ettinger, Monika %A Haferkamp, Sebastian %A Halupczok, Anna %A Hegemann, Marie %A Dinauer, Verena %A Maagk, Maria %A Mickler, Marion %A Philipp, Biance %A Wilm, Anna %A Wittmann, Constanze %A Gesierich, Anja %A Glutsch, Valerie %A Kahlert, Katrin %A Kerstan, Andreas %A Schilling, Bastian %A Schrüfer, Philipp %B European Journal of Cancer %V 113 %P 47 - 54 %8 Jan-05-2019 %G eng %R 10.1016/j.ejca.2019.04.001 %0 Book %D 2019 %T Designing AI futures: A symbiotic vision %A Gill, Karamjit S. %E Kravets, Alla G. %E Groumpos, Peter P. %E Shcherbakov, Maxim %E Kultsova, Marina %I Springer International Publishing %C Cham %V 1083 %P 3 - 18 %@ 978-3-030-29742-8 %G eng %R 10.1007/978-3-030-29743-5_1 %0 Journal Article %J Journal of Economic Literature %D 2019 %T Digital Economics %A Goldfarb, Avi %A Tucker, Catherine %B Journal of Economic Literature %V 57 %P 3 - 43 %8 Jan-03-2019 %G eng %N 1 %R 10.1257/jel.20171452 %0 Journal Article %J Human Behavior and Emerging Technologies %D 2019 %T Digital inequalities in the age of artificial intelligence and big data %A Lutz, Christoph %B Human Behavior and Emerging Technologies %V 1 %P 141 - 148 %8 Feb-04-2021 %G eng %N 2 %R 10.1002/hbe2.140 %0 Generic %D 2019 %T Digitalization and the future of work: Macroeconomic consequences %A Melanie Arntz %A Terry Gregory %A Ulrich Zierahn %K automation %K Digitalization %K Inequality %K unemployment %X 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. %I ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung %G eng %U http://hdl.handle.net/10419/200063 %0 Conference Paper %B 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 '19 %D 2019 %T Does automation influence career decisions among South African students? %A Mbilini, Sakhumzi N. %A le Roux, Daniel B. %A Parry, Douglas A. %Y de Villiers, Carina %Y Smuts, Hanlie %B 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 '19 %I ACM Press %C Skukuza, South AfricaNew York, New York, USA %P 1 - 10 %@ 9781450372657 %G eng %R 10.1145/335110810.1145/3351108.3351137 %0 Journal Article %J Computers in Human Behavior %D 2019 %T Does the use of synchrony and artificial intelligence in video interviews affect interview ratings and applicant attitudes? %A Suen, Hung-Yue %A Chen, Mavis Yi-Ching %A Lu, Shih-Hao %B Computers in Human Behavior %V 98 %P 93 - 101 %8 Jan-09-2019 %G eng %R 10.1016/j.chb.2019.04.012 %0 Report %D 2019 %T Is a driverless future also jobless? %A Groshen, Erica L. %I W.E. Upjohn Institute %G eng %R 10.17848/pb2019-17 %0 Journal Article %J Social Sciences %D 2019 %T Economic, Social Impacts and Operation of Smart Factories in Industry 4.0 Focusing on Simulation and Artificial Intelligence of Collaborating Robots %A Benotsmane, Rabab %A Kovács, György %A Dudás, László %B Social Sciences %V 8 %P 143 %8 Jan-05-2019 %G eng %N 5 %R 10.3390/socsci8050143 %0 Book %D 2019 %T Educating those most impacted by artificial intelligence %A Gemmell, Laura %A Wenham, Lucy %A Hauert, Sabine %E Isotani, Seiji %E Millán, Eva %E Ogan, Amy %E Hastings, Peter %E McLaren, Bruce %E Luckin, Rose %I Springer International Publishing %C Cham %V 11626 %P 344 - 349 %@ 978-3-030-23206-1 %G eng %R 10.1007/978-3-030-23207-8_63 %0 Book %D 2019 %T The emergence of complexity %A Hager, Paul %A Beckett, David %I Springer International Publishing %C Cham %@ 978-3-030-31837-6 %G eng %R 10.1007/978-3-030-31839-0 %0 Journal Article %J Computers in Human Behavior %D 2019 %T Emotional processes in human-robot interaction during brief cognitive testing %A Desideri, Lorenzo %A Ottaviani, Cristina %A Malavasi, Massimiliano %A di Marzio, Roberto %A Bonifacci, Paola %B Computers in Human Behavior %V 90 %P 331 - 342 %8 Jan-01-2019 %G eng %R 10.1016/j.chb.2018.08.013 %0 Generic %D 2019 %T Employment Transformation through Artificial Intelligence %A Dheeraj Singh, %A Geetali Tilak %7 International Journal of Applied Engineering Research %G eng %U 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 %0 Magazine Article %D 2019 %T Examples of artificial intelligence in education %A Daniel Faggella %K process automation %B emerj %G eng %U https://emerj.com/ai-sector-overviews/examples-of-artificial-intelligence-in-education/ %0 Report %D 2019 %T Exploring and developing policies to future proof Washington’s workers and businesses %A Joe Wilcox %A Lew McMurran %B Future of Work Task Force Plan of Action %I Workforce Training and Education Coordinating Board %G eng %U http://www.wtb.wa.gov/Documents/FutureofWork2018Report.pdf %0 Journal Article %J Asia-pacific Journal of Convergent Research Interchange %D 2019 %T An Extensive Review on Recent Emerging Applications of Artificial Intelligence %A Harini, B %B Asia-pacific Journal of Convergent Research Interchange %V 5 %P 79 - 88 %8 Jun-06-2021 %G eng %U http://www.apjcri.org/papers/v5n2/9.pdf %N 2 %R 10.21742/apjcri10.21742/apjcri.2019.0610.21742/apjcri.2019.06.09 %0 Conference Paper %B the 9th International ConferenceProceedings of the 9th International Conference on Learning Analytics & Knowledge - LAK19 %D 2019 %T Fairer but not fair enough on the equitability of knowledge tracing %A Doroudi, Shayan %A Brunskill, Emma %B the 9th International ConferenceProceedings of the 9th International Conference on Learning Analytics & Knowledge - LAK19 %I ACM Press %C Tempe, AZ, USANew York, New York, USA %P 335 - 339 %@ 9781450362566 %G eng %R 10.1145/3303772.3303838 %0 Book %D 2019 %T The fourth industrial revolution: Trends and impacts on the world of work %A Kim, Sang Yun %E McGrath, Simon %E Mulder, Martin %E Papier, Joy %E Suart, Rebecca %I Springer International Publishing %C Cham %P 177 - 194 %@ 978-3-319-94531-6 %G eng %R 10.1007/978-3-319-94532-3_115 %0 Report %D 2019 %T From immigrants to robots: The changing locus of substitutes for workers %A Borjas, George %A Freeman, Richard %I National Bureau of Economic Research %C Cambridge, MA %G eng %U http://www.nber.org/papers/w25438.pdf %R 10.3386/w25438 %0 Journal Article %J Journal of Information Systems and Technology Management %D 2019 %T The future digital work force: Robotic process automation (RPA) %A Madakam, Somayya %A M. Holmukhe, Rajesh %A Kumar Jaiswal, Durgesh %B Journal of Information Systems and Technology Management %V 16 %8 Apr-01-2019 %G eng %R 10.4301/S1807-1775201916001 %0 Journal Article %J JMIR Research Protocols %D 2019 %T The future of health care: Protocol for measuring the potential of task automation grounded in the national health service primary care system %A Willis, Matthew %A Duckworth, Paul %A Coulter, Angela %A Meyer, Eric T %A Osborne, Michael %B JMIR Research Protocols %V 8 %P e11232 %8 Jan-01-2019 %G eng %N 4 %R 10.2196/11232 %0 Conference Paper %B Hawaii International Conference on System Sciences (HICSS) %D 2019 %T The future of human-AI collaboration: A taxonomy of design knowledge for hybrid intelligence systems %A Dominik Dellermann %A Adrian Calma %A Nikolaus Lipusch %A Thorsten Weber %A Sascha Weigel %A Philipp Ebel %X 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. %B Hawaii International Conference on System Sciences (HICSS) %8 09/2018 %G eng %U https://www.alexandria.unisg.ch/publications/254994 %0 Report %D 2019 %T The future of the work in America %A Susan Lund %A James Manyika %A Liz Hilton Segal %A Andre Dua %A Bryan Hancock %A Scott Rutherford %A Brent Macon %K consulting reports %B McKinsey Global Institute %8 07/2019 %G eng %U https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-in-america-people-and-places-today-and-tomorrow %0 Generic %D 2019 %T The future of women at work %A Anu Madgavkar %A James Manyika %A Mekala Krishnan %A Kweilin Ellingrud %A Lareina Yee %A Jonathan Woetzel %A Michael Chui %A Vivian Hunt %A Sruti Balakrishnan %K consulting reports %V McKinsey Global Institute %8 06/2019 %G eng %U 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 %0 Magazine Article %D 2019 %T Future of work initiatives promise lots of noise and lots of activity, but to what end? %A Jeff Schwartz %A John Hagel III %A Maggie Wooll %A Kelly Monahan %B MIT Slogan Management Review %G eng %U https://sloanreview.mit.edu/article/reframing-the-future-of-work/ %0 Journal Article %J Foresight and STI Governance %D 2019 %T Getting ready for a post-work future %A Hines, Andy %B Foresight and STI Governance %V 13 %P 19 - 30 %8 Jun-03-2021 %G eng %N 1 %R 10.17323/2500-2597.2019.1.19.30 %0 Report %D 2019 %T Global commission on the future of work %A Cyril Ramaphosa %A Stefan Lofven %K government reports %B Work for a brighter future %I International Labour Organization %G eng %U https://www.ilo.org/global/topics/future-of-work/WCMS_569528/lang--en/index.htm %0 Magazine Article %D 2019 %T Google’s head of translation on fighting bias in language and why AI loves religious texts %A James Vincent %B The Verge %G eng %U https://www.theverge.com/2019/1/30/18195909/google-translate-ai-machine-learning-bias-religion-macduff-hughes-interview %0 Conference Proceedings %B FCA Conference on Governance in Banking %D 2019 %T The governance of artificial intelligence %A James Proudman %K AI use cases %B FCA Conference on Governance in Banking %8 05/2019 %G eng %U https://www.bankofengland.co.uk/-/media/boe/files/speech/2019/managing-machines-the-governance-of-artificial-intelligence-speech-by-james-proudman %0 Journal Article %J Digital Policy, Regulation and Governance %D 2019 %T Governance of artificial intelligence and personal health information %A Winter, Jenifer Sunrise %A Davidson, Elizabeth %B Digital Policy, Regulation and Governance %V 21 %P 280 - 290 %8 Jan-05-2020 %G eng %N 3 %R 10.1108/DPRG-08-2018-0048 %0 Journal Article %J Postdigital Science and Education %D 2019 %T Higher education in the age of Artificial Intelligence %A Sudlow, Brian %B Postdigital Science and Education %V 1 %P 236 - 239 %8 Jan-04-2019 %G eng %N 1 %R 10.1007/s42438-018-0005-8 %0 Magazine Article %D 2019 %T How 5 data dynamos do their jobs %A Lindsey Rogers Cook %B Times Insider %G eng %U https://www.nytimes.com/2019/06/12/reader-center/data-reporting-spreadsheets.html %0 Book %D 2019 %T How artificial intelligence and machine learning can impact market design %A Agrawal, Ajay %A Gans, Joshua %A Goldfarb, Avi %I University of Chicago Press %P 567 - 586 %@ 9780226613338 %G eng %R 10.7208/chicago/9780226613475.003.0023 %0 Magazine Article %D 2019 %T How big data is changing the job market %A Editorial Team %B insideBIGDATA %G eng %U 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 %0 Magazine Article %D 2019 %T How frightened should we be of AI ? %A Tad Friend %B The New Yorker %G eng %U https://www.newyorker.com/books/double-take/sunday-reading-the-rise-of-artificial-intelligence %0 Conference Paper %B Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences %D 2019 %T How May I Help You? – State of the Art and Open Research Questions for Chatbots at the Digital Workplace %A Meyer von Wolff, Raphael %A Hobert, Sebastian %A Schumann, Matthias %Y Bui, Tung %B Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences %I Hawaii International Conference on System Sciences %@ 978-0-9981331-2-6 %G eng %R 10.24251/HICSS.2019.013 %0 Magazine Article %D 2019 %T How one scientist coped when AI beat him at his life’s work %A Sigal Samuel %B Vox %G eng %U https://www.vox.com/future-perfect/2019/2/15/18226493/deepmind-alphafold-artificial-intelligence-protein-folding %0 Conference Paper %B 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC)2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC) %D 2019 %T How Smart is your Manufacturing? Build Smarter with AI %A Mcmahon, Mike %A Mumper, Dale %A Ihaza, Mitsuko %A Farrar, Dominic %B 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC)2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC) %I IEEE %C Milwaukee, WI, USA %P 55 - 60 %@ 978-1-7281-2607-4 %G eng %R 10.1109/COMPSAC.2019.10183 %0 Conference Proceedings %B Electronic Government %D 2019 %T How to Streamline AI Application in Government? A Case Study on Citizen Participation in Germany %A Balta, Dian %A Kuhn, Peter %A Sellami, Mahdi %A Kulus, Daniel %A Lieven, Claudius %A Krcmar, Helmut %E Lindgren, Ida %E Janssen, Marijn %E Lee, Habin %E Polini, Andrea %E Rodríguez Bolívar, Manuel Pedro %E Scholl, Hans Jochen %E Tambouris, Efthimios %X 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. %B Electronic Government %I Springer International Publishing %C Cham %V Lecture Notes in Computer Science 11685 %P 233-247 %@ 978-3-030-27324-8 %G eng %R 10.1007/978-3-030-27325-5 %0 Journal Article %J BMC Health Services Research %D 2019 %T Human resource technology disruptions and their implications for human resources management in healthcare organizations %A Tursunbayeva, Aizhan %B BMC Health Services Research %V 19 %8 Jan-12-2019 %G eng %N 1 %R 10.1186/s12913-019-4068-3 %0 Journal Article %J Business & Information Systems Engineering %D 2019 %T Hybrid Intelligence %A Dellermann, Dominik %A Ebel, Philipp %A Söllner, Matthias %A Leimeister, Jan Marco %B Business & Information Systems Engineering %V 61 %P 637 - 643 %8 Jan-10-2019 %G eng %N 5 %R 10.1007/s12599-019-00595-2 %0 Conference Paper %D 2019 %T IBM Talent Management Solutions The role of AI in mitigating bias to enhance diversity and inclusion %A Haiyan Zhang %A Sheri Feinzi %A Louise Raisbec %A Iain McCombe %A Nigel Guenol %A Jenny Montalt %A Kimberley Messe %8 03/2019 %G eng %U https://www.ibm.com/downloads/cas/2DZELQ4O %0 Generic %D 2019 %T The impact of automation technologies for employment in Northern Ireland %A Lisa Wilson %A Paul Mac Flynn %K economics of automation %I Nevin Economic Research Institute %G eng %U https://www.nerinstitute.net/research/the-future-of-work-the-impact-of-automation-techno-1/ %0 Journal Article %J Emerald Open Research %D 2019 %T The impact of emerging technologies on work: a review of the evidence and implications for the human resource function %A Parry, Emma %A Battista, Valentina %B Emerald Open Research %V 1 %P 5 %8 Jan-01-2019 %G eng %R 10.12688/emeraldopenres.12907.1 %0 Conference Paper %B 2019 14th Iberian Conference on Information Systems and Technologies (CISTI) %D 2019 %T Impacts of Artificial Intelligence on Public Administration: A Systematic Literature Review %A João Reis %A Paula Espírito Santo %A Lisbon, Portugal %A Nuno Melão %B 2019 14th Iberian Conference on Information Systems and Technologies (CISTI) %@ 978-989-98434-9-3 %G eng %U https://ieeexplore.ieee.org/document/8760778 %0 Conference Proceedings %B Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52) %D 2019 %T Impacts of machine learning on work %A Kevin Crowston %A Bolici, Francesco %K artificial intelligence %K automation %K machine learning %K work design %X

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.

%B Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52) %C Wailea, HI %G eng %U http://hdl.handle.net/10125/60031 %R 10.24251/HICSS.2019.719 %> https://waim.network/sites/crowston.syr.edu/files/Impacts_of_machine_learning_on_work__revision_.pdf %0 Journal Article %J Business Information Review %D 2019 %T In the age of the smart artificial intelligence: AI’s dual capacities for automating and informating work %A Jarrahi, Mohammad Hossein %K Algorithmic management %K artificial intelligence %K augmentation %K automating %K informating %K intelligent machine %X 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. %B Business Information Review %I Sage %P 026638211988399 %8 Dec-10-2020 %G eng %U https://journals.sagepub.com/doi/abs/10.1177/0266382119883999 %R 10.1177/0266382119883999 %> 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 %0 Conference Paper %B the 2019 AAAI/ACM ConferenceProceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society - AIES '19 %D 2019 %T Inferring work task automatability from AI expert evidence %A Duckworth, Paul %A Graham, Logan %A Osborne, Michael %Y Conitzer, Vincent %Y Hadfield, Gillian %Y Vallor, Shannon %B the 2019 AAAI/ACM ConferenceProceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society - AIES '19 %I ACM Press %C Honolulu, HI, USANew York, New York, USA %P 485 - 491 %@ 9781450363242 %G eng %R 10.1145/330661810.1145/3306618.3314247 %0 Generic %D 2019 %T Integrating ethical values and economic value to steer progress in Artificial Intelligenc %A Anton Korinek %K ethics %B National bureau of economic research %8 08/2019 %G eng %U https://www.nber.org/papers/w26130 %0 Journal Article %J Journal of Management Inquiry %D 2019 %T Introduction: The Future of Jobs in an Increasingly Autonomous Economy %A Choi, David Y. %A Kang, Jae Hyeung %B Journal of Management Inquiry %V 28 %P 298 - 299 %8 Jun-07-2021 %G eng %N 3 %R 10.1177/1056492619827373 %0 Journal Article %J Journal of Industrial and Business Economics %D 2019 %T Labor, technology and work organization: An introduction to the forum %A Cirillo, Valeria %A Molero Zayas, José %B Journal of Industrial and Business Economics %V 46 %P 313 - 321 %8 Jan-09-2019 %G eng %N 3 %R 10.1007/s40812-019-00126-w %0 Journal Article %J AI & SOCIETY %D 2019 %T A machine is cheaper than a human for the same task %A Pereira, Luís Moniz %B AI & SOCIETY %8 Feb-01-2019 %G eng %R 10.1007/s00146-018-0874-0 %0 Journal Article %J Pediatric Radiology %D 2019 %T Machine learning concepts, concerns and opportunities for a pediatric radiologist %A Moore, Michael M. %A Slonimsky, Einat %A Long, Aaron D. %A Sze, Raymond W. %A Iyer, Ramesh S. %B Pediatric Radiology %V 49 %P 509 - 516 %8 Jan-04-2019 %G eng %N 4 %R 10.1007/s00247-018-4277-7 %0 Book Section %B researchgate.net %D 2019 %T Machine learning for clinical psychology and clinical neuroscience %A Marc N. Countanche %A Lauren S. Hallion %X 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. %B researchgate.net %G eng %U https://www.researchgate.net/publication/331000572_Machine_Learning_for_Clinical_Psychology_and_Clinical_Neuroscience %0 Conference Paper %B Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences %D 2019 %T Machine learning in Artificial Intelligence: Towards a common understanding %A Kühl, Niklas %A Goutier, Marc %A Hirt, Robin %A Satzger, Gerhard %Y Bui, Tung %B Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences %I Hawaii International Conference on System Sciences %G eng %R 10.24251/HICSS.2019.630 %0 Journal Article %J JCO Clinical Cancer Informatics %D 2019 %T A Machine Learning Platform to Optimize the Translation of Personalized Network Models to the Clinic %A Salvucci, Manuela %A Rahman, Arman %A Resler, Alexa J. %A Udupi, Girish M. %A McNamara, Deborah A. %A Kay, Elaine W. %A Laurent-Puig, Pierre %A Longley, Daniel B. %A Johnston, Patrick G. %A Lawler, Mark %A Wilson, Richard %A Salto-Tellez, Manuel %A Van Schaeybroeck, Sandra %A Rafferty, Mairin %A Gallagher, William M. %A Rehm, Markus %A Prehn, Jochen H.M. %B JCO Clinical Cancer Informatics %P 1 - 17 %8 Jan-04-2019 %G eng %N 3 %R 10.1200/CCI.18.00056 %0 Generic %D 2019 %T Managing Machines: The governance of artificial intelligence %A James Proudman %B FCA Conference on Governance in Banking %G eng %U https://www.bankofengland.co.uk/speech/2019/james-proudman-speech-at-fca-conference-on-governance-in-banking-london %0 Journal Article %J Computers in Human Behavior %D 2019 %T Marketing AI recruitment: The next phase in job application and selection %A van Esch, Patrick %A Black, J. Stewart %A Ferolie, Joseph %B Computers in Human Behavior %V 90 %P 215 - 222 %8 Jan-01-2019 %G eng %R 10.1016/j.chb.2018.09.009 %0 Journal Article %J Science and Engineering Ethics %D 2019 %T Massive technological unemployment without redistribution: A case for cautious optimism %A Chomanski, Bartek %B Science and Engineering Ethics %V 25 %P 1389 - 1407 %8 Jan-10-2019 %G eng %N 5 %R 10.1007/s11948-018-0070-0 %0 Journal Article %D 2019 %T Mitigating bias in algorithmic employment screening: Evaluating claims and practices %A Manish Raghavan %A Solon Barocas %A Jon KleinbergKaren Levy %K social power of algorithms %X

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’ for-mulation of “bias” 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.

%G eng %U https://www.researchgate.net/publication/333971698_Mitigating_Bias_in_Algorithmic_Employment_Screening_Evaluating_Claims_and_Practices %0 Journal Article %J Tourism Management %D 2019 %T The moderating roles of perceived organizational support and competitive psychological climate %A Li, Jun (Justin) %A Bonn, Mark A. %A Ye, Ben Haobin %B Tourism Management %V 73 %P 172 - 181 %8 Jan-08-2019 %G eng %R 10.1016/j.tourman.2019.02.006 %0 Book %D 2019 %T Moral reasoning at work automation and ethics %A Kvalnes, Øyvind %A Kvalnes, Øyvind %I Springer International Publishing %C Cham %P 69 - 77 %@ 978-3-030-15190-4 %G eng %U 10.1007/978-3-030-15191-1_8 %0 Journal Article %J Computers in Human Behavior %D 2019 %T Negotiated and reciprocal exchange structures in human-agent cooperation %A Chiou, Erin K. %A Lee, John D. %A Su, Tianshuo %B Computers in Human Behavior %V 90 %P 288 - 297 %8 Jan-01-2019 %G eng %R 10.1016/j.chb.2018.08.012 %0 Journal Article %J Journal of Management Inquiry %D 2019 %T Net job creation in an increasingly autonomous economy: The challenge of a generation %A Choi, David Y. %A Kang, Jae Hyeung %B Journal of Management Inquiry %V 28 %P 300 - 305 %8 Jun-07-2021 %G eng %N 3 %R 10.1177/1056492619827372 %0 Journal Article %J Journal of Pediatric Nursing %D 2019 %T Nurses' Views on the Potential Use of Robots in the Pediatric Unit %A Liang, Hwey-Fang %A Wu, Kuang-Ming %A Weng, Cheng-Hsing %A Hsieh, Hui-Wen %B Journal of Pediatric Nursing %V 47 %P e58 - e64 %8 Jan-07-2019 %G eng %R 10.1016/j.pedn.2019.04.027 %0 Journal Article %J npj Digital Medicine %D 2019 %T Physician perspectives on integration of artificial intelligence into diagnostic pathology %A Sarwar, Shihab %A Dent, Anglin %A Faust, Kevin %A Richer, Maxime %A Djuric, Ugljesa %A Van Ommeren, Randy %A Diamandis, Phedias %B npj Digital Medicine %V 2 %8 Jan-12-2019 %G eng %N 1 %R 10.1038/s41746-019-0106-0 %0 Journal Article %J California Management Review %D 2019 %T Pooling knowledge through artificial swarm intelligence to improve business decision making %A Metcalf, Lynn %A Askay, David A. %A Rosenberg, Louis B. %B California Management Review %V 61 %P 84 - 109 %8 Sep-08-2019 %G eng %N 4 %R 10.1177/0008125619862256 %0 Journal Article %J Future Healthcare Journal %D 2019 %T The potential for artificial intelligence in healthcare %A Davenport, Thomas %A Kalakota, Ravi %B Future Healthcare Journal %V 6 %P 94 - 98 %8 Jan-06-2020 %G eng %N 2 %R 10.7861/futurehosp.6-2-94 %0 Journal Article %J Social Forces %D 2019 %T Precarious lives: Job insecurity and well-being in rich democracies %A Pugh, Allison J %B Social Forces %V 97 %P e1 - e3 %8 Jun-04-2019 %G eng %N 4 %R 10.1093/sf/soz022 %0 Journal Article %J European Journal of Radiology %D 2019 %T The present and future of deep learning in radiology %A Saba, Luca %A Biswas, Mainak %A Kuppili, Venkatanareshbabu %A Cuadrado Godia, Elisa %A Suri, Harman S. %A Edla, Damodar Reddy %A Omerzu, Tomaž %A Laird, John R. %A Khanna, Narendra N. %A Mavrogeni, Sophie %A Protogerou, Athanasios %A Sfikakis, Petros P. %A Viswanathan, Vijay %A Kitas, George D. %A Nicolaides, Andrew %A Gupta, Ajay %A Suri, Jasjit S. %B European Journal of Radiology %V 114 %P 14 - 24 %8 Jan-05-2019 %G eng %U https://doi.org/10.1016/j.ejrad.2019.02.038 %R 10.1016/j.ejrad.2019.02.038 %0 Journal Article %J Journal of Organization Design %D 2019 %T Primer on artificial intelligence and robotics %A Raj, Manav %A Seamans, Robert %B Journal of Organization Design %V 8 %8 Jan-12-2019 %G eng %N 1 %R 10.1186/s41469-019-0050-0 %0 Journal Article %J JAMA %D 2019 %T Questions for artificial intelligence in health care %A Maddox, Thomas M. %A Rumsfeld, John S. %A Payne, Philip R. O. %B JAMA %V 321 %P 31 %8 Jan-01-2019 %G eng %N 1 %R 10.1001/jama.2018.18932 %0 Journal Article %J Radiology: Artificial Intelligence %D 2019 %T The Rebirth of CAD: How Is Modern AI Different from the CAD We Know? %A Oakden-Rayner, Luke %B Radiology: Artificial Intelligence %V 1 %P e180089 %8 Jan-05-2019 %G eng %N 3 %R 10.1148/ryai.2019180089 %0 Thesis %B Department of Management and Engineering %D 2019 %T Recruiters just wanna have AI? %A Hannimari Savola %A Bijona Troqe %B Department of Management and Engineering %7 Spring semester 2019 %G eng %U https://liu.diva-portal.org/smash/get/diva2:1333711/FULLTEXT01.pdf %0 Generic %D 2019 %T A Review of the Social Impacts and Ethical Implications of Artificial Intelligence %A Alexa Hagerty %A Igor Rubinov %K ethics %I Global AI Ethics %G eng %U https://arxiv.org/ftp/arxiv/papers/1907/1907.07892.pdf %0 Journal Article %J Öneri Dergisi %D 2019 %T The rise of robots! Effects on employment and income %A ÖZCAN, Rasim %B Öneri Dergisi %P 1 - 17 %8 Jun-02-2019 %G eng %R 10.14783/maruoneri.vi.522005 %0 Journal Article %J Trends in Cancer %D 2019 %T Rise of the Machines: Advances in Deep Learning for Cancer Diagnosis %A Levine, Adrian B. %A Schlosser, Colin %A Grewal, Jasleen %A Coope, Robin %A Jones, Steve J.M. %A Yip, Stephen %B Trends in Cancer %V 5 %P 157 - 169 %8 Jan-03-2019 %G eng %N 3 %R 10.1016/j.trecan.2019.02.002 %0 Conference Paper %B Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences %D 2019 %T The roles of initiated and received task interdependence %A Berntzen, Marthe %A Wong, Sut I %Y Bui, Tung %B Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences %I Hawaii International Conference on System Sciences %G eng %R 10.24251/HICSS.2019.119 %0 Journal Article %J Proceedings of the National Academy of Sciences %D 2019 %T Scaling up analogical innovation with crowds and AI %A Kittur, Aniket %A Yu, Lixiu %A Hope, Tom %A Chan, Joel %A Lifshitz-Assaf, Hila %A Gilon, Karni %A Ng, Felicia %A Kraut, Robert E. %A Shahaf, Dafna %B Proceedings of the National Academy of Sciences %V 116 %P 1870-1877 %G eng %N 6 %R 10.1073/pnas.1807185116 %0 Journal Article %J On the Horizon %D 2019 %T The solution lies in education: Artificial intelligence & the skills gap %A Chrisinger, David %B On the Horizon %V 27 %P 1 - 4 %8 Nov-03-2019 %G eng %N 1 %R 10.1108/OTH-03-2019-096 %0 Book %D 2019 %T Steps toward a scaffolding design framework %A Correia, António %A Jameel, Shoaib %A Paredes, Hugo %A Fonseca, Benjamim %A Schneider, Daniel %E Khan, Vassillis-Javed %E Papangelis, Konstantinos %E Lykourentzou, Ioanna %E Markopoulos, Panos %I Springer International Publishing %C Cham %P 149 - 161 %@ 978-3-030-12333-8 %G eng %R 10.1007/978-3-030-12334-5_5 %0 Journal Article %J International Journal of Research and Analytical Review %D 2019 %T A study of artificial intelligence and it's role on human resource management %A Vivek V. Yawalkar %B International Journal of Research and Analytical Review %V 6 %G eng %U https://www.researchgate.net/publication/331596981_A_Study_of_Artificial_Intelligence_and_its_role_in_Human_Resource_Management %N 1 %0 Journal Article %D 2019 %T Synthesis of Strategies for Robotic Process Automation %A Simone Agostinelli %G eng %U http://ceur-ws.org/Vol-2400/paper-53.pdf %N DIAG, Sapienza University of Rome, Italy %0 Book %D 2019 %T Technology and Work Worth Doing (Not Jobs) Post-AlphaGo: A World-Building Workshop on the Future of Artificial Intelligence %A Pendleton-Jullian, Ann %A Lempert, Robert %I RAND Corporation %G eng %R 10.7249/CF398 %0 Report %D 2019 %T Ten ways the precautionary principle undermines progress in artificial intelligence %A Daniel Castro %A Michael McLaughlin %K consulting reports %B Information Technology & Innovation Foundation %8 02/2019 %G eng %U https://itif.org/publications/2019/02/04/ten-ways-precautionary-principle-undermines-progress-artificial-intelligence %0 Journal Article %D 2019 %T There is no general AI: Why Turing machines cannot pass the Turing test %A Jobst Landgrebe %G eng %U https://arxiv.org/abs/1906.05833 %0 Journal Article %J Journal of Industrial and Business Economics %D 2019 %T Is this time different? A note on automation and labour in the fourth industrial revolution %A Marengo, Luigi %K economics of automation %B Journal of Industrial and Business Economics %V 46 %P 323 - 331 %8 Jan-09-2019 %G eng %N 3 %R 10.1007/s40812-019-00123-z %0 Journal Article %J Research Policy %D 2019 %T Is this time different? How digitalization influences job creation and destruction %A Balsmeier, Benjamin %A Woerter, Martin %B Research Policy %V 48 %P 103765 %8 Jan-10-2019 %G eng %N 8 %R 10.1016/j.respol.2019.03.010 %0 Journal Article %J International Journal of Sociology and Social Policy %D 2019 %T “This time may be a little different” – exploring the Finnish view on the future of work %A Pulkka, Ville-Veikko %B International Journal of Sociology and Social Policy %V 39 %P 22 - 37 %8 Nov-03-2019 %G eng %N 1/2 %R 10.1108/IJSSP-05-2018-0070 %0 Book %D 2019 %T Toward a conceptual framework for understanding AI action and legal reaction %A Dahya, Raheena %A Morris, Alexis %E Meurs, Marie-Jean %E Rudzicz, Frank %I Springer International Publishing %C Cham %V 11489 %P 453 - 459 %@ 978-3-030-18304-2 %G eng %R 10.1007/978-3-030-18305-9_44 %0 Journal Article %J Proceedings of the National Academy of Sciences %D 2019 %T Toward understanding the impact of artificial intelligence on labor %A Frank, Morgan R %A Autor, David %A Bessen, James E %A Brynjolfsson, Erik %A Cebrian, Manuel %A Deming, David J %A Feldman, Maryann %A Groh, Matthew %A Lobo, José %A Moro, Esteban %A Wang, Dashun %A Youn, Hyejin %A Rahwan, Iyad %X

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–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.

%B Proceedings of the National Academy of Sciences %V 116 %P 6531–6539 %8 apr %G eng %U http://www.pnas.org/lookup/doi/10.1073/pnas.1900949116 %R 10.1073/pnas.1900949116 %0 Journal Article %J Economics, Management, and Financial Markets %D 2019 %T Towards a smart automated society: Cognitive technologies, knowledge production, and economic growth %A Mitchell Udell %A Vojtech Stehel %A Tomas Kliestik %A Jana Kliestikova %A Pavol Durana %B Economics, Management, and Financial Markets %V 14 %P 44 %8 Jan-01-2019 %G eng %N 1 %R 10.22381/EMFM14120195 %0 Report %D 2019 %T Towards an AI economy that works for all %A Stephen Herzenberg %A John Alic %K ethics %B Keystone Research Center Future of Work Project sponsored by The Heinz Endowments %8 02/2019 %G eng %U https://www.keystoneresearch.org/sites/default/files/FOW_TowardAIEconomyForAllFinalEdit.pdf %0 Journal Article %J European Journal of Risk Regulation %D 2019 %T Towards intelligent regulation of Artificial Intelligence %A BUITEN, Miriam C %B European Journal of Risk Regulation %V 10 %P 41 - 59 %8 Jan-03-2019 %G eng %N 1 %R 10.1017/err.2019.8 %0 Journal Article %J Government Information Quarterly %D 2019 %T Transforming the communication between citizens and government through AI-guided chatbots %A Androutsopoulou, Aggeliki %A Karacapilidis, Nikos %A Loukis, Euripidis %A Charalabidis, Yannis %B Government Information Quarterly %V 36 %P 358 - 367 %8 Jan-04-2019 %G eng %U https://doi.org/10.1016/j.giq.2018.10.001 %N 2 %R 10.1016/j.giq.2018.10.001 %0 Journal Article %J Big Data & Society %D 2019 %T Unsupervised by any other name: Hidden layers of knowledge production in artificial intelligence on social media %A Bechmann, Anja %A Bowker, Geoffrey C %B Big Data & Society %V 6 %P 205395171881956 %8 May-01-2019 %G eng %N 1 %R 10.1177/2053951718819569 %0 Journal Article %J Water %D 2019 %T Use of Artificial Intelligence to Improve Resilience and Preparedness Against Adverse Flood Events %A Saravi, Sara %A Kalawsky, Roy %A Joannou, Demetrios %A Rivas Casado, Monica %A Fu, Guangtao %A Meng, Fanlin %B Water %V 11 %P 973 %8 Jan-05-2019 %G eng %N 5 %R 10.3390/w11050973 %0 Journal Article %J American Journal of Health-System Pharmacy %D 2019 %T Using artificial intelligence in health-system pharmacy practice: Finding new patterns that matter %A Flynn, Allen %B American Journal of Health-System Pharmacy %V 76 %P 622 - 627 %8 May-04-2020 %G eng %N 9 %R 10.1093/ajhp/zxz018 %0 Generic %D 2019 %T What happens when the jobs disappear? %A Andrew Yang %V The Superintendent journal %G eng %U https://super.journalxr.com/journal/index.php/TSJ %N Vol 1 No 2 (2019) %0 Journal Article %J Work, Employment and Society %D 2019 %T Why artificial intelligence will not outsmart complex knowledge work %A Pettersen, Lene %B Work, Employment and Society %V 33 %P 1058 - 1067 %8 Jan-12-2019 %G eng %N 6 %R 10.1177/0950017018817489 %0 Conference Paper %B 8th International Conference on Data Science, Technology and ApplicationsProceedings of the 8th International Conference on Data Science, Technology and Applications %D 2019 %T Why small data holds the key to the future of artificial intelligence %A Greco, Ciro %A Polonioli, Andrea %A Tagliabue, Jacopo %B 8th International Conference on Data Science, Technology and ApplicationsProceedings of the 8th International Conference on Data Science, Technology and Applications %I SCITEPRESS - Science and Technology Publications %C Prague, Czech Republic %P 340 - 347 %G eng %R 10.5220/0007956203400347 %0 Journal Article %J Social research: An international quarterly %D 2019 %T Why we are failing to understand the societal impact of artificial intelligence %A Lorena Jaume-Palasi %B Social research: An international quarterly %V 86 %P pp. 477-498 %G eng %U https://muse.jhu.edu/article/732186 %6 2 %0 Journal Article %J Radiology: Artificial Intelligence %D 2019 %T Will Artificial Intelligence Replace Radiologists? %A Langlotz, Curtis P. %B Radiology: Artificial Intelligence %V 1 %P e190058 %8 Jan-05-2019 %G eng %N 3 %R 10.1148/ryai.2019190058 %0 Journal Article %J Network Intelligence Studies %D 2019 %T Will artificial intelligence take over human resources recruitment and selection? %A Bilal Hmoud %A Varallya Laszlo %K artificial intelligence %K human resources information systems %K recruitment and selection %B Network Intelligence Studies %V VII %G eng %U https://ideas.repec.org/a/cmj/networ/y2019i13p21-30.html %N 13 %0 Journal Article %J The British Journal of Radiology %D 2019 %T Will machine learning end the viability of radiology as a thriving medical specialty? %A Chan, Stephen %A Siegel, Eliot L %B The British Journal of Radiology %V 92 %P 20180416 %8 Jan-02-2019 %G eng %N 1094 %R 10.1259/bjr.20180416 %0 Web Page %D 2018 %T 10 examples of Artificial Intelligence you’re using in daily life %A Rachit Agarwal %B Beebom %8 09/2018 %G eng %U https://beebom.com/examples-of-artificial-intelligence/ %N Smart Gadgets %0 Web Page %D 2018 %T 16 examples of Artificial Intelligence in your everyday life %A The Manifest %B Medium %8 10/2018 %G eng %U https://medium.com/@the_manifest/16-examples-of-artificial-intelligence-ai-in-your-everyday-life-655b2e6a49de %0 Web Page %D 2018 %T 7 job skills of the future (That AI's and robots can't do better than humans) %A Bernard Marr %B Forbes %7 Enterprise Tech %8 08/2018 %G eng %U 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 %0 Newspaper Article %B forbes %D 2018 %T 7 things I learned from building an AI chatbot for leadership development %A Kevin Kruse %B forbes %G eng %U https://www.forbes.com/sites/kevinkruse/2018/10/15/ai-chatbot-leadership-development-training-hr/#206492515ff0 %0 Newspaper Article %B forbes %D 2018 %T 7 things I learned from building an AI chatbot for leadership development %A Kevin Kruse %B forbes %G eng %U https://www.forbes.com/sites/kevinkruse/2018/10/15/ai-chatbot-leadership-development-training-hr/#206492515ff0 %0 Journal Article %J data-efficient ML %D 2018 %T Accounting for the neglected dimensions of AI progress %A Fernando Martine-Plumed %A Shahar Avin %A Miles Brundage %A Allan Dafoe %A Sean O hEigeartaigh %A José Hernández-Orallo %B data-efficient ML %G eng %U https://arxiv.org/abs/1806.00610 %0 Book %B Proceedings of the 1st International Conference on Intelligent Human Systems Integration %D 2018 %T Advances in intelligent systems and computing %A Advances in Intelligent Systems and Computing 722 Waldemar Karwowski %B Proceedings of the 1st International Conference on Intelligent Human Systems Integration %G eng %U https://link.springer.com/book/10.1007/978-3-030-11051-2?page=2 %0 Journal Article %J MATEC Web of Conferences %D 2018 %T Advances in the development of a cognitive user interface %A Jokisch, Oliver %A Huber, Markus %E Ronzhin, A. %E Shishlakov, V. %B MATEC Web of Conferences %V 161 %P 01003 %8 Jan-01-2018 %G eng %U https://www.matec-conferences.org/10.1051/matecconf/201816101003https://www.matec-conferences.org/10.1051/matecconf/201816101003/pdf %R 10.1051/matecconf/201816101003 %0 Web Page %D 2018 %T A.I. And big data could power a new war on poverty %A Elisabeth a. Mason %8 01/2018 %G eng %U https://www.nytimes.com/2018/01/01/opinion/ai-and-big-data-could-power-a-new-war-on-poverty.html %0 Report %D 2018 %T AI and the Economy %A Furman, Jason %A Seamans, Robert %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w24689 %0 Conference Paper %B 21st DMI: Academic Design Management Conference %D 2018 %T AI Assistants as Non-human Actors in Service Design %A TiTitta Jylkastta Jylkäs %A Mikko Äijälä %A Tytti Vuorikari %A Vésaal Rajab %B 21st DMI: Academic Design Management Conference %G eng %U 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&_ %0 Magazine Article %D 2018 %T AI: Augmentation, more so than automation %A Steven Miller %B Asian Management Insights %I Singapore Management University %G eng %U https://cmp.smu.edu.sg/ami/all %0 Web Page %D 2018 %T AI Could Provide Moment-by-Moment Nursing for a Hospital’s Sickest Patients %A Behnood Gholami %A Wassim M. Haddad %A James M. Bailey %B spectrum.ieee.org %G eng %U https://globaltechnologies.ca/ai-could-provide-moment-by-moment-nursing-for-a-hospitals-sickest-patients/ %0 Journal Article %J venturebeat %D 2018 %T AI is coming after highly skilled jobs, and it’s meeting resistance %A Sascha Eder %K AI %B venturebeat %G eng %U https://venturebeat.com/2018/03/04/ai-is-coming-after-highly-skilled-jobs-and-its-meeting-resistance/ %0 Conference Paper %B the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES '18 %D 2018 %T AI risk mitigation through democratic governance %A Garvey, Colin %Y Furman, Jason %Y Marchant, Gary %Y Price, Huw %Y Rossi, Francesca %B the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES '18 %I ACM Press %C New Orleans, LA, USANew York, New York, USA %P 366 - 367 %@ 9781450360128 %G eng %R 10.1145/3278721.3278801 %0 Web Page %D 2018 %T AI stumbles in the spotlight %A Kaveh Waddell %G eng %U https://www.axios.com/artificial-intelligence-mistakes-limitations-amazon-ibm-14014597-03e9-43e3-b224-a91205a232c1.html %0 Journal Article %J Journal of Affective Disorders %D 2018 %T Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review %A Lee, Yena %A Ragguett, Renee-Marie %A Mansur, Rodrigo B. %A Boutilier, Justin J. %A Rosenblat, Joshua D. %A Trevizol, Alisson %A Brietzke, Elisa %A Lin, Kangguang %A Pan, Zihang %A Subramaniapillai, Mehala %A Chan, Timothy C.Y. %A Fus, Dominika %A Park, Caroline %A Musial, Natalie %A Zuckerman, Hannah %A Chen, Vincent Chin-Hung %A Ho, Roger %A Rong, Carola %A McIntyre, Roger S. %B Journal of Affective Disorders %V 241 %P 519-532 %G eng %R 10.1016/j.jad.2018.08.073 %0 Thesis %B International Design Business Management %D 2018 %T Archetypes of artificial intelligence utilization %A Selim Saukkomaa %B International Design Business Management %G eng %U https://aaltodoc.aalto.fi/handle/123456789/33983 %0 Journal Article %J Radiology %D 2018 %T Are You Working with AI or Being Replaced by AI? %A Bluemke, David A. %B Radiology %V 287 %P 365 - 366 %8 Jan-05-2018 %G eng %N 2 %R 10.1148/radiol.2018184007 %0 Conference Paper %D 2018 %T Artificial General Intelligence %A Matthew Iklé %A Arthur Franz %A Rafal Rzepka %A Ben Goertzel %G eng %U https://ivizlab.org/wp-content/uploads/sites/2/2018/09/TurnerDiPaola_2018_ArtificialGeneralIntelligence.pdf %0 Journal Article %J International Journal of Computer Science and Network Security %D 2018 %T Artificial Intelligence: A Case Study on Risk Mitigation %A Ahmed AL-Gindy %K AI application %K artificial intelligence %K Risk mitigation %X 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. %B International Journal of Computer Science and Network Security %V 18 %P 9-12 %8 04/2018 %G eng %N 4 %0 Report %D 2018 %T Artificial intelligence and privacy in the fourth industrial revolution %A Sarah W. Denton %A Eleonore Pauwels %B synenergene %I Institute for Philosophy & Public Policy %G eng %U https://www.wilsoncenter.org/sites/default/files/ai_and_privacy.pdf %0 Journal Article %J Technology in Society %D 2018 %T Artificial intelligence and sports journalism: Is it a sweeping change? %A Yair Galily %B Technology in Society %G eng %R 10.1016/j.techsoc.2018.03.001 %0 Journal Article %J Business Horizons %D 2018 %T Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making %A Mohammad Hossein Jarrahi %K Analytical and intuitive decision making %K artificial intelligence %K Human augmentation %K Human-machine symbiosis %K Organization decision making %X 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' 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. %B Business Horizons %7 586 %I Elsevier %V 61 %G eng %& 577 %R 10.1016/j.bushor.2018.03.007 %0 Journal Article %J Business Horizons %D 2018 %T Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making %A Jarrahi, Mohammad Hossein %B Business Horizons %V 61 %P 577 - 586 %8 Jan-07-2018 %G eng %N 4 %R 10.1016/j.bushor.2018.03.007 %0 Conference Paper %B 14th IFIP WG 12.5 International Conference, AIAI 2018 %D 2018 %T Artificial Intelligence Applications and Innovations %A Lazaros Iliadis %A Ilias Maglogiannis %A Vassilis Plagianakos %B 14th IFIP WG 12.5 International Conference, AIAI 2018 %G eng %U https://www.springer.com/gp/book/9783319920153 %0 Journal Article %D 2018 %T Artificial intelligence can transform the economy %A Erik Brynjolfsson %A Xiang Hui %A Meng Liu %8 09/2018 %G eng %U https://www.washingtonpost.com/opinions/artificial-intelligence-can-transform-the-economy/2018/09/18/50c9c9c8-bab8-11e8-bdc0-90f81cc58c5d_story.html %0 Book %D 2018 %T Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide %A Vassilis Galanos %E Kreps, David %E Ess, Charles %E Leenen, Louise %E Kimppa, Kai %I Springer International Publishing %C Cham %V 537 %P 359 - 373 %@ 978-3-319-99604-2 %G eng %R 10.1007/978-3-319-99605-9_27 %0 Book %D 2018 %T Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide %A Vassilis Galanos %E Kreps, David %E Ess, Charles %E Leenen, Louise %E Kimppa, Kai %I Springer International Publishing %C Cham %V 537 %P 359 - 373 %@ 978-3-319-99604-2 %G eng %R 10.1007/978-3-319-99605-9_27 %0 Conference Paper %B IFIP International Conference on Human Choice and Computers %D 2018 %T Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide %A Vassilis Galanos %B IFIP International Conference on Human Choice and Computers %G eng %U https://doi.org/10.1007/978-3-319-99605-9_27 %0 Journal Article %J Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences %D 2018 %T Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration %A Mikhaylov, Slava Jankin %A Esteve, Marc %A Campion, Averill %B Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences %V 376 %P 20170357 %8 Jan-09-2019 %G eng %N 2128 %R 10.1098/rsta.2017.0357 %0 Journal Article %J Risk Management and Insurance Review %D 2018 %T Artificial intelligence: Implications for social inflation and insurance %A Kelley, Kevin H. %A Fontanetta, Lisa M. %A Heintzman, Mark %A Pereira, Nikki %B Risk Management and Insurance Review %V 21 %P 373 - 387 %8 Jan-12-2018 %G eng %N 3 %R 10.1111/rmir.12111 %0 Journal Article %J Journal of the American College of Cardiology %D 2018 %T Artificial Intelligence in Cardiology %A Johnson, Kipp W. %A Torres Soto, Jessica %A Glicksberg, Benjamin S. %A Shameer, Khader %A Miotto, Riccardo %A Ali, Mohsin %A Ashley, Euan %A Joel T. Dudley %B Journal of the American College of Cardiology %V 71 %P 2668 - 2679 %8 Jan-06-2018 %G eng %N 23 %R 10.1016/j.jacc.2018.03.521 %0 Journal Article %J Cureus %D 2018 %T Artificial Intelligence in Medicine and Radiation Oncology %A Weidlich, Vincent %A Weidlich, Georg A. %K artificial intelligence %K big data %K error analysis %K error prevention %K machine learning %K process efficiency %K process optimization %K quality improvement %K radiation oncology %X 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. %B Cureus %8 Jan-04-2019 %G eng %U https://www.cureus.com/articles/11443-artificial-intelligence-in-medicine-and-radiation-oncology %R 10.7759/cureus.2475 %0 Journal Article %J Journal of Service Research %D 2018 %T Artificial Intelligence in Service %A Huang, Ming-Hui %A Rust, Roland T. %B Journal of Service Research %V 21 %P 155 - 172 %8 May-05-2018 %G eng %N 2 %R 10.1177/1094670517752459 %0 Journal Article %J Electronics Science Technology and Application %D 2018 %T Artificial intelligence in the computer-age threatens human beings and working conditions at workplaces %A Saithibvongsa, Phothong %A Yu, Jae Eon %B Electronics Science Technology and Application %V 5 %8 Feb-08-2019 %G eng %N 3 %R 10.18686/esta.v5i3.76 %0 Thesis %B Management Engineering Department %D 2018 %T Artificial Intelligence In The Sport Industry %A Jacopo Mosele %B Management Engineering Department %G eng %U https://www.politesi.polimi.it/bitstream/10589/142501/1/ARTIFICIAL%20INTELLIGENCE%20IN%20THE%20SPORT%20INDUSTRY_JACOPO%20MOSELE.pdf %0 Web Page %D 2018 %T Artificial Intelligence Is Automating Hollywood %A Dan Robitzki %K AI use cases %B Futurism %8 07/2018 %G eng %U https://futurism.com/artificial-intelligence-automating-hollywood-art %0 Generic %D 2018 %T Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter %A Thomas Gries %A Wim Naude %K artificial intelligence %K economics of automation %K growth theory %K innovation %K labour demand %K productivity %K technology %B Maastricht Economic and social Research institute on Innovation and Technology %I Maastricht University %G eng %U http://ftp.iza.org/dp12005.pdf %0 Journal Article %J Journal of Global Health %D 2018 %T Artificial intelligence, machine learning and health systems %A Panch, Trishan %A Szolovits, Peter %A Atun, Rifat %B Journal of Global Health %V 8 %8 Sep-10-2019 %G eng %N 2 %R 10.7189/jogh.08.020303 %0 Journal Article %J British Journal of Radiology %D 2018 %T Artificial intelligence, machine learning and the evolution of healthcare A bright future or cause for concern? %A L.D. Jones %A D. Golan %A S. A. Hanna %A M. Ramachandran %K artificial intelligence %K deep learning %K machine learning %B British Journal of Radiology %V 7 %P 223-225 %G eng %N 7 %9 Editorial %0 Journal Article %J Bone & Joint Research %D 2018 %T Artificial intelligence, machine learning and the evolution of healthcare %A Jones, L. D. %A D. Golan %A S. A. Hanna %A M. Ramachandran %B Bone & Joint Research %V 7 %P 223 - 225 %8 Jan-03-2018 %G eng %N 3 %R 10.1302/2046-3758.73.BJR-2017-0147.R1 %0 Report %D 2018 %T As s essing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour %A Emilia Gómez %A Carlos Castillo %A Vicky Charisi %A Verónica Dahl %A Gustavo Deco %A Blagoj Delipetrev %A Nicole Dewandre %A Miguel Ángel González-Ballester %A Fabien Gouyon %A José Hernández-Orallo %A Perfecto Herrera %A Anders Jonsson %A Ansgar Koene %A Martha Larson %A Ramón López de Mántaras %A Bertin Martens %A Marius Miron %A Rubén Moreno-Bote %A Nuria Oliver %A Antonio Puertas Gallardo %A Heike Schweitzer %A Nuria Sebastian %A Xavier Serra %A Joan Serrà %A Songül Tolan %A Karina Vold %G eng %U https://arxiv.org/ftp/arxiv/papers/1806/1806.03192.pdf %0 Conference Paper %D 2018 %T Assisting tourism in rural Southern Africa using machine learning %A Laurie Butgereit %A Laura Martinus %X 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'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. %I IEEE %G eng %U https://ieeexplore.ieee.org/document/8465441 %0 Journal Article %J Asian Journal of Convergence in Technology %D 2018 %T Automated Classification of chest X-ray images as normal or abnormal using Convolutional Neural Network %A Aayushi Gupta %A Anupama C %A P Indumathi %A Anuj Kumar %K classification %K machine learning %K radiology %X 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. %B Asian Journal of Convergence in Technology %V 4 %8 04/2018 %G eng %N 1 %0 Journal Article %J Geoforum %D 2018 %T Automating the black art: Creative places for artificial intelligence in audio mastering %A Birtchnell, Thomas %A Elliott, Anthony %B Geoforum %V 96 %P 77-86 %G eng %U https://linkinghub.elsevier.com/retrieve/pii/S0016718518302392 %R 10.1016/j.geoforum.2018.08.005 %0 Generic %D 2018 %T Automation and the future of jobs in India %A Francis Kuriakose %A Deepa Iyer %K economics of automation %B Center For The Advanced Study of India %I University of Pennsylvania %8 11/2018 %G eng %U https://casi.sas.upenn.edu/iit/kuriakoseiyer %9 Economy, Politics, Science and Technology %0 Journal Article %J Centre for International Governance Innovation %D 2018 %T Automation and the future of work %A Joel Blit %A Samantha St. Amand %A Joanna Wajda %B Centre for International Governance Innovation %G eng %U https://www.cigionline.org/publications/automation-and-future-work-scenarios-and-policy-options %N 174 %0 Report %D 2018 %T Is automation labor-displacing? Productivity growth, employment, and the labor share %A Autor, David %A Salomons, Anna %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w24871 %0 Generic %D 2018 %T Automation, taxes and transfers with international rivalry %A Rod Tyers %A Yixiao Zhou %K automation %K global modelling %K income distribution %K taxes %K transfers %B Centre for Applied Macroeconomic Analysis %I Australian National University %G eng %U https://cama.crawford.anu.edu.au/sites/default/files/publication/cama_crawford_anu_edu_au/2018-09/44_2018_tyers_zhou.pdf %0 Journal Article %J Communications of the ACM %D 2018 %T Autonomous tools and design: a triple-loop approach to human-machine learning %A Seidel, Stefan %A Berente, Nicholas %A Lindberg, Aron %A Lyytinen, Kalle %A Jeffrey V Nickerson %B Communications of the ACM %I ACM %V 62 %P 50–57 %G eng %0 Journal Article %J Computer %D 2018 %T Autonomous Tools in System Design: Reflective Practice in Ubisofts Ghost Recon Wildlands Project %A Seidel, Stefan %A Berente, Nicholas %A Martinez, Beno\^ıt %A Lindberg, Aron %A Lyytinen, Kalle %A Jeffrey V Nickerson %B Computer %I IEEE %V 51 %P 16–23 %G eng %0 Report %D 2018 %T Autonomous trucks and the future of the american trucker %A Steve Viscelli %B UC Berkeley Center for Labor Research and Education and Working Partnerships USA %8 09/2018 %G eng %U https://www.steveviscelli.com/self-driving-trucks %0 Report %D 2018 %T Autonomous vehicles employment impact study %A Brian Haratsis %A Tony Carmichael %A Mark Coutney %A Jacob Fong %B Australia & New Zealand Driverless Vehicle Initiate %8 09/2018 %G eng %U https://advi.org.au/wp-content/uploads/2018/09/Autonomous-Vehicles-Employment-Impact-Survey-COR050918-5.pdf %0 Journal Article %J The NewYork Times %D 2018 %T ‘The beginning of a wave’: A.I. Tiptoes into the workplace %A Steve Lohr %K AI %K impacts %B The NewYork Times %G eng %U https://www.nytimes.com/2018/08/05/technology/workplace-ai.html %0 Generic %D 2018 %T Beyond r&d: The role of embodied technological change in affecting employment %A Gabriele Pelleegrino %A Mariacristina Piva %A Marco Vivarelli %K Innovation; R&D; Embodied Technological Change; Employment; GMM-SY %G eng %U https://ideas.repec.org/p/ssa/lemwps/2018-15.html %0 Journal Article %J Sustainability Science %D 2018 %T Boundary spanning at the science–policy interface: the practitioners’ perspectives %A Bednarek, A. T. %A Wyborn, C. %A Cvitanovic, C. %A Meyer, R. %A Colvin, R. M. %A Addison, P. F. E. %A Close, S. L. %A Curran, K. %A Farooque, M. %A Goldman, E. %A Hart, D. %A Mannix, H. %A McGreavy, B. %A Parris, A. %A Posner, S. %A Robinson, C. %A Ryan, M. %A Leith, P. %B Sustainability Science %V 13 %P 1175 - 1183 %8 Jan-07-2018 %G eng %N 4 %R 10.1007/s11625-018-0550-9 %0 Journal Article %J Strategic HR Review %D 2018 %T Can artificial intelligence make work more human? %A He, Emily %B Strategic HR Review %V 17 %P 263 - 264 %8 Aug-10-2018 %G eng %N 5 %R 10.1108/SHR-10-2018-146 %0 Journal Article %J Creative Education %D 2018 %T Character qualities and the imagination age %A Alvarez, María García %B Creative Education %V 09 %P 152 - 164 %8 Jan-01-2018 %G eng %N 02 %R 10.4236/ce.2018.92012 %0 Journal Article %J Strategic HR Review %D 2018 %T Chat bots are the new HR managers %A Sheth, Beerud %B Strategic HR Review %V 17 %P 162 - 163 %8 Nov-06-2018 %G eng %N 3 %R 10.1108/SHR-03-2018-0024 %0 Journal Article %J Cognitive Science – New Media – Education %D 2018 %T Cognitive and technological aspects of e-learning in context of robotization %A Shvets, Anna %A Shvets, Valentyna %K artificial intelligence worker %K Blue Prism automation %K intelligent system of feedbacks %K robotic process automation %X 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' 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'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. %B Cognitive Science – New Media – Education %V 3 %P 65 %8 Mar-06-2020 %G eng %U http://apcz.umk.pl/czasopisma/index.php/CSNME/article/view/CSNME.2017.013 %N 2 %R 10.12775/CSNME.2017.013 %0 Web Page %D 2018 %T Collaborative intelligence: Humans and AI are joining forces %A H. James Wilson %A Paul R. Daugherty %B Havard Business Review %G eng %U https://hbr.org/2018/07/collaborative-intelligence-humans-and-ai-are-joining-forces %N Reprint R1804J %0 Journal Article %J Journal of Monetary Economics %D 2018 %T Comment on “Should we fear the robot revolution? (The correct answer is yes)” by Andrew Berg, Ed Buffie, and Felipe Zanna %A Hanley, Douglas %B Journal of Monetary Economics %V 97 %P 149 - 152 %8 Jan-08-2018 %G eng %R 10.1016/j.jmoneco.2018.05.012 %0 Journal Article %J SSRN Electronic Journal %D 2018 %T Computational power and the social impact of artificial intelligence %A Tim Hwang %X 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. %B SSRN Electronic Journal %G eng %R 10.2139/ssrn.3147971 %0 Book %D 2018 %T Creativity, the arts, and the future of work %A Nathan, Linda F. %E Cook, Justin W. %I Springer International Publishing %C Cham %P 283 - 310 %@ 978-3-319-78579-0 %G eng %R 10.1007/978-3-319-78580-6_9 %0 Journal Article %J Information and Organization %D 2018 %T A critical approach to human helping in information systems: Heteromation in the Brazilian correspondent banking system %A Diane E. Bailey %A Eduardo H. Diniz %A Bonnie A. Nardi %A Paul M. Leonardi %A Dan Sholler %B Information and Organization %V 28 %P 111 - 128 %8 Jan-09-2018 %G eng %N 3 %R 10.1016/j.infoandorg.2018.08.002 %0 Book %D 2018 %T A critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America’s labour force %A Wogu, Ikedinachi Ayodele %A Misra, Sanjay %A Assibong, Patrick %A Adewumi, Adewole %A Damasevicius, Robertas %A Maskeliunas, Rytis %E Gervasi, Osvaldo %E Murgante, Beniamino %E Misra, Sanjay %E Stankova, Elena %E Torre, Carmelo M. %E Rocha, Ana Maria A.C. %E Taniar, David %E Apduhan, Bernady O. %E Tarantino, Eufemia %E Ryu, Yeonseung %I Springer International Publishing %C Cham %V 10963 %P 217 - 232 %@ 978-3-319-95170-6 %G eng %R 10.1007/978-3-319-95171-3_18 %0 Journal Article %J Path of Science %D 2018 %T Cryptocurrency, Artificial Intelligence and basic income as innovative technological system %A Sopilnyk, Lyubomyr %A Shevchuk, Andriy %A Kopytko, Vasyl %B Path of Science %V 4 %P 2024 - 2030 %8 Jul-08-2020 %G eng %N 8 %R 10.22178/pos10.22178/pos.37-6 %0 Book %D 2018 %T Data Science for Undergraduates %I National Academies Press %C Washington, D.C. %@ 978-0-309-47559-4 %G eng %U https://www.nap.edu/catalog/25104 %R 10.17226/25104 %0 Journal Article %J Landscape Architecture Frontiers %D 2018 %T DEFINITION, APPLICATION AND INFLUENCE OF ARTI FICIAL INTELLIGENCE ON DESIGN INDUSTRIES %A Linghao Cai %A Ling Fan %A Wenbo Lai %A LONG, Ying %A Peng Wang %A Xiangyang Xin %B Landscape Architecture Frontiers %V 6 %P 56 %8 Jan-01-2018 %G eng %N 2 %R 10.15302/J-LAF-20180207 %0 Journal Article %J Business Horizons %D 2018 %T Developing an ethical framework %A Wright, Scott A. %A Schultz, Ainslie E. %B Business Horizons %V 61 %P 823 - 832 %8 Jan-11-2018 %G eng %N 6 %R 10.1016/j.bushor.2018.07.001 %0 Journal Article %J European View %D 2018 %T Developing robots: The need for an ethical framework %A Leveringhaus, Alex %B European View %V 17 %P 37 - 43 %8 Aug-04-2019 %G eng %N 1 %R 10.1177/1781685818761016 %0 Journal Article %J SHS Web of Conferences %D 2018 %T Digital economy and the models of income distribution in the society %A Akaev, Askar %A Rudskoi, Andrew %A Devezas, Tessaleno %E Sarygulov, A. %E Sergeev, V. %E Ungvári, L. %E Semmler, W. %B SHS Web of Conferences %V 44 %P 00005 %8 Jan-01-2018 %G eng %R 10.1051/shsconf/20184400005 %0 Journal Article %J SHS Web of Conferences %D 2018 %T Digital economy: backgrounds, main drivers and new challenges %A Akaev, Askar %A Sarygulov, Askar %A Sokolov, Valentin %E Sarygulov, A. %E Sergeev, V. %E Ungvári, L. %E Semmler, W. %B SHS Web of Conferences %V 44 %P 00006 %8 Jan-01-2018 %G eng %R 10.1051/shsconf/20184400006 %0 Journal Article %J Journal of the Association for Information Systems %D 2018 %T The discourse approach to boundary identification and corpus construction for theory review articles %A Kai R. Larsen %A Dirik S. Hovorka %A Alan R. Dennis %A Jevin D. West %K article identification %K boundary identification %K citation search %K keyword search %K literature review %K machine learning %K research review %K review article %B Journal of the Association for Information Systems %G eng %U https://www.researchgate.net/publication/325215971_Understanding_the_Elephant_The_Discourse_Approach_to_Boundary_Identification_and_Corpus_Construction_for_Theory_Review_Articles %0 Journal Article %J Journal of Monetary Economics %D 2018 %T Discussion for JME special issue: APST paper %A Hershbein, Brad %B Journal of Monetary Economics %V 97 %P 68 - 70 %8 Jan-08-2018 %G eng %R 10.1016/j.jmoneco.2018.05.003 %0 Web Page %D 2018 %T Dreyfus on the 'Fringe': information processing, intelligent activity, and the future of thinking machines %A Jeffrey White %B Ai & Society %G eng %U https://www.researchgate.net/publication/323956550_Dreyfus_on_the_fringe_-_accepted_draft %0 Generic %D 2018 %T Economic policy for artificial intelligence %A Ajay Agrawal %A Joshua Gans %A Avi Goldfarb %K economics of automation %X Recent progress in artificial intelligence (AI) – 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. %B National Bureau of Economic Research %8 06/2018 %G eng %U https://econpapers.repec.org/paper/nbrnberwo/24690.htm %0 Report %D 2018 %T Economic policy for Artificial Intelligence %A Agrawal, Ajay %A Gans, Joshua %A Goldfarb, Avi %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w24690 %0 Report %D 2018 %T The economics of artificial intelligence: Implications for the future of work %A Ekkehard Ernst %A Rossana Merola %A Daniel Samaan %B International Labour Office %@ 978-92-2-031137-0 %G eng %U https://www.ilo.org/wcmsp5/groups/public/---dgreports/---cabinet/documents/publication/wcms_647306.pdf %0 Thesis %B Engineering and Policy Analysis %D 2018 %T Economies of the future: Robots and Artificial Intelligence, the new economic motor or downfall of the working class? %A Koen Spaanderman %K economics of automation %X 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? %B Engineering and Policy Analysis %8 11/2018 %G eng %U https://repository.tudelft.nl/islandora/object/uuid%3Af30b5d2e-d48d-4c90-8780-3d55a2e1a7d3 %9 master thesis %0 Magazine Article %D 2018 %T The effects of automation %A Jim L. Smith %B Quality Magazine %G eng %U https://www.dropbox.com/sh/8sxki5mwikjxlte/AAB6zvW5F0s2FIJ6jUmEW7P-a/Popular%20press%20about%20impacts?dl=0&preview=effects+of+automation.pdf&subfolder_nav_tracking=1 %0 Book %D 2018 %T eHealth - Making Health Care SmarterUse of Artificial Intelligence in Healthcare Delivery %A Reddy, Sandeep %E Heston, Thomas F. %I InTech %@ 978-1-78923-522-7 %G eng %R http://dx.doi.org/10.5772/intechopen.74714 %0 Magazine Article %D 2018 %T Embracing the new world of work %A John M. Lewin %B Strategic Finance %G eng %U https://sfmagazine.com/post-entry/june-2018-embracing-the-new-world-of-work/ %0 Journal Article %J European Journal of Training and Development %D 2018 %T Embracing the sobering reality of technological influences on jobs, employment and human resource development %A Chuang, Szufang %A Graham, Carroll Marion %B European Journal of Training and Development %V 42 %P 400 - 416 %8 Mar-09-2018 %G eng %N 7/8 %R 10.1108/EJTD-03-2018-0030 %0 Journal Article %J Texas A&M Journal of Property Law %D 2018 %T Ethics of using Artificial Intelligence to augment drafting legal documents %A David Hricik Hri %A Asya-Lorrene S. Morgan %A Kyle H. Williams %B Texas A&M Journal of Property Law %7 3 %V 4 %G eng %U https://scholarship.law.tamu.edu/cgi/viewcontent.cgi?article=1080&context=journal-of-property-law %N 5 %0 Report %D 2018 %T The evolving role of ICT in the economy %A Mirko Draca %A Ralf Martin %A Rosa Sanchis-Guarner %K consulting reports %B The London School of Economics and Political Science %8 06/2018 %G eng %U http://www.lse.ac.uk/business-and-consultancy/consulting/consulting-reports/the-evolving-role-of-ict-in-the-economy %0 Thesis %D 2018 %T Examination of cognitive load in the human-machine teaming context %A Clarke, Alan J. %A Knudson, Daniel F. III %X 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’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. %8 06/2018 %G eng %U https://hdl.handle.net/10945/59638 %0 Generic %D 2018 %T Experimental evidence on complimentarities between human capital and machine learning %A Prithwiraj Choudhury %A Evan Starr %A Rajshree Agarwal %K economics of automation %B Havard Business Review %8 01/2018 %G eng %U https://hbswk.hbs.edu/item/different-strokes-for-different-folks-experimental-evidence-on-complementarities-between-human-capital-and-machine-learning %0 Generic %D 2018 %T Experimental evidence on productivity complementarities %A Prithwiraj Choudhury %Y Evan Starr %Y Rajshree Agarwal %K Human Capital %K Performance Productivity %K Technological Innovation %K Technology Adoption %I Harvard Business School Working Paper %G eng %U https://www.hbs.edu/faculty/Pages/item.aspx?num=53855 %0 Report %D 2018 %T Explaining the decline in the u. S. Employment-to-population ratio: A review of the evidence %A Abraham, Katharine %A Kearney, Melissa %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w24333 %0 Journal Article %J IUI Workshops %D 2018 %T Explanation to Avert Surprise %A Melinda Gervasio %A Karen Myers %A Eric Yeh %A Boone Adkins %B IUI Workshops %G eng %U https://www.semanticscholar.org/paper/Explanation-to-Avert-Surprise-Gervasio-Myers/8e3b3d9e9075095a87c96fa9690d2ccbf127234e %0 Journal Article %J The Information Society %D 2018 %T Exploiting ability for human adaptation to facilitate improved human-robot interaction and acceptance %A Caleb-Solly, Praminda %A Dogramadzi, Sanja %A Huijnen, Claire A.G.J. %A Heuvel, Herjan van den %B The Information Society %V 34 %P 153 - 165 %8 Mar-05-2020 %G eng %N 3 %R 10.1080/01972243.2018.1444255 %0 Magazine Article %D 2018 %T Fedex follows Amazon into the robotic future %A Cade Metz %B The New York Times %G eng %U https://www.nytimes.com/2018/03/18/technology/fedex-robots.html %0 Report %D 2018 %T Financing Terror Enterprises Funding Operations in Prolonged Conflicts in South Asia %A Nikita Kohli %I KW Publishers Pvt Ltd %C New Delhi %G eng %U https://www.claws.in/images/publication_pdf/1589740822_1515901225_MP71-NikitaKohli(Final)_CLAWS.pdf %0 Journal Article %J Big Data Analytics %D 2018 %T foo.castr: visualising the future AI workforce %A Amador Diaz Lopez, Julio %A Molina-Solana, Miguel %A Kennedy, Mark T. %B Big Data Analytics %V 3 %8 Jan-12-2018 %G eng %N 1 %R 10.1186/s41044-018-0034-z %0 Web Page %D 2018 %T forbes.com 10 Amazing Examples Of How Deep Learning AI Is Used In Practice? %A Bernard Marr %B Forbes %G eng %0 Conference Paper %B the 11th International WorkshopProceedings of the 11th International Workshop on Cooperative and Human Aspects of Software Engineering - CHASE '18 %D 2018 %T A framework for understanding chatbots and their future %A Paikari, Elahe %A van der Hoek, André %Y Sharp, Helen %Y de Souza, Cleidson R. B. %Y Graziotin, Daniel %Y Levy, Meira %Y Socha, David %B the 11th International WorkshopProceedings of the 11th International Workshop on Cooperative and Human Aspects of Software Engineering - CHASE '18 %I ACM Press %C Gothenburg, SwedenNew York, New York, USA %P 13 - 16 %@ 9781450357258 %G eng %R 10.1145/3195836.3195859 %0 Journal Article %J American Journal Of Modern Physics And Application %D 2018 %T Future of artificial intelligence: Japan’s path to growth %A Salman Abdou %A Nadeen Nustafa Kamal %B American Journal Of Modern Physics And Application %V 5 %P 48-52 %8 05/2018 %G eng %U https://www.researchgate.net/publication/326625497_Future_of_Artificial_Intelligence_Japan's_Path_to_Growth_Email_address %6 3 %0 Journal Article %J Journal of Legal Studies Education %D 2018 %T The future of work, business education, and the role of AACSB %A Beck-Dudley, Caryn L. %B Journal of Legal Studies Education %V 35 %P 165 - 170 %8 Jan-12-2018 %G eng %N 1 %R 10.1111/jlse.2018.35.issue-110.1111/jlse.12073 %0 Magazine Article %D 2018 %T The Future of Work: Compulsory, by Martha Wells %A Martha Wells %B Wired %G eng %U https://www.wired.com/story/future-of-work-compulsory-martha-wells/ %0 Journal Article %D 2018 %T The future of work in the light of technological change %A Vesna Novak %A Denis Dizdarevic %K Impact of technology on the labour market %K Labour market %K Technological unemployment %X 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. %V UDC: 005.32:005.95/.96 %G eng %U http://media3.novi.economicsandlaw.org/2017/07/Vol23/IJEAL-23-09.pdf %9 Original Scientific Paper %0 Journal Article %J European View %D 2018 %T The Future of Work: Robots Cooking Free Lunches? %A Turk, Ziga %B European View %V 17 %P 241 - 241 %8 Jun-10-2020 %G eng %N 2 %R 10.1177/1781685818813010 %0 Magazine Article %D 2018 %T The Future of Work: The Trustless, by Ken Liu %A Ken Liu %B Wired %G eng %U https://www.wired.com/story/future-of-work-trustless-ken-liu/ %0 Journal Article %J Strategy & Leadership %D 2018 %T Game changing value from Artificial Intelligence: eight strategies %A Plastino, Eduardo %A Purdy, Mark %B Strategy & Leadership %V 46 %P 16 - 22 %8 Mar-01-2019 %G eng %N 1 %R 10.1108/SL-11-2017-0106 %0 Magazine Article %D 2018 %T G.M says its driverless car could be in fleets by next year %A Neal E. Boudette %K autonomous vehicles %B The NewYork Times %8 01/2018 %G eng %U https://www.nytimes.com/2018/01/12/business/gm-driverless-car.html %0 Magazine Article %D 2018 %T Google and others are building AI systems that doubt themselves %A Will Knight %B MIT Technology Review %G eng %U https://www.technologyreview.com/s/609762/google-and-others-are-building-ai-systems-that-doubt-themselves/ %0 Web Page %D 2018 %T Google glass is back with AI %A Tom Simonite %X An app for Glass aimed at factory workers can understand spoken language and respond verbally. %B wired.com %8 07/2018 %G eng %U https://www.wired.com/story/google-glass-is-backnow-with-artificial-intelligence/ %N Business %0 Web Page %D 2018 %T Google Researchers Are Learning How Machines Learn %A Cade Metz %B The NewYork Times %G eng %U https://www.nytimes.com/2018/03/06/technology/google-artificial-intelligence.html %0 Journal Article %J Historical Materialism %D 2018 %T High tech, low growth: Robots and the future of work abstract %A Moody, Kim %B Historical Materialism %V 26 %P 3 - 34 %8 May-12-2019 %G eng %N 4 %R 10.1163/1569206X-00001745 %0 Magazine Article %D 2018 %T High-skilled white-collar work? Machines can do that, too %A Noam Scheiber %B The New York Times %G eng %U https://www.nytimes.com/2018/07/07/business/economy/algorithm-fashion-jobs.html %0 Web Page %D 2018 %T How cheap labor drives China’s AI Ambitions %A Li Yuan %K human and machine intelligence %B nytimes %8 11/2018 %G eng %U https://www.nytimes.com/2018/11/25/business/china-artificial-intelligence-labeling.html %0 Journal Article %J Communications of the Association for Information Systems %D 2018 %T How do machine learning, robotic process automation, and blockchains affect the human factor in business process management? %A Mendling, Jan %A Decker, Gero %A Hull, Richard %A Reijers, Hajo A. %A Weber, Ingo %B Communications of the Association for Information Systems %P 297 - 320 %8 Jan-01-2018 %G eng %R 10.17705/1CAIS.04319 %0 Journal Article %J management revu %D 2018 %T How does the digital transformation affect organizations? Key themes of change in work design and leadership %A Schwarzmüller, Tanja %A Brosi, Prisca %A Duman, Denis %A Welpe, Isabell M. %B management revu %V 29 %P 114 - 138 %8 Jan-01-2018 %G eng %N 2 %R 10.5771/0935-9915-2018-2-114 %0 Magazine Article %D 2018 %T How driverless cars could disrupt the real estate industry %A Ely Razin %K autonomous vehicles %B forbes %G eng %U https://www.forbes.com/sites/elyrazin/2018/03/11/how-driverless-cars-could-disrupt-the-real-estate-industry/#1595cb8613c1 %0 Magazine Article %D 2018 %T How leaders face the future of work ? %A Lynda Gratton %B MIT Slogan Management Review %V 59 %G eng %U https://sloanreview.mit.edu/article/how-leaders-face-the-future-of-work/ %N 3 %0 Journal Article %J JBEL %D 2018 %T How machine learning can permanently capture legal expertise and optimize the law firm pyramid %A J. Mark Phillips %X 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’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’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’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. %B JBEL %V 11 %G eng %U https://digitalcommons.pepperdine.edu/jbel/vol11/iss2/3/ %N 2 %0 Journal Article %J Business Information Review %D 2018 %T How real is the impact of artificial intelligence? The business information survey 2018 %A Carter, Denise %K Artificial Intelligence (AI) %K blockchain %K chatbot %K cybersecurity %K data economy %K data governance %K data lakes %K data literacy %K data quality %K data trusts %K data value %K ethics %K information literacy %K intelligent virtual agents %K machine learning (ML) %K Robotics %B Business Information Review %V 35 %P 99 - 115 %8 12/2019 %G eng %U http://journals.sagepub.com/doi/10.1177/0266382118790150 %N 3 %R 10.1177/0266382118790150 %0 Journal Article %J Academy of Management Proceedings %D 2018 %T How the anthropormorphization of virtual assistants influences user's trust %A Crone, Tim %A Shafeie Zargar, Mahmood %B Academy of Management Proceedings %V 2018 %P 16328 %8 Jan-08-2018 %G eng %N 1 %R 10.5465/AMBPP.2018.16328abstract %0 Journal Article %J Journal of Open Innovation: Technology, Market, and Complexity %D 2018 %T 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 %A Lee, MinHwa %A Yun, JinHyo %A Pyka, Andreas %A Won, DongKyu %A Kodama, Fumio %A Schiuma, Giovanni %A Park, HangSik %A Jeon, Jeonghwan %A Park, KyungBae %A Jung, KwangHo %A Yan, Min-Ren %A Lee, SamYoul %A Zhao, Xiaofei %B Journal of Open Innovation: Technology, Market, and Complexity %V 4 %P 21 %8 Jan-09-2018 %G eng %N 3 %R 10.3390/joitmc4030021 %0 Book %B CEDA – the Committee for Economic Development of Australia %D 2018 %T How unequal? Insights on inequality %K ethics %B CEDA – the Committee for Economic Development of Australia %8 04/2018 %@ 0 85801 318 5 %G eng %U https://www.ceda.com.au/CEDA/media/General/Publication/PDFs/CEDA-How-unequal-Insights-on-inequality-April-2018-FINAL_WEB.pdf %0 Journal Article %J Computational Economics %D 2018 %T Human and Machine Learning %A Kao, Ying-Fang %A Venkatachalam, Ragupathy %B Computational Economics %8 Sep-02-2019 %G eng %R 10.1007/s10614-018-9803-z %0 Journal Article %J IEEE SMC Magazine %D 2018 %T Human and smart machine co-learning with brain computer interface %A Chang - Shing Lee %A Mei - Hui Wang %A Li - Wei Ko %A Naoyuki Kubota %A Lu - An Lin %A Shinya Kitaoka %A Yu - Te Wang %A Shun - Feng Su %K human and machine inttelligence %B IEEE SMC Magazine %V 4 %G eng %U https://arxiv.org/abs/1802.06521 %6 2 %0 Journal Article %J OALib %D 2018 %T Human capital management and future of work; job creation and unemployment: a literature review %A Mukhalipi, Adamson %B OALib %V 05 %P 1 - 17 %8 Jan-01-2018 %G eng %N 09 %R 10.4236/oalib.1104859 %0 Web Page %D 2018 %T IBM Watson Talent The Business Case for AI in HR With Insights and Tips on Getting Started %A Nigel Guenole %A Sheri Feinzig %G eng %U https://www.ibm.com/downloads/cas/AGKXJX6M %0 Journal Article %J Sustainability %D 2018 %T Identifying factors reinforcing robotization: Interactive forces of employment, working hour and wage %A Cho, Joonmo %A Kim, Jinha %B Sustainability %V 10 %P 490 %8 Jan-02-2018 %G eng %N 2 %R 10.3390/su10020490 %0 Conference Paper %B Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences %D 2018 %T Image Recognition of Disease-Carrying Insects: A System for Combating Infectious Diseases Using Image Classification Techniques and Citizen Science %A Munoz, J. Pablo %A Boger, Rebecca %A Dexter, Scott %A Low, Russanne %A Li, Justin %Y Bui, Tung %B Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences %I Hawaii International Conference on System Sciences %G eng %U http://hdl.handle.net/10125/49887http://hdl.handle.net/10125/50247 %R 10.24251/HICSS.2018.00010.24251/HICSS.2018.359 %0 Magazine Article %D 2018 %T Imagining a future of work that fosters mobility for all %A Lawrence Katz %A Ai-Jen Poo %A Elaine Waxman %B Us partnership on mobility from poverty %G eng %U https://www.mobilitypartnership.org/imagining-future-work-fosters-mobility-all %0 Conference Paper %B IES Perspectives on HR 2018 %D 2018 %T The impact of artificial intelligence on the HR function %A Peter Reilly %K HR %B IES Perspectives on HR 2018 %G eng %U https://www.employment-studies.co.uk/system/files/resources/files/mp142_The_impact_of_Artificial_Intelligence_on_the_HR_function-Peter_Reilly.pdf %0 Journal Article %J Sustainability %D 2018 %T The impact of automation on employment: Just the usual structural change? %A Vermeulen, Ben %A Kesselhut, Jan %A Pyka, Andreas %A Saviotti, Pier %B Sustainability %V 10 %P 1661 %8 Jan-05-2018 %G eng %N 5 %R 10.3390/su10051661 %0 Generic %D 2018 %T The impact of industrial robots on eu employment and wages: A local labour market approach %A Francesco Chiacchio %A Georgios Petropoulos %A David Pichler %K economics of automation %I bruegel %8 04/2018 %G eng %U https://bruegel.org/2018/04/the-impact-of-industrial-robots-on-eu-employment-and-wages-a-local-labour-market-approach/ %0 Journal Article %J Oxford Review of Economic Policy %D 2018 %T The impact of technological progress on labour markets: policy challenges %A Goos, Maarten %B Oxford Review of Economic Policy %V 34 %P 362 - 375 %8 Feb-07-2018 %G eng %N 3 %R 10.1093/oxrep/gry002 %0 Journal Article %J International Journal of Global Sustainability %D 2018 %T The impact of technology and globalization on employment and equity %A Arogyaswamy, Bernard %A Hunter, John %B International Journal of Global Sustainability %V 3 %P 49 %8 Oct-11-2019 %G eng %N 1 %R 10.5296/ijgs.v3i1.14127 %0 Journal Article %J American Economic Review %D 2018 %T Implications of technology for growth, factor shares, and employment %A Acemoglu, Daron %A Restrepo, Pascual %B American Economic Review %V 108 %P 1488 - 1542 %8 Jan-06-2018 %G eng %N 6 %R 10.1257/aer.20160696 %0 Journal Article %J BMC Medical Informatics and Decision Making %D 2018 %T Improving palliative care with deep learning %A Avati, Anand %A Jung, Kenneth %A Harman, Stephanie %A Downing, Lance %A Ng, Andrew %A Shah, Nigam H. %B BMC Medical Informatics and Decision Making %V 18 %8 Jan-12-2018 %G eng %N S4 %R 10.1186/s12911-018-0677-8 %0 Journal Article %J Applications in Plant Sciences %D 2018 %T iNaturalist as a tool to expand the research value of museum specimens %A Heberling, J. Mason %A Isaac, Bonnie L. %K AI use cases %B Applications in Plant Sciences %V 6 %P e01193 %8 Jan-11-2018 %G eng %N 11 %R 10.1002/aps3.1193 %0 Journal Article %J Structural Change and Economic Dynamics %D 2018 %T Industrial employment and income inequality: Evidence from panel data %A Mehic, Adrian %B Structural Change and Economic Dynamics %V 45 %P 84 - 93 %8 Jan-06-2018 %G eng %U 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 %R 10.1016/j.strueco.2018.02.006 %0 Journal Article %J Computers in Human Behavior %D 2018 %T The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions %A Araujo, Theo %B Computers in Human Behavior %V 85 %P 183 - 189 %8 Jan-08-2018 %G eng %R 10.1016/j.chb.2018.03.051 %0 Report %D 2018 %T The internet and jobs opportunities and ambiguous trends %A Lorenzo Pupillo %A Eli Noam %A Leonard Waverman %K economics of automation %B Policy Insights %8 02/2018 %G eng %U https://www.ceps.eu/system/files/PI2018_06_LP-EN-LW_InternetAndJobs.pdf %0 Book %D 2018 %T Investigating ergonomics in the context of human-robot collaboration as a sociotechnical system %A Rücker, Daniel %A Hornfeck, Rüdiger %A Paetzold, Kristin %E Chen, Jessie %I Springer International Publishing %C Cham %V 784 %P 127 - 135 %@ 978-3-319-94345-9 %G eng %R 10.1007/978-3-319-94346-6_12 %0 Journal Article %J MIS Quarterly %D 2018 %T Is IT changing the world? Conceptions of causality for information systems theorizing %A M. Lynne Markus %A Frantz Rowe %B MIS Quarterly %V 42 %P 1255-1280 %G eng %U https://dl.acm.org/citation.cfm?id=3370119.3370131 %N 4 %0 Journal Article %J War on the rocks %D 2018 %T ‘It’s either a panda or a gibbon’: AI winters and the limits of deep learning %A Robert Richbourg %B War on the rocks %G eng %U https://warontherocks.com/2018/05/its-either-a-panda-or-a-gibbon-ai-winters-and-the-limits-of-deep-learning/ %9 Commentary %0 Book %D 2018 %T Lecture Notes in Computer ScienceArtificial General IntelligenceTowards a Sociological Conception of Artificial Intelligence %A Jakub Mlynar %A Hamed S. Alavi %A Himanshu Verma %A Lorenzo Cantoni %E Matthew Iklé %E Arthur Franz %E Rafal Rzepka %E Ben Goertzel %I Springer International Publishing %C Cham %V 10999 %P 130 - 139 %@ 978-3-319-97675-4 %G eng %R 10.1007/978-3-319-97676-1 %0 Book %D 2018 %T 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 %A Fernandes, Farley %A Filgueiras, Ernesto %A Neves, André %E Marcus, Aaron %E Wang, Wentao %I Springer International Publishing %C Cham %V 10918 %P 693 - 710 %@ 978-3-319-91796-2 %G eng %R 10.1007/978-3-319-91797-9_48 %0 Conference Proceedings %B Americas Conference on Information Systems %D 2018 %T A literature Analysis of Research on Artificial Intelligence in Management Information System (MIS) %A Alexandre Moreira Nascimento %A Maria Alexandra V. C. da Cunha %A Fernando de Souza Meirelles %A Eusebio Scornavacca %A Vinicius Veloso de Melo %K artificial intelligence %K Information Systems %K Literature Analysis %X 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. %B Americas Conference on Information Systems %G eng %0 Journal Article %J AI & SOCIETY %D 2018 %T Looking though the Pygmalion Lens %A Gill, Karamjit S. %B AI & SOCIETY %V 33 %P 459 - 465 %8 Jan-11-2018 %G eng %N 4 %R 10.1007/s00146-018-0866-0 %0 Book %D 2018 %T Machine intelligence: Blessing or curse? It depends on us! %A Helbing, Dirk %E Helbing, Dirk %I Springer International Publishing %C Cham %P 25 - 39 %@ 978-3-319-90868-7 %G eng %R 10.1007/978-3-319-90869-4_4 %0 Book %D 2018 %T Machine Learning for Ecology and Sustainable Natural Resource ManagementUse of Machine Learning (ML) for Predicting and Analyzing Ecological and ‘Presence Only’ Data: An Overview of Applications and a Good Outlook %A Huettmann, Falk %A Craig, Erica H. %A Herrick, Keiko A. %A Baltensperger, Andrew P. %A Grant Humphries %A Lieske, David J. %A Miller, Katharine %A Mullet, Timothy C. %A Oppel, Steffen %A Resendiz, Cynthia %A Rutzen, Imme %A Schmid, Moritz S. %A Suwal, Madan K. %A Young, Brian D. %E Grant Humphries %E Magness, Dawn R. %E Huettmann, Falk %I Springer International Publishing %C Cham %P 27 - 61 %@ 978-3-319-96976-3 %G eng %R 10.1007/978-3-319-96978-7_2 %0 Book %D 2018 %T Machine Learning for Ecology and Sustainable Natural Resource ManagementMachine Learning and ‘The Cloud’ for Natural Resource Applications: Autonomous Online Robots Driving Sustainable Conservation Management Worldwide? %A Grant Humphries %A Huettmann, Falk %E Grant Humphries %E Magness, Dawn R. %E Huettmann, Falk %I Springer International Publishing %C Cham %P 353 - 377 %@ 978-3-319-96976-3 %G eng %R 10.1007/978-3-319-96978-7_18 %0 Book Section %B Machine Learning for Ecology and Sustainable Natural Resource Management %D 2018 %T Machine Learning in Wildlife Biology: Algorithms, Data Issues and Availability, Workflows, Citizen Science, Code Sharing, Metadata and a Brief Historical Perspective %A Grant Humphries %A Huettmann, Falk %E Grant Humphries %E Magness, Dawn R. %E Huettmann, Falk %B Machine Learning for Ecology and Sustainable Natural Resource Management %I Springer International Publishing %C Cham %P 3 - 26 %@ 978-3-319-96976-3 %G eng %R 10.1007/978-3-319-96978-7_1 %0 Journal Article %J Social Studies of Science %D 2018 %T Machine learning, social learning and the governance of self-driving cars %A Jack Stilgoe %X Self-driving cars, a quintessentially ‘smart’ 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 ‘Who is learning, what are they learning and how are they learning?’ 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. ‘Self-driving’ or ‘autonomous’ 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. %B Social Studies of Science %V 48 %P 25-56 %G eng %R 10.1177/0306312717741687 %0 Conference Paper %B Hawaii International Conference on System Sciences %D 2018 %T Machines as Teammates: A Collaboration Research Agenda %A Seeber, Isabella %A Bittner, Eva %A Briggs, Robert O. %A de Vreede, Gert-Jan %A de Vreede, Triparna %A Druckenmiller, Doug %A Maier, Ronald %A Merz, Alexander B. %A Oeste-Reiß, Sarah %A Randrup, Nils %A Gerhard Schwabe %A Söllner, Matthias %B Hawaii International Conference on System Sciences %I Hawaii International Conference on System Sciences %G eng %U http://hdl.handle.net/10125/49887 %R 10.24251/HICSS.2018.055 %> https://waim.network/sites/crowston.syr.edu/files/SeeberEtAl_2018_MachinesAsTeammates.pdf %0 Journal Article %J Systematic Reviews %D 2018 %T Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR) %A Elaine Beller %A Justin Clark %A Guy Tsafnat %A Clive Adams %A Heinz Diehl %A Hans Lund %A Mourad Ouzzani %A Kristina Thayer %A James Thomas %A Tari Turner %A Jun Xia %A Karen Robinson %A Paul Glasziou %K automation %K Collaboration %K Systematic review %X 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 'Vienna Principles' 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. %B Systematic Reviews %I Springer %8 2018 %G eng %N 77 %9 Review %6 7 %R 10.1186/s13643-018-0740-7 %0 Journal Article %J Systematic Reviews %D 2018 %T Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR) %A Elaine Beller %A Justin Clark %A Guy Tsafnat %A Clive Adams %A Heinz Diehl %A Hans Lund %A Mourad Ouzzani %A Kristina Thayer %A James Thomas %A Tari Turner %A Jun Xia %A Karen Robinson %A Paul Glasziou %K science %B Systematic Reviews %V 7 %8 Jan-12-2018 %G eng %N 1 %R 10.1186/s13643-018-0740-7 %0 Journal Article %J JNCI: Journal of the National Cancer Institute %D 2018 %T Making Sure We Don’t Forget the Basics When Using Machine Learning %A Winn, Aaron N %A Neuner, Joan M %B JNCI: Journal of the National Cancer Institute %V 111 %P 529 - 530 %8 Sep-10-2019 %G eng %N 6 %R 10.1093/jnci/djy179 %0 Journal Article %J Jurnal Aplikasi Manajemen %D 2018 %T Managing talented worker in the era of new psychological contract %A Haryadi, Haryadi %A Anggraeni, Ade Irma %A Ibrahim, Daing Nasir %B Jurnal Aplikasi Manajemen %V 16 %P 20 - 26 %8 Jan-03-2018 %G eng %N 1 %R 10.21776/ub.jam.2018.016.01.03 %0 Journal Article %J BMJ Leader %D 2018 %T Medicine and the rise of the robots: a qualitative review of recent advances of artificial intelligence in health %A Loh, Erwin %B BMJ Leader %V 2 %P 59 - 63 %8 Apr-06-2020 %G eng %N 2 %R 10.1136/leader-2018-000071 %0 Journal Article %J AEA Papers and Proceedings %D 2018 %T A method to link advances in Artificial Intelligence to occupational abilities %A Felten, Edward W. %A Raj, Manav %A Seamans, Robert %B AEA Papers and Proceedings %V 108 %P 54 - 57 %8 Jan-01-2018 %G eng %R 10.1257/pandp.20181021 %0 Generic %D 2018 %T New education models for the future of work force %A Francesco Pastore %K industry 4.0; robotics; sequential versus dual education systems; human resources management and policy %I Global Labor Organization %8 10/2018 %G eng %U http://ftp.iza.org/pp143.pdf %0 Report %D 2018 %T The nordic future of work drivers, institutions, and politics %A Jon Erik Dølvik %A Johan Røed Steen %B The future of work: opportunities and challenges for the nordic models %I Nordic Council of Ministers %G eng %U https://norden.diva-portal.org/smash/get/diva2:1265618/FULLTEXT01.pdf %0 Report %D 2018 %T Occupational Classifications With A Machine Learning Approach %A Akina Ikudo %A Julia Lane %A Joseph Staudt %A Bruce A. Weinberg %K administrative data %K machine learning %K occupational classifications %K transaction data %K UMETRICS %B IZA DP No. 11738 %G eng %U https://www.iza.org/publications/dp/11738/occupational-classifications-a-machine-learning-approach %0 Magazine Article %D 2018 %T The OD imperative to add inclusion to the algorithms of artificial intelligence %A Frederick A. Miller %A Judith H. Katz %A Roger Gans %X 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. %B ResearchGate %8 01/2018 %G eng %U https://www.researchgate.net/publication/323830092_AI_x_I_AI2_The_OD_imperative_to_add_inclusion_to_the_algorithms_of_artificial_intelligence %0 Journal Article %J Proceedings of the International Conference on Business Excellence %D 2018 %T The operating system for the digital enterprise %A Anagnoste, Sorin %B Proceedings of the International Conference on Business Excellence %V 12 %P 54 - 69 %8 Jan-05-2018 %G eng %N 1 %R 10.2478/picbe-2018-0007 %0 Generic %D 2018 %T An overview of autonomous vehicles safety %X 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 “responsibility sensitive safety”, in order to provide the overall level of trust that the community is expecting from autonomous vehicles. %B IEEE %G eng %U https://ieeexplore.ieee.org/document/8353618 %0 Journal Article %J Journal of Participation and Employee Ownership %D 2018 %T Ownership when AI robots do more of the work and earn more of the income %A Freeman, Richard B. %B Journal of Participation and Employee Ownership %V 1 %P 74 - 95 %8 Nov-06-2018 %G eng %N 1 %R 10.1108/JPEO-04-2018-0015 %0 Journal Article %J Canadian Public Policy %D 2018 %T Paving the way for the future of work %A Anani, Namir %B Canadian Public Policy %P 1 - 10 %8 Mar-11-2019 %G eng %R 10.3138/cpp.2018-012 %0 Journal Article %D 2018 %T Platforms at work: Automated hiring platforms and other new intermediaries in the organization of work %A Ifeoma Ajunwa %A Daniel Greene %G eng %U http://dmgreene.net/wp-content/uploads/2018/09/Ajunwa-Greene-Platforms-at-Work-Accepted-Version.pdf %0 Journal Article %J Postmodern Openings %D 2018 %T The predictions on the future of labour are not grounded; some arguments for a bayesian approach %A Rotila, Viorel %B Postmodern Openings %V 9 %P 36 - 63 %8 Jan-09-2020 %G eng %N 3 %R 10.18662/po/35 %0 Journal Article %J npj Digital Medicine %D 2018 %T A principled machine learning framework improves accuracy of stage II colorectal cancer prognosis %A Dimitriou, Neofytos %A Arandjelović, Ognjen %A Harrison, David J. %A Caie, Peter D. %B npj Digital Medicine %V 1 %8 Jan-12-2018 %G eng %N 1 %R 10.1038/s41746-018-0057-x %0 Report %D 2018 %T The productivity j-curve: How intangibles complement general purpose technologies %A Brynjolfsson, Erik %A Rock, Daniel %A Syverson, Chad %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w25148 %0 Web Page %D 2018 %T Promethean AI uses artificial intelligence to help artists fill out game worlds %A Dean Takahashi %K AI use cases %B venturebeat.com %G eng %U https://venturebeat.com/2018/07/18/promethean-ai-uses-artificial-intelligence-to-help-artists-fill-out-game-worlds/ %0 Conference Proceedings %B 10th International RAIS Conference on Social Sciences and Humanities %D 2018 %T Recent advances in social & cognitive robotics and imminent ethical challenges %A Ali Meghdari %A Minoo Alemi %K ethics %B 10th International RAIS Conference on Social Sciences and Humanities %V 211 %G eng %U https://www.atlantis-press.com/proceedings/rais-18/25902731 %0 Generic %D 2018 %T Recommendations to improve the nation's workforce and labor market information system %B Workforce Information Advisory Council %8 01/2018 %G eng %U https://www.doleta.gov/wioa/wiac/docs/Second_Draft_of_the_WIAC_Final_Report.pdf %0 Journal Article %J education policy analysis archives %D 2018 %T Reflections on the meaning of automated education %A Coelho, Heitor %B education policy analysis archives %V 26 %P 115 %8 May-01-2018 %G eng %R 10.14507/epaa.26.3863 %0 Journal Article %J Competition & Change %D 2018 %T Reinventing capitalism to address automation: Sharing work to secure employment and income %A Rafi Khan, Shahrukh %B Competition & Change %V 22 %P 343 - 362 %8 Jan-08-2020 %G eng %N 4 %R 10.1177/1024529418783579 %0 Journal Article %J AI Magazine %D 2018 %T Reports of the Workshops Held at the Sixth AAAI Conference on Human Computation and Crowdsourcing %A Aroyo, Lora %A Dumitrache, Anca %A Jeffrey V Nickerson %A Lease, Matthew %A Michelucci, Pietro %B AI Magazine %V 39 %P 57–63 %G eng %0 Conference Paper %B 2018 2nd International Conference on Systems, Computing, and Applications2018 2nd International Conference on Systems, Computing, and Applications (SYSTCA 2018) %D 2018 %T Research on the application of artificial intelligence technology in human resource management %B 2018 2nd International Conference on Systems, Computing, and Applications2018 2nd International Conference on Systems, Computing, and Applications (SYSTCA 2018) %I Francis Academic Press %G eng %R 10.25236/systca.18.038 %0 Web Page %D 2018 %T Researchably's AI parsers medical research for pharmaceutical companies %A Kyle Wiggers %B venturebeat.com %8 10/2018 %G eng %U https://venturebeat.com/2018/10/02/researchablys-ai-parses-medical-research-for-pharmaceutical-companies/ %0 Conference Paper %B the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES '18 %D 2018 %T Rethinking AI strategy and policy as entangled super wicked problems %A Gruetzemacher, Ross %Y Furman, Jason %Y Marchant, Gary %Y Price, Huw %Y Rossi, Francesca %B the 2018 AAAI/ACM ConferenceProceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society - AIES '18 %I ACM Press %C New Orleans, LA, USANew York, New York, USA %P 122 - 122 %@ 9781450360128 %G eng %R 10.1145/3278721.3278746 %0 Journal Article %J Journal of Innovation in Health Informatics %D 2018 %T Robot Assisted Surgical Ward Rounds: Virtually Always There %A Stefanie M. Croghan %A Paul Carroll %A Sarah Reade %A Amy E Gillis %A Paul F. Ridgway %B Journal of Innovation in Health Informatics %V 25 %P 041 %8 Sep-03-2018 %G eng %N 1 %R 10.14236/jhi.v25i1.982 %0 Journal Article %J The Information Society %D 2018 %T Robot companions: A legal and ethical analysis %A Bertolini, Andrea %A Aiello, Giuseppe %B The Information Society %V 34 %P 130 - 140 %8 Mar-05-2020 %G eng %N 3 %R 10.1080/01972243.2018.1444249 %0 Journal Article %J Proceedings of the IEEE %D 2018 %T Robot revolution: Myth or reality %A Joel Trussell, H. %B Proceedings of the IEEE %V 106 %P 2095 - 2097 %8 Jan-12-2018 %G eng %N 12 %R 10.1109/JPROC.2018.2877520 %0 Journal Article %J Journal of Tax Reform %D 2018 %T Robot vs. tax inspector or how the fourth industrial revolution will change the tax system: a review of problems and solutions %A Vishnevsky, Valentine P. %A Chekina, Viktoriia D. %K blockchain %K cyber-physical technologies %K digitization %K taxes in Big Data %K taxes on cryptocurrencies %K taxes on digital goods %K taxes on robots %X 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'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 %B Journal of Tax Reform %V 4 %P 6 - 26 %8 Jan-01-2018 %G eng %U https://jtr.urfu.ru/en/archive/journal/95/article/1113/ %N 1 %R 10.15826/jtr.2018.4.1.042 %0 Journal Article %J Business & Information Systems Engineering %D 2018 %T Robotic process automation %A van der Aalst, Wil M. P. %A Bichler, Martin %A Heinzl, Armin %B Business & Information Systems Engineering %V 60 %P 269 - 272 %8 Jan-08-2018 %G eng %N 4 %R 10.1007/s12599-018-0542-4 %0 Journal Article %J Journal of Emerging Technologies in Accounting %D 2018 %T Robotic Process Automation for Auditing %A Moffitt, Kevin C. %A Rozario, Andrea M. %A Vasarhelyi, Miklos A. %B Journal of Emerging Technologies in Accounting %V 15 %P 1 - 10 %8 Jan-07-2018 %G eng %N 1 %R 10.2308/jeta-10589 %0 Journal Article %J The American Economist %D 2018 %T Robots and computers enhance us more than they replace us %A Diamond, Arthur M. %B The American Economist %P 056943451879267 %8 Oct-08-2018 %G eng %R 10.1177/0569434518792674 %0 Journal Article %J Organization Studies %D 2018 %T Robots and Organization Studies: Why Robots Might Not Want to Steal Your Job %A Fleming, Peter %K artificial intelligence %K bounded automation %K neoliberalism %K public organization studies %K Robotics %K unemployment %K work %X 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't in the near future. To explain why, some basic insights from organization studies can make a contribution. I propose the concept of 'bounded automation' 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. %B Organization Studies %7 2 %P 017084061876556 %8 04/2018 %G eng %U http://journals.sagepub.com/doi/10.1177/0170840618765568 %R 10.1177/0170840618765568 %0 Generic %D 2018 %T Robots worldwide: The impact of automation on employment and trade %A Francesco Carnonero %A Ekkehard Ernst %A Enzo Weber %K economics of automation %K Employment %K off-shoring %K re-shoring %K robot %K technology %B International Labour Office %8 10/2018 %G eng %U https://www.ilo.org/wcmsp5/groups/public/---dgreports/---inst/documents/publication/wcms_648063.pdf %0 Book %D 2018 %T The role of technological progress and structural change in the labour market %A Bosio, Giulio %A Cristini, Annalisa %E Bosio, Giulio %E Minola, Tommaso %E Origo, Federica %E Tomelleri, Stefano %I Springer International Publishing %C Cham %P 15 - 41 %@ 978-3-319-90547-1 %G eng %R 10.1007/978-3-319-90548-8_2 %0 Journal Article %J Journal of Monetary Economics %D 2018 %T Should we fear the robot revolution? %A Berg, Andrew %A Buffie, Edward F. %A Zanna, Luis-Felipe %B Journal of Monetary Economics %V 97 %P 117 - 148 %8 Jan-08-2018 %G eng %R 10.1016/j.jmoneco.2018.05.014 %0 Report %D 2018 %T Skill shift automation and the future of the workforce %A Jaccques Bughin %A Eric Hazan %A Susan Lund %A Peter Dahlstrom %A Anna Wiesinger %A Amresh Subramaniam %B McKinsey Global Institute %8 05/2018 %G eng %U https://www.mckinsey.com/featured-insights/future-of-work/skill-shift-automation-and-the-future-of-the-workforce %0 Book %D 2018 %T The social consequences of the digital revolution %A Basso, Pietro %A Chiaretti, Giuliana %A Krzywdzinski, Martin %A Gerber, Christine %A Evers, Maren %I Edizioni Ca' Foscari %C Venice %V 6 %@ 978-88-6969-274-1 %G eng %U 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/ %R 10.30687/2610-968910.30687/978-88-6969-273-410.30687/978-88-6969-273-4/008 %0 Journal Article %J BiD: textos universitaris de biblioteconomia i documentaci� %D 2018 %T Social machines and the Internet : What went wrong? %B BiD: textos universitaris de biblioteconomia i documentaci� %8 Jan-01-2018 %G eng %N 2018.41 %R 10.1344/BiD2018.41.8 %0 Journal Article %J The Information Society %D 2018 %T Social robots as cultural objects: The sixth dimension of dynamicity? %A Fortunati, Leopoldina %A Sarrica, Mauro %A Ferrin, Giovanni %A Brondi, Sonia %A Honsell, Furio %B The Information Society %V 34 %P 141 - 152 %8 Mar-05-2020 %G eng %N 3 %R 10.1080/01972243.2018.1444253 %0 Journal Article %J IEEE Technology and Society Magazine %D 2018 %T Socio-economic and legal impact of autonomous robotics and ai entities %A Broman, Morgan M. %A Finckenberg-Broman, Pamela %B IEEE Technology and Society Magazine %V 37 %P 70 - 79 %8 Jan-03-2018 %G eng %N 1 %R 10.1109/MTS.2018.2795120 %0 Journal Article %J Systems Research and Behavioral Science %D 2018 %T Sustainable skills for the world of work in the digital age %A Sousa, Maria José %A Wilks, Daniela %E Laszlo, Alexander %B Systems Research and Behavioral Science %V 35 %P 399 - 405 %8 Jan-07-2018 %G eng %N 4 %R 10.1002/sres.v35.410.1002/sres.2540 %0 Journal Article %J IEEE Intelligent Transportation Systems Magazine %D 2018 %T System architecture of a driverless electric car in the grand cooperative driving challenge %A Xu, Philippe %A Dherbomez, Gerald %A Hery, Elwan %A Abidli, Abderrahmen %A Bonnifait, Philippe %B IEEE Intelligent Transportation Systems Magazine %V 10 %P 47 - 59 %8 Jan-21-2018 %G eng %N 1 %R 10.1109/MITS.2017.2776135 %0 Journal Article %J Research Policy %D 2018 %T Technology and employment: Mass unemployment or job creation? Empirical evidence from European patenting firms %A Van Roy, Vincent %A Vértesy, Dániel %A Vivarelli, Marco %B Research Policy %V 47 %P 1762 - 1776 %8 Jan-11-2018 %G eng %N 9 %R 10.1016/j.respol.2018.06.008 %0 Journal Article %J Journal of Business Thought %D 2018 %T Technology, productivity and employment: an empirical analysis of indian industries %A Aggarwal, Suresh Chand %B Journal of Business Thought %V 9 %P 1 - 10 %8 Jan-04-2020 %G eng %R 10.18311/jbt/2018/21173 %0 Journal Article %J Journal of Evaluation in Clinical Practice %D 2018 %T Technology-induced bias in the theory of evidence-based medicine %A Eustace, Scott %B Journal of Evaluation in Clinical Practice %V 24 %P 945 - 949 %8 Jan-10-2018 %G eng %N 5 %R 10.1111/jep.12972 %0 Journal Article %J Telematics and Informatics %D 2018 %T Techno-unemployment: A framework for assessing the effects of information and communication technologies on work %A Garcia-Murillo, Martha %A MacInnes, Ian %A Bauer, Johannes M. %B Telematics and Informatics %V 35 %P 1863 - 1876 %8 Jan-10-2018 %G eng %N 7 %R 10.1016/j.tele.2018.05.013 %0 Conference Paper %B Thirty - n inth International Conference on Information Systems, %D 2018 %T Theorizing human and bot co - production effects on information quality %A Amber G. Young %A Amber G. Young %A Gerald C. Kane %B Thirty - n inth International Conference on Information Systems, %G eng %U https://icis2018postergallery.weebly.com/416-social-media-and-digital-collaboration.html %0 Journal Article %J The NewYork Times %D 2018 %T Is There a Smarter Path to Artificial Intelligence? Some Experts Hope So %A Steve Lohr %B The NewYork Times %G eng %U https://www.nytimes.com/2018/06/20/technology/deep-learning-artificial-intelligence.html %0 Journal Article %J European Scientific Journal ESJ %D 2018 %T This time it might be different: Analysis of the impact of digitalization on the labour market %A Lovergine, Saverio %A Pellero, Alberto %B European Scientific Journal ESJ %V 14 %8 Jul-12-2020 %G eng %N 36 %R 10.19044/esj.2018.v14n36p68 %0 Conference Paper %B Artificial General Intelligence (AGI) %D 2018 %T Towards a Sociological Conception of Artificial Intelligence %A Jakub Mlynar %A Hamed S. Alavi %A Himanshu Verma %A Lorenzo Cantoni %K artificial intelligence %K Social sciences %K Sociology %X 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's employment? We argue that such conceptual investigation is a crucial step for further empirical studies of phenomena related to AI'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. %B Artificial General Intelligence (AGI) %I Springer %G eng %R 10.1007/978-3-319-97676-1_13 %0 Conference Paper %B Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences %D 2018 %T Towards an understanding of how chatbots create value %A Stoeckli, Emanuel %A Uebernickel, Falk %A Brenner, Walter %Y Bui, Tung %B Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences %I Hawaii International Conference on System Sciences %G eng %R 10.24251/HICSS.2018.255 %0 Journal Article %J Texas A&M Journal of Property Law %D 2018 %T Transparency and fairness in machine learning applications %A Jim Shook %A Robyn Smith %A Alex Antonio %B Texas A&M Journal of Property Law %V 4 %G eng %U https://scholarship.law.tamu.edu/cgi/viewcontent.cgi?article=1079&context=journal-of-property-law %0 Journal Article %J Journal of Information, Communication and Ethics in Society %D 2018 %T An Uber ethical dilemma: examining the social issues at stake %A Chee, Florence M. %B Journal of Information, Communication and Ethics in Society %V 16 %P 261 - 274 %8 Jan-08-2019 %G eng %U 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 %N 3 %R 10.1108/JICES-03-2018-0024 %0 Conference Paper %B the 2018 CHI ConferenceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18 %D 2018 %T Understanding Chatbot-mediated Task Management %A Toxtli, Carlos %A Monroy-Hernández, Andrés %A Cranshaw, Justin %Y Mandryk, Regan %Y Hancock, Mark %Y Perry, Mark %Y Cox, Anna %B the 2018 CHI ConferenceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18 %I ACM Press %C Montreal QC, CanadaNew York, New York, USA %P 1 - 6 %@ 9781450356206 %G eng %R 10.1145/317357410.1145/3173574.3173632 %0 Book %D 2018 %T Understanding tasks, automation, and the national health service %A Willis, Matt %A Meyer, Eric T. %E Chowdhury, Gobinda %E McLeod, Julie %E Gillet, Val %E Willett, Peter %I Springer International Publishing %C Cham %V 10766 %P 544 - 549 %@ 978-3-319-78104-4 %G eng %R 10.1007/978-3-319-78105-1_60 %0 Journal Article %J Bioethics %D 2018 %T The value of work: Addressing the future of work through the lens of solidarity %A Prainsack, Barbara %A Buyx, Alena %E Buyx, Alena %E Prainsack, Barbara %B Bioethics %V 32 %P 585 - 592 %8 Jan-11-2018 %G eng %N 9 %R 10.1111/bioe.12507 %0 Generic %D 2018 %T When Will AI Exceed Human Performance? Evidence from AI Experts %A Katja Grace %A John Salvatier %A Allan Dafoe %A Baobao Zhang %A Owain Evans %G eng %U https://jair.org/index.php/jair/article/download/11222/26431/ %0 Journal Article %J BMC Health Services Research %D 2018 %T Will artificial intelligence solve the human resource crisis in healthcare? %A Meskó, Bertalan %A Hetényi, Gergely %A Győrffy, Zsuzsanna %B BMC Health Services Research %V 18 %8 Jan-12-2018 %G eng %N 1 %R 10.1186/s12913-018-3359-4 %0 Journal Article %J Frontiers in Psychology %D 2018 %T Work and organizational psychology looks at the fourth industrial revolution: How to support workers and organizations? %A Ghislieri, Chiara %A Molino, Monica %A Cortese, Claudio G. %B Frontiers in Psychology %V 9 %8 Apr-11-2020 %G eng %R 10.3389/fpsyg.2018.02365 %0 Conference Paper %B iConference %D 2018 %T Work that Enables Care: Understanding Tasks, Automation, and the National Health Service %A Matt WIllis %A Eric T. Meyer %K automation %K Ethnography %K Primary care %K Sociotechnical %X 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. %B iConference %I Springer %G eng %R 10.1007/978-3-319-78105-1_60 %0 Journal Article %J Information and Organization %D 2018 %T Working and organizing in the age of the learning algorithm %A Samer Faraj %A Stella Pachidi %A Karla Sayegh %X 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. %B Information and Organization %I Elsevier %V 28 %G eng %& 62-70 %R 10.1016/j.inforandorg.2018.02.005 %0 Journal Article %J Information and Organization %D 2018 %T Working and organizing in the age of the learning algorithm %A Faraj, Samer %A Pachidi, Stella %A Sayegh, Karla %B Information and Organization %V 28 %P 62 - 70 %8 Jan-03-2018 %G eng %N 1 %R 10.1016/j.infoandorg.2018.02.005 %0 Web Page %D 2017 %T 6 areas of AI and machine learning to watch closely %A Nathan Benaich %B Medium %G eng %U https://medium.com/@NathanBenaich/6-areas-of-artificial-intelligence-to-watch-closely-673d590aa8aa %0 Web Page %D 2017 %T 9 IT projects primed for machine learning %A Mary Branscombe %B CIO %8 10/2017 %G eng %U https://www.cio.com/article/3231650/9-it-projects-primed-for-machine-learning.html %0 Book Section %D 2017 %T Agents as collaborating team members %A Abhijit V. Deshmukh %A Sara A.McComb %A Christian Wernz %K bots %I EBSCO %8 09/2017 %G eng %U https://www.taylorfrancis.com/books/e/9781315593166/chapters/10.1201/9781315593166-7 %0 Web Page %D 2017 %T AI AND THE GHOST IN THE MACHINE %A Cameron Coward %B HACKADAY %G eng %U http://hackaday.com/2017/02/06/ai-and-the-ghost-in-the-machine/ %0 Web Page %D 2017 %T AI can take over our mundane tasks %A Gordon Ritter %X

Here’s how human workers can learn new, more stimulating skills

%B vox %8 10/2017 %G eng %U https://www.vox.com/2017/10/18/16492156/coaching-cloud-future-work-jobs-artificial-intelligence-ai-enterprise-employee-training %0 Newspaper Article %B Science %D 2017 %T The AI detectives %A Voosen, Paul %B Science %V 357 %P 22 - 27 %8 Jul-07-2017 %G eng %N 6346 %R 10.1126/science.357.6346.22 %0 Web Page %D 2017 %T AI has become so popular in picking stocks that it’s become ineffective %A Ryan Vlastelica %B MarketWatch %8 10/2017 %G eng %U https://www.marketwatch.com/story/ai-has-become-so-popular-in-picking-stocks-that-its-become-ineffective-2017-10-06 %0 Journal Article %J Science %D 2017 %T AI in Action: Combing the genome for the roots of autism %A Pennisi, Elizabeth %B Science %V 357 %P 25 - 25 %8 Jul-07-2017 %G eng %N 6346 %R 10.1126/science.357.6346.25 %0 Journal Article %J Science %D 2017 %T AI in Action: Machines that make sense of the sky %A Sokol, Joshua %B Science %V 357 %P 26 - 26 %8 Jul-07-2017 %G eng %N 6346 %R 10.1126/science.357.6346.26 %0 Journal Article %J Communications of the ACM %D 2017 %T AI in contact centers %A Kirkpatrick, Keith %B Communications of the ACM %V 60 %P 18 - 19 %8 Dec-07-2018 %G eng %N 8 %R 10.1145/312734310.1145/3105442 %0 Journal Article %J salesforce %D 2017 %T AI will create 800,000 jobs and $1.1 trillion revenue by 2021: Salesforce %A Tas Bindi %B salesforce %8 06/2017 %G eng %U https://www.salesforce.com/company/news-press/press-releases/2017/06/170614/ %9 AI %0 Journal Article %J Information, Communication & Society %D 2017 %T Algorithmic IF  … THEN rules and the conditions and consequences of power %A Neyland, Daniel %A Möllers, Norma %B Information, Communication & Society %V 20 %P 45 - 62 %8 Feb-01-2017 %G eng %N 1 %R 10.1080/1369118X.2016.1156141 %0 Journal Article %J Information, Communication & Society %D 2017 %T The algorithmic imaginary: Exploring the ordinary affects of Facebook algorithms %A Bucher, Taina %B Information, Communication & Society %V 20 %P 30 - 44 %8 Feb-01-2017 %G eng %N 1 %R 10.1080/1369118X.2016.1154086 %0 Journal Article %J Information, Communication & Society %D 2017 %T Algorithmically recognizable: Santorum’s google problem, and google’s santorum problem %A Gillespie, Tarleton %B Information, Communication & Society %V 20 %P 63 - 80 %8 Feb-01-2017 %G eng %N 1 %R 10.1080/1369118X.2016.1199721 %0 Journal Article %J Information, Communication & Society %D 2017 %T Algorithms (and the) everyday %A Willson, Michele %B Information, Communication & Society %V 20 %P 137 - 150 %8 Feb-01-2017 %G eng %N 1 %R 10.1080/1369118X.2016.1200645 %0 Journal Article %J AEIdeas %D 2017 %T Anxiety about automation and jobs: Will we see anti-tech laws? %A James Pethokoukis %B AEIdeas %8 07/2017 %G eng %U https://www.aei.org/economics/anxiety-about-automation-and-jobs-will-we-see-anti-tech-laws/ %9 economics %0 Conference Paper %B Scientific Methods in Academic Research and Teaching International Conference %D 2017 %T Are We Safe Enough in the Future of Artificial Intelligence? A Discussion on Machine Ethics and Artificial Intelligence Safety %A Utku Köse %K artificial intelligence %K artificial intelligence safety %K future of artificial intelligence %K machine ethics %K machine learning %X 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 'Are we safe enough in the future of Artificial Intelligence?'. In detail, the discussion includes a comprehensive focus on 'dystopic' scenarios, enables interested researchers to think about some 'moral dilemmas' 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 %B Scientific Methods in Academic Research and Teaching International Conference %P 184-197 %G eng %0 Generic %D 2017 %T Artificial intelligence and the modern productivity paradox: a clash of expectations and statistics %A Erik Brynjolfsson %A Daniel Rock %A Chad Syverson %K economics of automation %B National bureau of economic research %8 11/2017 %G eng %U http://www.nber.org/papers/w24001 %0 Book %B A Chapman & Hall Book %D 2017 %T Artificial Intelligence and the two singularities %A Calum Chace %B A Chapman & Hall Book %7 1st %I EBSCO %8 08/2018 %G eng %U https://www.amazon.com/Artificial-Intelligence-Singularities-Chapman-Robotics/dp/0815368534 %0 Report %D 2017 %T Artificial Intelligence For Social Good %A Gregory D. Hager %A Ann Drobnis %A Fei Fang %A Rayid Ghani %A Amy Greenwald %A Terah Lyons %A David C. Parkes %A Jason Schultz %A Suchi Saria %A Stephen F. Smith %A Milind Tambe %G eng %U https://cra.org/ccc/wp-content/uploads/sites/2/2016/04/AI-for-Social-Good-Workshop-Report.pdf %0 Journal Article %J Stroke and Vascular Neurology %D 2017 %T Artificial intelligence in healthcare: past, present and future %A Jiang, Fei %A Jiang, Yong %A Zhi, Hui %A Dong, Yi %A Li, Hao %A Ma, Sufeng %A Wang, Yilong %A Dong, Qiang %A Shen, Haipeng %A Wang, Yongjun %B Stroke and Vascular Neurology %V 2 %P 230 - 243 %8 Aug-12-2018 %G eng %N 4 %R 10.1136/svn-2017-000101 %0 Journal Article %J Science %D 2017 %T Artificial intelligence in research %A Musib, Mrinal %A Wang, Feng %A Tarselli, Michael A. %A Yoho, Rachel %A Yu, Kun-Hsing %A Andrés, Rigoberto Medina %A Greenwald, Noah F. %A Pan, Xubin %A Lee, Chien-Hsiu %A Zhang, Jian %A Dutton-Regester, Ken %A Johnston, Jake Wyatt %A Sharafeldin, Icell Mahmoud %B Science %V 357 %P 28 - 30 %8 Jul-07-2017 %G eng %N 6346 %R 10.1126/science.357.6346.28 %0 Report %D 2017 %T Artificial Intelligence Index %A Yoav Shoham %A Raymond Perrault %A Erik Brynjolfsson %A Jack Clark %G eng %U https://aiindex.org/2017-report.pdf %0 Magazine Article %D 2017 %T Artificial Intelligence: The next digital frontier %A Jaccques Bughin %A Eric Hazan %A Sree Ramaswamy %A Michael Chui %A Tera Allas %A Peter Dahlstrom %A Nicolaus Henke %A Monica Trench %B McKinsey Global Institute %G eng %U 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 %0 Web Page %D 2017 %T As amazon pushes forward with robots, workers find new roles %A Nick Wingfield %B The New York Times %8 10/2017 %G eng %U https://www.nytimes.com/2017/09/10/technology/amazon-robots-workers.html %0 Journal Article %J Journal of Safety Research %D 2017 %T Assessing drivers' response during automated driver support system failures with non-driving tasks %A Shen, Sijun %A Neyens, David M. %B Journal of Safety Research %V 61 %P 149 - 155 %8 Jan-06-2017 %G eng %R 10.1016/j.jsr.2017.02.009 %0 Journal Article %J Journal of Southeast Asian Economies %D 2017 %T Automation, computerisation and future employment in Singapore %A King Fuei Lee %K economics of automation %B Journal of Southeast Asian Economies %V 34 %G eng %U https://mpra.ub.uni-muenchen.de/79961/ %6 2 %0 Journal Article %J Southeast Asian Economies %D 2017 %T Automation, computerization and future employment in Singapore %A Fuei, Lee King %B Southeast Asian Economies %V 34 %P 388 - 399 %8 Jul-08-2019 %G eng %N 2 %R 10.1355/ae34-2h %0 Conference Proceedings %B Workshop on Engineering Applications (WEA 2017): Applied Computer Sciences in Engineering %D 2017 %T Automation of a Business Process Using Robotic Process Automation (RPA): A Case Study %A Aguirre, Santiago %A Rodriguez, Alejandro %E Figueroa-García, Juan Carlos %E López-Santana, Eduyn Ramiro %E Villa-Ramírez, José Luis %E Ferro-Escobar, Roberto %B Workshop on Engineering Applications (WEA 2017): Applied Computer Sciences in Engineering %I Springer International Publishing %C Cham %V 742 %P 65 - 71 %@ 978-3-319-66962-5 %G eng %R 10.1007/978-3-319-66963-2_7 %0 Journal Article %J Innovation %D 2017 %T Big data and organizational design – the brave new world of algorithmic management and computer augmented transparency %A Schildt, Henri %B Innovation %V 19 %P 23 - 30 %8 Feb-01-2017 %G eng %N 1 %R 10.1080/14479338.2016.1252043 %0 Book %D 2017 %T Big Data in Organizations and the Role of Human Resource Management %A Peter Lang %G eng %U https://www.jstor.org/stable/j.ctv9hj9z6.1 %0 Conference Proceedings %B Hawai'i International Conference on System Sciences %D 2017 %T Blending machine and human learning processes %A Kevin Crowston %A Carsten Østerlund %A Lee, Tae Kyoung %X

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.

%B Hawai'i International Conference on System Sciences %G eng %U http://hdl.handle.net/10125/41159 %R 10.24251/HICSS.2017.009 %> https://waim.network/sites/crowston.syr.edu/files/training%20v3%20to%20share_0.pdf %0 Magazine Article %D 2017 %T Can ford turn itself find a tech company %A Kevin Roose %B nytimes %G eng %U https://www.nytimes.com/interactive/2017/11/09/magazine/tech-design-autonomous-future-cars-detroit-ford.html %0 Journal Article %J Academy of Management Discoveries %D 2017 %T The changing nature of work: Careers, identities, and work lives in the 21 century %A Barley, Stephen R. %A Bechky, Beth A. %A Milliken, Frances J. %B Academy of Management Discoveries %V 3 %P 111 - 115 %8 Jan-06-2017 %G eng %N 2 %R 10.5465/amd.2017.0034 %0 Conference Proceedings %B CASCON '17 Proceedings of the 27th Annual International Conference on Computer Science and Software Engineering %D 2017 %T Chatbots as assistants, an architectural framework %A Adam Di Prospera %A Nojan norouzi %A Morios Fokaefs %A Marin Litoiu %B CASCON '17 Proceedings of the 27th Annual International Conference on Computer Science and Software Engineering %G eng %U https://dl.acm.org/citation.cfm?id=3172805 %0 Journal Article %J Computers in Human Behavior %D 2017 %T Comparing the initial human-human and human-AI social interactions %A Mou, Yi %A Xu, Kun %B Computers in Human Behavior %V 72 %P 432 - 440 %8 Jan-07-2017 %G eng %R 10.1016/j.chb.2017.02.067 %0 Journal Article %J Journal of the Japanese and International Economies %D 2017 %T Computer technology and probable job destructions in Japan: An evaluation %A David, Benjamin %B Journal of the Japanese and International Economies %V 43 %P 77 - 87 %8 Jan-03-2017 %G eng %R 10.1016/j.jjie.2017.01.001 %0 Journal Article %J Information, Communication & Society %D 2017 %T Computing brains: Learning algorithms and neurocomputation in the smart city %A Williamson, Ben %B Information, Communication & Society %V 20 %P 81 - 99 %8 Feb-01-2017 %G eng %N 1 %R 10.1080/1369118X.2016.1181194 %0 Journal Article %J Science %D 2017 %T The cyberscientist %A Bohannon, John %B Science %V 357 %P 18 - 21 %8 Jul-07-2017 %G eng %N 6346 %R 10.1126/science.357.6346.18 %0 Conference Paper %B the 2017 ACM ConferenceProceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW '17 %D 2017 %T Data tracking in search of workflows %A Holten Møller, Naja L. %A Bjørn, Pernille %A Villumsen, Jonas Christoffer %A Hancock, Tine C. Hansen %A Aritake, Toshimitsu %A Tani, Shigeyuki %Y Lee, Charlotte P. %Y Poltrock, Steve %Y Barkhuus, Louise %Y Borges, Marcos %Y Kellogg, Wendy %B the 2017 ACM ConferenceProceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW '17 %I ACM Press %C Portland, Oregon, USANew York, New York, USA %P 2153 - 2165 %@ 9781450343350 %G eng %R 10.1145/2998181.2998296 %0 Journal Article %J The Journal of Strategic Information Systems %D 2017 %T Datification, organizational strategy, and is research: What’s the score? %A Markus, M. Lynne %B The Journal of Strategic Information Systems %V 26 %P 233 - 241 %8 Jan-09-2017 %G eng %N 3 %R 10.1016/j.jsis.2017.08.003 %0 Journal Article %J The Journal of Strategic Information Systems %D 2017 %T Debating big data: A literature review on realizing value from big data %A Günther, Wendy Arianne %A Rezazade Mehrizi, Mohammad H. %A Huysman, Marleen %A Feldberg, Frans %B The Journal of Strategic Information Systems %V 26 %P 191 - 209 %8 Jan-09-2017 %G eng %N 3 %R 10.1016/j.jsis.2017.07.003 %0 Journal Article %J Scientific Reports %D 2017 %T A deep learning approach for quantifying tumor extent %A Cruz-Roa, Angel %A Gilmore, Hannah %A Basavanhally, Ajay %A Feldman, Michael %A Ganesan, Shridar %A Shih, Natalie N.C. %A Tomaszewski, John %A González, Fabio A. %A Madabhushi, Anant %B Scientific Reports %V 7 %8 Jan-06-2017 %G eng %N 1 %R 10.1038/srep46450 %0 Journal Article %J Briefings in Bioinformatics %D 2017 %T Deep learning for healthcare: review, opportunities and challenges %A Miotto, Riccardo %A Wang, Fei %A Wang, Shuang %A Jiang, Xiaoqian %A Joel T. Dudley %B Briefings in Bioinformatics %V 19 %P 1236 - 1246 %8 Jun-05-2017 %G eng %N 6 %R 10.1093/bib/bbx044 %0 Web Page %D 2017 %T DeepMind just published a mind blowing paper: PathNet %A Théo Szymkowiak %B Medium %G eng %U https://medium.com/mcgill-artificial-intelligence-review/deepmind-just-published-a-mind-blowing-paper-pathnet-f72b1ed38d46 %0 Journal Article %J Nature %D 2017 %T Dermatologist-level classification of skin cancer with deep neural networks %A Esteva, Andre %A Kuprel, Brett %A Novoa, Roberto A %A Ko, Justin %A Swetter, Susan M %A Blau, Helen M %A Thrun, Sebastian %B Nature %V 542 %P 115–118 %G eng %9 Journal Article %0 Journal Article %J AI & SOCIETY %D 2017 %T Digital technologies and artificial intelligence’s present and foreseeable impact on lawyering, judging, policing and law enforcement %A Nissan, Ephraim %B AI & SOCIETY %V 32 %P 441 - 464 %8 Jan-08-2017 %G eng %N 3 %R 10.1007/s00146-015-0596-5 %0 Journal Article %J Economies %D 2017 %T Do technological innovations affect unemployment? Some empirical evidence from European countries %A Matuzeviciute, Kristina %A Butkus, Mindaugas %A Karaliute, Akvile %B Economies %V 5 %P 48 %8 Jan-12-2017 %G eng %N 4 %R 10.3390/economies5040048 %0 Newspaper Article %B Wall Street Journal %D 2017 %T Elon Musk Lays Out Worst-Case Scenario for AI Threat %A Tim Higgins %B Wall Street Journal %G eng %U https://www.wsj.com/articles/elon-musk-warns-nations-governors-of-looming-ai-threat-calls-for-regulations-1500154345 %0 Thesis %B Administration, Economics %D 2017 %T An empirical analysis of the impacts of robotization on employment in the Norwegian manufacturing industry %A Fredrik Grøndahl %A Gina Hegland Eriksen %X 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. %B Administration, Economics %G eng %U https://www.semanticscholar.org/paper/Will-robots-replace-us-%3A-an-Empirical-analysis-of-Gr%C3%B8ndahl-Eriksen/e4e22bf2498e42d6308d81cc7483b5a0b8ba48e7 %9 master thesis %0 Journal Article %J The IPPR Commission on Economic Justice %D 2017 %T Employment, inequality and ethics in the digital age %A Mathew Lawrence %A Carys Roberts %A Loren King %B The IPPR Commission on Economic Justice %8 12/2017 %G eng %U https://www.ippr.org/publications/managing-automation %0 Journal Article %J Frontiers in Robotics and AI %D 2017 %T Empowerment As Replacement for the Three Laws of Robotics %A Salge, Christoph %A Polani, Daniel %B Frontiers in Robotics and AI %V 4 %8 May-06-2019 %G eng %R 10.3389/frobt.2017.00025 %0 Generic %D 2017 %T Evaluating Assessments in the Age of Big Data and AI %A Nigel Guenole %A Sheri Feinzig %B IBM Talent Management Solutions %G eng %U https://www.ibm.com/downloads/cas/D5GQD70R %0 Thesis %B Employment and wage effects %D 2017 %T Evaluating the effects of industrial robots on the European labour market %A Elena Natalie %A Cagnol Hveem %K economics of automation %B Employment and wage effects %V Bergen, Fall, 2017 %G eng %U https://pdfs.semanticscholar.org/4e19/3a0a02315803d799520b094cce36a1888a94.pdf %0 Conference Paper %B Proceedings of the CHI Conference on Human Factors in Computing Systems %D 2017 %T Examining crowd work and gig work through the historical lens of piecework %A Alkhatib, Ali %A Michael S. Bernstein %A Levi, Margaret %B Proceedings of the CHI Conference on Human Factors in Computing Systems %I ACM %P 4599-4616 %@ 1450346553 %G eng %9 Conference Proceedings %0 Journal Article %J Computers in Human Behavior %D 2017 %T An experimental comparison of Chatbot and Human task partners %A Fryer, Luke K. %A Ainley, Mary %A Thompson, Andrew %A Gibson, Aaron %A Sherlock, Zelinda %B Computers in Human Behavior %V 75 %P 461 - 468 %8 Jan-10-2017 %G eng %R 10.1016/j.chb.2017.05.045 %0 Journal Article %J The Journal of Strategic Information Systems %D 2017 %T Exploring the tension between transparency and datification effects of open government IS through the lens of Complex Adaptive Systems %A Marjanovic, Olivera %A Cecez-Kecmanovic, Dubravka %B The Journal of Strategic Information Systems %V 26 %P 210 - 232 %8 Jan-09-2017 %G eng %N 3 %R 10.1016/j.jsis.2017.07.001 %0 Journal Article %J Futures %D 2017 %T The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms %A Makridakis, Spyros %B Futures %V 90 %P 46 - 60 %8 Jan-06-2017 %G eng %R 10.1016/j.futures.2017.03.006 %0 Book %D 2017 %T The Frontiers of MACHINE LEARNING %A Lisa Casola %G eng %U https://www.nap.edu/read/25021/chapter/5 %0 Journal Article %J Technological Forecasting and Social Change %D 2017 %T The future of employment: How susceptible are jobs to computerisation? %A Frey, Carl Benedikt %A Osborne, Michael A. %B Technological Forecasting and Social Change %V 114 %P 254 - 280 %8 Jan-01-2017 %G eng %R 10.1016/j.techfore.2016.08.019 %0 Report %D 2017 %T The future of skills employment in 2030 %K consulting reports %B Pearson %G eng %U https://futureskills.pearson.com/research/assets/pdfs/technical-report.pdf %0 Magazine Article %D 2017 %T A future that works: Automation, employment and productivity %A James Manyika %A Michael Chui %A Mehdi Miremadi %A Jaccques Bughin %A Katy George %A Paul Willmott %A Martin Dewhurst %B McKinsey Global Institute %G eng %U https://www.mckinsey.com/mgi/overview %0 Journal Article %J Health and Technology %D 2017 %T Google DeepMind and healthcare in an age of algorithms %A Powles, Julia %A Hodson, Hal %B Health and Technology %V 7 %P 351 - 367 %8 Jan-12-2017 %G eng %N 4 %R 10.1007/s12553-017-0179-1 %0 Journal Article %J Classical and Quantum Gravity %D 2017 %T Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science %A Michael Zevin %A Scott Coughlin %A Sara Bahaadini %A Emre Besler %A Neda Rohani %A Sarah Allen %A Miriam Cabero %A Kevin Crowston %A Aggelos Katsaggelos %A Shane Larson %A Tae Kyoung Lee %A Chris Lintott %A Tyson Littenberg %A Andrew Lundgren %A Carsten Oesterlund %A Joshua Smith %A Laura Trouille %A Vicky Kalogera %B Classical and Quantum Gravity %V 34 %P 064003 %G eng %9 Journal Article %R 10.1088/1361-6382/aa5cea %0 Web Page %D 2017 %T A History of Deep Learning %A Andrew Fogg %G eng %U https://www.import.io/post/history-of-deep-learning/ %0 Magazine Article %D 2017 %T House gets serious about driverless cars %A Melanie Zanona %B The Hill %G eng %U https://thehill.com/policy/transportation/344141-driverless-car-bill-speeds-through-house %0 Web Page %D 2017 %T How AI is streamlining marketing and sales %A Brad Power %K AI use cases %B hbr.com %8 06/2017 %G eng %U https://hbr.org/2017/06/how-ai-is-streamlining-marketing-and-sales %0 Journal Article %J Journal of Emerging Technologies in Accounting %D 2017 %T How automation is changing auditing %A Kokina, Julia %A Davenport, Thomas H. %B Journal of Emerging Technologies in Accounting %V 14 %P 115 - 122 %8 Jan-03-2017 %G eng %N 1 %R 10.2308/jeta-51730 %0 Magazine Article %D 2017 %T How big data is empowering AI and machine learning at scale %A Randy Bean %K data and analytics %B MIT Slogan Management Review %8 05/2017 %G eng %U https://sloanreview.mit.edu/article/how-big-data-is-empowering-ai-and-machine-learning-at-scale/ %0 Magazine Article %D 2017 %T How can architects adapt to the coming age of AI? %A Phil Bernstein %B The Architects Newspaper %G eng %U https://archpaper.com/2017/11/architects-adapt-coming-ai/ %0 Magazine Article %D 2017 %T How computers will replace your doctor? %A Pascal-Emmanuel Gobry %B The Week %G eng %U https://theweek.com/articles/441528/how-computers-replace-doctor %0 Report %D 2017 %T How fortune 500 firms are adopting online freelancing platforms %A Greetje F. Corporaal %A Vili Lehdonvirta %B Oxford Internet Institute %I University of Oxford %G eng %U https://www.oii.ox.ac.uk/publications/platform-sourcing.pdf %0 Journal Article %J IZA World of Labor %D 2017 %T How is new technology changing job design? %A Gibbs, Michael %B IZA World of Labor %8 Jan-01-2017 %G eng %R 10.15185/izawol.344 %0 Journal Article %J Gale Academic Onefile %D 2017 %T How the internet of people will change the future of work %A Anna Tavis %B Gale Academic Onefile %I Human Resource Planning Society %V 40 %G eng %N 3 %9 People & Strategy %0 Conference Paper %B Proceedings of the Conference on Computer supported Cooperative Work and Social Media %D 2017 %T Huddler: Convening stable and familiar crowd teams despite unpredictable availability %A Salehi, Niloufar %A McCabe, Andrew %A Valentine, Melissa %A Michael S. Bernstein %B Proceedings of the Conference on Computer supported Cooperative Work and Social Media %G eng %9 Conference Proceedings %0 Journal Article %J Information, Communication & Society %D 2017 %T ‘Hypernudge’: Big Data as a mode of regulation by design %A Yeung, Karen %B Information, Communication & Society %V 20 %P 118 - 136 %8 Feb-01-2017 %G eng %N 1 %R 10.1080/1369118X.2016.1186713 %0 Journal Article %J Convergence: The International Journal of Research into New Media Technologies %D 2017 %T Imagining the thinking machine %A Natale, Simone %A Ballatore, Andrea %B Convergence: The International Journal of Research into New Media Technologies %P 135485651771516 %8 Aug-06-2018 %G eng %R 10.1177/1354856517715164 %0 Journal Article %J The Journal of Financial Perspectives: Insurance %D 2017 %T Impact of robotics, RPA and AI on the insurance industry %A Chris Lamberton %A Damiano Brigo %A Dave Hoy %B The Journal of Financial Perspectives: Insurance %G eng %U 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 %0 Book %D 2017 %T Information Technology and the U.S. Workforce %I National Academies Press %C Washington, D.C. %@ 978-0-309-45402-5 %G eng %U https://www.nap.edu/catalog/24649 %R 10.17226/24649 %0 Report %D 2017 %T Jobs lost, jobs gained: Workforce transactions in a time of automation %A James Manyika %A Susan Lund %A Michael Chui %A Jonathan Woetzel %A Ryan Ko %A Saurabh Sanghvi %A Parul Batra %A Jacques Bughin %K consulting reports %B McKinsey Global Institute %G eng %U 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 %0 Web Page %D 2017 %T Machine Learning to Detect Anomalies from Application Logs %A Adwait Bhave %B Druva %G eng %U https://www.druva.com/blog/machine-learning-detect-anomalies-application-logs/ %0 Newspaper Article %B The New York Times %D 2017 %T Meet the people who train the robots to do their own jobs %A Daisuke Wakabayashi %B The New York Times %G eng %U https://nyti.ms/2paCS5X %0 Report %D 2017 %T A new chart conclusively proves that automation is a serious threat %A Scott Santens %8 11/2017 %G eng %U https://futurism.com/new-chart-proves-automation-serious-threat %9 Robots & Machines %0 Journal Article %J Academy of Management Perspectives %D 2017 %T Of robots, Artificial Intelligence, and work %A Phan, Phillip %A Wright, Michael %A Lee, Soo-Hoon %B Academy of Management Perspectives %V 31 %P 253 - 255 %8 Jan-11-2017 %G eng %N 4 %R 10.5465/amp.2017.0199 %0 Journal Article %J Journal of Applied Psychology %D 2017 %T One hundred years of work design research: Looking back and looking forward %A Parker, Sharon K. %A Morgeson, Frederick P. %A Johns, Gary %B Journal of Applied Psychology %V 102 %P 403 - 420 %8 Jan-01-2017 %G eng %N 3 %R 10.1037/apl0000106 %0 Book %D 2017 %T Oxford research encyclopedia of psychology %A Van den Broeck, Anja %A Parker, Sharon K. %A Van den Broeck, Anja %A Parker, Sharon K. %I Oxford University Press %G eng %U \ %R 10.1093/acrefore/9780190236557.013.15 %0 Conference Paper %B Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing %D 2017 %T Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving %A Malone, Thomas W. %A Jeffrey V Nickerson %A Laubacher, Robert J. %A Fisher, Laur Hesse %A de Boer, Patrick %A Han, Yue %A Towne, W. Ben %K climate change %K collective intelligence %K contest webs %K contests %K Coordination %K incentives %K knowledge reuse %B Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing %I ACM %C New York, NY, USA %P 1661–1674 %@ 978-1-4503-4335-0 %G eng %U http://doi.acm.org/10.1145/2998181.2998343 %R 10.1145/2998181.2998343 %0 Report %D 2017 %T Rapid Evidence Review: Impact of artificial intelligence, robotics and automation technologies on work %A Donald Hislop %A Crispin Coombs %A Stanimira Taneva %A Sarah Barnard %X The CIPD and Loughborough University’s report gathers the evidence and insights on emerging technology at work and explores the ethical implications of how we’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? %I Chartered Institute of Personnel and Development %C London, United Kingdom %G eng %U https://www.cipd.co.uk/knowledge/work/technology/artificial-intelligence-workplace-impact %0 Book %D 2017 %T Refining the concept of scientific inference when working with big data %E Wender, Ben A. %I National Academies Press %C Washington, D.C. %@ 978-0-309-45444-5 %G eng %R 10.17226/24654 %0 Journal Article %J Academy of Management Annals %D 2017 %T A review and synthesis of the individual work performance literature %A Carpini, Joseph A. %A Parker, Sharon K. %A Griffin, Mark A. %B Academy of Management Annals %V 11 %P 825 - 885 %8 Jan-06-2017 %G eng %N 2 %R 10.5465/annals.2015.0151 %0 Journal Article %J Economics Letters %D 2017 %T Revisiting the risk of automation %A Arntz, Melanie %A Gregory, Terry %A Zierahn, Ulrich %B Economics Letters %V 159 %P 157 - 160 %8 Jan-10-2017 %G eng %R 10.1016/j.econlet.2017.07.001 %0 Journal Article %J Futures %D 2017 %T The rise of technological unemployment and its implications on the future macroeconomic landscape %A Kim, Young Joon %A Kim, Kyungsoo %A Lee, SuKyoung %B Futures %V 87 %P 1 - 9 %8 Jan-03-2017 %G eng %R 10.1016/j.futures.2017.01.003 %0 Conference Paper %B Journal of science communication %D 2017 %T Robots, ai, and the question of 'e-persons' %A Michael zollosy %K bots %K Public perception of science and technology %K Public understanding of science and technology %K Science and policy-making %B Journal of science communication %8 07/2017 %G eng %U http://eprints.whiterose.ac.uk/124830/ %0 Journal Article %J Information, Communication & Society %D 2017 %T Scrutinizing an algorithmic technique: the Bayes classifier as interested reading of reality %A Rieder, Bernhard %B Information, Communication & Society %V 20 %P 100 - 117 %8 Feb-01-2017 %G eng %N 1 %R 10.1080/1369118X.2016.1181195 %0 Journal Article %J Glocalism %D 2017 %T Seeing Like a Tesla: How Can We Anticipate Self-Driving Worlds? %A Jack Stilgoe %K automotive autonomy %K governance %K risk %K self-driving cars %K Tesla %X 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 – able to navigate the world’s complexity using only its sensors and processors – on offer from companies like Tesla is intentionally misleading. So-called “autonomous” 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. %B Glocalism %V 3 %G eng %R 10.12893/gjcpi.2017.3.2 %0 Magazine Article %D 2017 %T A self-driving shuttle in Las Vegas got into an accident on its first day of service %A Nick Statt %K autonomous vehicles %B the verge %8 11/2017 %G eng %U https://www.theverge.com/2017/11/8/16626224/las-vegas-self-driving-shuttle-crash-accident-first-day %0 Journal Article %J Robotics and Autonomous Systems %D 2017 %T Service Robotics and Human Labor: A first technology assessment of substitution and cooperation %A Decker, Michael %A Fischer, Martin %A Ott, Ingrid %B Robotics and Autonomous Systems %V 87 %P 348 - 354 %8 Jan-01-2017 %G eng %R 10.1016/j.robot.2016.09.017 %0 Journal Article %J Academy of Management Discoveries %D 2017 %T Situated redesign in creative occupations – An ethnography of architects %A Rahman, Hatim A. %A Barley, Stephen R. %B Academy of Management Discoveries %V 3 %P 404 - 424 %8 Jan-12-2017 %G eng %N 4 %R 10.5465/amd.2016.0039 %0 Journal Article %J The International Journal of Robotics Research %D 2017 %T Situational awareness, workload, and workflow preferences %A Gombolay, Matthew %A Bair, Anna %A Huang, Cindy %A Shah, Julie %B The International Journal of Robotics Research %V 36 %P 597 - 617 %8 Sep-06-2017 %G eng %N 5-7 %R 10.1177/0278364916688255 %0 Web Page %D 2017 %T The skeptic's guide to artificial intelligence artificial intelligence %A By Catherine O'Connor %B CIO DIVE %G eng %U https://www.ciodive.com/news/the-skeptics-guide-to-artificial-intelligence/441674/ %0 Journal Article %J Information, Communication & Society %D 2017 %T The social power of algorithms %A Beer, David %B Information, Communication & Society %V 20 %P 1 - 13 %8 Feb-01-2017 %G eng %N 1 %R 10.1080/1369118X.2016.1216147 %0 Journal Article %J Journal of science communication %D 2017 %T Speculations and concerns on robots status in society %A Erik Stengler %A Jimena Escudero Perez %K bots %K Participation and science governance %K Public engagement with science and technology %K Science and policy-making %B Journal of science communication %G eng %U https://jcom.sissa.it/sites/default/files/documents/JCOM_1604_2017_C06.pdf %0 Conference Paper %B SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications IX %D 2017 %T SPIE ProceedingsBuilding a framework to manage trust in automation %A Metcalfe, J. S. %A Amar R. Marathe %A Haynes, B. %A Paul, V. J. %A Gremillion, G. M. %A Drnec, K. %A Atwater, C. %A Estepp, J. R. %A Lukos, J. R. %A Carter, E. C. %A W. D. Nothwang %E George, Thomas %E Dutta, Achyut K. %E Islam, M. Saif %B SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications IX %I SPIE %C Anaheim, California, United States %V 10194 %P 101941U %G eng %R 10.1117/12.2264245 %0 Journal Article %J Peer-reviewed journal on the internet %D 2017 %T Stewardship in the age of algorithms %A Clifford Lynch %B Peer-reviewed journal on the internet %G eng %U https://firstmonday.org/article/view/8097/6583 %0 Journal Article %J The Journal of Strategic Information Systems %D 2017 %T The strategic opportunities and challenges of algorithmic decision-making %A Galliers, R.D. %A Newell, S. %A Shanks, G. %A Topi, H. %B The Journal of Strategic Information Systems %V 26 %P 185 - 190 %8 Jan-09-2017 %G eng %N 3 %R 10.1016/j.jsis.2017.08.002 %0 Journal Article %J Information Systems Research %D 2017 %T A systematic framework for multilevel theorizing in information systems research %A Zhang, Meng %A Gable, Guy G. %B Information Systems Research %V 28 %P 203 - 224 %8 Jan-06-2017 %G eng %N 2 %R 10.1287/isre.2017.0690 %0 Journal Article %J Information, Communication & Society %D 2017 %T Thinking critically about and researching algorithms %A Kitchin, Rob %K Algorithmic management %B Information, Communication & Society %V 20 %P 14 - 29 %8 Feb-01-2017 %G eng %N 1 %R 10.1080/1369118X.2016.1154087 %0 Journal Article %J ACM Computing Surveys %D 2017 %T Understanding human-machine networks %A Tsvetkova, Milena %A Yasseri, Taha %A Meyer, Eric T. %A Pickering, J. Brian %A Engen, Vegard %A Walland, Paul %A Lüders, Marika %A Følstad, Asbjørn %A Bravos, George %B ACM Computing Surveys %V 50 %P 1 - 35 %8 Jan-04-2018 %G eng %N 1 %R 10.1145/3039868 %0 Journal Article %J MIT SLOAN MANAGEMENT REVIEW %D 2017 %T What to expect from artificial intelligence %A Ajay Agrawal %A Joshua S. Gans %A Avi Goldfarb %B MIT SLOAN MANAGEMENT REVIEW %V 58 %G eng %U http://ilp.mit.edu/media/news_articles/smr/2017/58311.pdf %) 58311 %0 Magazine Article %D 2017 %T When you're not quite sure if your teacher is human %A Tasnim Shamma %B nprEd %8 05/2017 %G eng %U https://www.npr.org/sections/ed/2017/05/08/524550295/when-youre-not-quite-sure-if-your-teacher-is-human %0 Magazine Article %D 2017 %T Where is technology taking the economy %A W. Brian Arthur %B McKinsey & Company %8 10/2017 %G eng %U mckinsey.com/business-functions/mckinsey-analytics/our-insights/where-is-technology-taking-the-economy %N McKinsey Analytics %0 Journal Article %J Science and Engineering Ethics %D 2017 %T Will Life Be Worth Living in a World Without Work? Technological Unemployment and the Meaning of Life %A John Danaher %K Antiwork %K automation %K Egalitarianism %K Freedom %K Meaning of life %K Technological unemployment %K Transhumanism %X 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. %B Science and Engineering Ethics %I Springer %V 23 %G eng %& 41-64 %R 10.1007s/11948-016-9770-5 %0 Journal Article %J Science and Engineering Ethics %D 2017 %T Will Life Be Worth Living in a World Without Work? Technological Unemployment and the Meaning of Life %A Danaher, John %B Science and Engineering Ethics %V 23 %P 41 - 64 %8 Jan-02-2017 %G eng %N 1 %R 10.1007/s11948-016-9770-5 %0 Report %D 2017 %T Workforce of the future: The competing forces shaping 2030 %A Carol Stubbings Stubbings %A Jon Williams %B pwc %G eng %U https://www.pwc.co.uk/economic-services/ukeo/pwc-uk-economic-outlook-full-report-march-2017-v2.pdf %0 Journal Article %J Work and Occupations %D 2017 %T Working algorithms: Software automation and the future of work %A Shestakofsky, Benjamin %B Work and Occupations %V 44 %P 376 - 423 %8 Nov-11-2018 %G eng %N 4 %R 10.1177/0730888417726119 %0 Magazine Article %D 2017 %T The zombie robot argument lurches on %A Lawrence Mishel %A Josh Bivens %B Economy policy institute %I Economic policy institute %8 m5/2017 %G eng %U http://epi.org/126750 %0 Magazine Article %D 2016 %T AI can show us the ravages of climate change %A Will Knight %K AI use cases %B MIT Technology Review %G eng %U https://www.technologyreview.com/f/613547/ai-can-show-us-the-ravages-of-climate-change/ %0 Journal Article %J Science, Technology, & Human Values %D 2016 %T Algorithms, governance, and governmentality %A Introna, Lucas D. %B Science, Technology, & Human Values %V 41 %P 17 - 49 %8 Jun-01-2018 %G eng %N 1 %R 10.1177/0162243915587360 %0 Web Page %D 2016 %T AP Sports is using robot reporters to cover Minor League Baseball %A Lora Kolodny %B techcrunch %G eng %U https://techcrunch.com/2016/07/03/ap-sports-is-using-robot-reporters-to-cover-minor-league-baseball/ %0 Web Page %D 2016 %T AP's robot journalists are writing about Minor League Baseball now %A Rich McCormick %B theverge %G eng %U https://www.theverge.com/2016/7/4/12092768/ap-robot-journalists-automated-insights-minor-league-baseball %0 Report %D 2016 %T ARTIFICIAL INTELLIGENCE AND LIFE IN 2030 %G eng %U https://ai100.stanford.edu/sites/g/files/sbiybj9861/f/ai_100_report_0831fnl.pdf %0 Journal Article %J Public Understanding of Science %D 2016 %T Citizen science on a smartphone: Participants’ motivations and learning %A Land-Zandstra, Anne M. %A Devilee, Jeroen L. A. %A Snik, Frans %A Buurmeijer, Franka %A van den Broek, Jos M. %B Public Understanding of Science %V 25 %P 45 - 60 %8 Mar-01-2017 %G eng %N 1 %R 10.1177/0963662515602406 %0 Conference Paper %B IEEE International Conference on Systems, Man and Cybernetics %D 2016 %T Degree of Automation in Command and Control Decision Support Systems %A Ryan M. Robinson %A Michael J. McCount %A Amar R. Marathe %A W. D. Nothwang %A Emily A. Doucette %B IEEE International Conference on Systems, Man and Cybernetics %G eng %U https://ieeexplore.ieee.org/document/7844402 %0 Journal Article %J Regional Science and Urban Economics %D 2016 %T Did the Computer Revolution shift the fortunes of U.S. cities? Technology shocks and the geography of new jobs %A Berger, Thor %A Frey, Carl Benedikt %B Regional Science and Urban Economics %V 57 %P 38 - 45 %8 Jan-03-2016 %G eng %R 10.1016/j.regsciurbeco.2015.11.003 %0 Journal Article %J Computers in Human Behavior %D 2016 %T Differences in perceptions of communication quality between a Twitterbot and human agent for information seeking and learning %A Edwards, Chad %A Beattie, Austin J. %A Edwards, Autumn %A Spence, Patric R. %B Computers in Human Behavior %V 65 %P 666 - 671 %8 Jan-12-2016 %G eng %R 10.1016/j.chb.2016.07.003 %0 Journal Article %J Academy of Management Journal %D 2016 %T The digital workforce and the workplace of the future %A Colbert, Amy %A Yee, Nick %A George, Gerard %B Academy of Management Journal %V 59 %P 731 - 739 %8 Jan-06-2016 %G eng %N 3 %R 10.5465/amj.2016.4003 %0 Conference Paper %B the 2016 24th ACM SIGSOFT International SymposiumProceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2016 %D 2016 %T Disrupting developer productivity one bot at a time %A Storey, Margaret-Anne %A Zagalsky, Alexey %Y Zimmermann, Thomas %Y Cleland-Huang, Jane %Y Su, Zhendong %B the 2016 24th ACM SIGSOFT International SymposiumProceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2016 %I ACM Press %C Seattle, WA, USANew York, New York, USA %P 928 - 931 %@ 9781450342186 %G eng %R 10.1145/2950290.2983989 %0 Thesis %B Computer Science %D 2016 %T Exploring design principles for human-machine symbiosis: Insights from constructing an air transportation logistics artifact %A Daniel A. Döppner %A Detlef Schoder %A Robert Wayne Gregory %A Honorata Siejka %K air transportation logistics %K design science research %K heuristic theorizing %K huma n - machine symbiosis %B Computer Science %G eng %U https://www.semanticscholar.org/paper/Artificial-Intelligence-and-its-Role-in-Near-Future-Shabbir-Anwer/b93d9995f9ce3b15f4c4855ae62f0bf6f9bc041f %0 Journal Article %J Big Data %D 2016 %T The Future of Artificial Intelligence %A Dhar, Vasant %B Big Data %V 4 %P 5 - 9 %8 Jan-03-2016 %G eng %N 1 %R 10.1089/big.2016.29004.vda %0 Generic %D 2016 %T The Future of Jobs: Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution %A The World Economic Forum %I World Economic Forum %G eng %9 Report %0 Book %D 2016 %T Handbook of Science and Technology ConvergenceConvergence-Divergence Process %A Roco, Mihail C. %E Bainbridge, William Sims %E Roco, Mihail C. %I Springer International Publishing %C Cham %P 79 - 93 %@ 978-3-319-07051-3 %G eng %R 10.1007/978-3-319-07052-0_11 %0 Magazine Article %D 2016 %T Hire a UR robot - pay for it by the hour %A Mahew Bush %K bots %B Universal Robots %8 07/2016 %G eng %U https://blog.universal-robots.com/hire-a-ur-robot-pay-for-it-by-the-hour %0 Magazine Article %D 2016 %T How artificial intelligence will redefine management %A Vegard Kolbjornsrud %A Richard Amico %A Robert J. Thomas %B Havard Business Review %8 11/2016 %G eng %U https://hbr.org/2016/11/how-artificial-intelligence-will-redefine-management %0 Journal Article %J Annual Review of Organizational Psychology and Organizational Behavior %D 2016 %T How technology is changing work and organizations %A Cascio, Wayne F. %A Montealegre, Ramiro %B Annual Review of Organizational Psychology and Organizational Behavior %V 3 %P 349 - 375 %8 Sep-03-2017 %G eng %N 1 %R 10.1146/annurev-orgpsych-041015-062352 %0 Journal Article %J Big Data & Society %D 2016 %T How the machine ‘thinks’: Understanding opacity in machine learning algorithms %A Burrell, Jenna %B Big Data & Society %V 3 %P 205395171562251 %8 May-01-2016 %G eng %N 1 %R 10.1177/2053951715622512 %0 Journal Article %J Transaction on human-machine systems %D 2016 %T Human Interaction With Robot Swarms: A Survey %K Human-robot interaction (HRI) %K human-swarm interaction (HSI) %K multi-robot systems %K swarm robotics %X 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. %B Transaction on human-machine systems %I IEEE %V 46 %P 9-26 %8 02/2016 %G eng %0 Journal Article %J Technology in Society %D 2016 %T Humans, robots and values %A Cockshott, Paul %A Renaud, Karen %B Technology in Society %V 45 %P 19 - 28 %8 Jan-05-2016 %G eng %R 10.1016/j.techsoc.2016.01.002 %0 Magazine Article %D 2016 %T If you're not collecting productivity data, you'll never succeed at work %A Michael Schrage %B Havard Business Review %8 02/2016 %G eng %U https://hbr.org/2016/02/if-youre-not-collecting-productivity-data-youll-never-succeed-at-work %0 Report %D 2016 %T Implications of technology for growth, factor shares and employment %A Acemoglu, Daron %A Restrepo, Pascual %I National Bureau of Economic Research %C Cambridge, MA %G eng %U http://www.nber.org/papers/w22252.pdf %R 10.3386/w22252 %0 Journal Article %J Data Informed %D 2016 %T IT drinking its own automation champagne %A Thomas H. Davenport %B Data Informed %8 11/2016 %G eng %U https://www.linkedin.com/pulse/drinking-its-own-automation-champagne-tom-davenport/ %0 Journal Article %J Organizational Behavior and Human Decision Processes %D 2016 %T Job design research and theory: Past, present and future %A Oldham, Greg R. %A Fried, Yitzhak %B Organizational Behavior and Human Decision Processes %V 136 %P 20 - 35 %8 Jan-09-2016 %G eng %R 10.1016/j.obhdp.2016.05.002 %0 Journal Article %J Proceedings of the IEEE %D 2016 %T Machine learning and decision support in critical care %A Johnson, Alistair E. W. %A Ghassemi, Mohammad M. %A Nemati, Shamim %A Niehaus, Katherine E. %A Clifton, David %A Clifford, Gari D. %B Proceedings of the IEEE %V 104 %P 444 - 466 %8 Jan-02-2016 %G eng %N 2 %R 10.1109/JPROC.2015.2501978 %0 Journal Article %J Complexity %D 2016 %T Models and people: An alternative view of the emergent properties of computational models %A Boschetti, Fabio %B Complexity %V 21 %P 202 - 213 %8 Jan-07-2016 %G eng %N 6 %R 10.1002/cplx.21680 %0 Journal Article %J Communications of the ACM %D 2016 %T The moral imperative of artificial intelligence %A Vardi, Moshe Y. %B Communications of the ACM %V 59 %P 5 %G eng %9 Journal Article %R 10.1145/2903530 %0 Journal Article %J New England Journal of Medicine %D 2016 %T Predicting the Future — Big Data, Machine Learning, and Clinical Medicine %A Obermeyer, Ziad %A Emanuel, Ezekiel J. %B New England Journal of Medicine %V 375 %P 1216 - 1219 %8 May-09-2018 %G eng %N 13 %R 10.1056/NEJMp1606181 %0 Report %D 2016 %T Preparing for the future of Artificial intelligence %I Executive Office of the President National Science and Technology Council Committee on Technology %8 10/2016 %G eng %U https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.pdf %0 Magazine Article %D 2016 %T Real-life examples of artificial intelligence %B letzgro %8 07/2016 %G eng %U https://letzgro.net/blog/real-life-examples-of-artificial-intelligence/ %0 Case %D 2016 %T Regional Diversity in Autonomy and Work: A Case Study from Uber and Lyft Drivers %A Alex Rosenblat %A Tim Hwang %B Data And Society %G eng %U https://datasociety.net/pubs/ia/Rosenblat-Hwang_Regional_Diversity-10-13.pdf %& Data And Society %0 Journal Article %J Natural Language Engineering %D 2016 %T The return of the chatbots %A Robert Dale %B Natural Language Engineering %V 22 %P 811 - 817 %8 Jan-09-2016 %G eng %U https://www.cambridge.org/core/product/identifier/S1351324916000243/type/journal_articlehttps://www.cambridge.org/core/services/aop-cambridge-core/content/view/S1351324916000243 %N 5 %R 10.1017/S1351324916000243 %0 Journal Article %J Communications of the ACM %D 2016 %T The rise of social bots %A Ferrara, Emilio %A Varol, Onur %A Davis, Clayton %A Menczer, Filippo %A Flammini, Alessandro %B Communications of the ACM %V 59 %P 96 - 104 %8 Dec-06-2017 %G eng %N 7 %R 10.1145/2818717 %0 Journal Article %J Journal of Macroeconomics %D 2016 %T Robots and humans – complements or substitutes? %A DeCanio, Stephen J. %B Journal of Macroeconomics %V 49 %P 280 - 291 %8 Jan-09-2016 %G eng %R 10.1016/j.jmacro.2016.08.003 %0 Journal Article %J Societies %D 2016 %T Robots working with humans or humans working with robots? %A Moniz, António %A Krings, Bettina-Johanna %B Societies %V 6 %P 23 %8 Jan-09-2016 %G eng %N 3 %R 10.3390/soc6030023 %0 Conference Paper %B SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications VIII %D 2016 %T SPIE ProceedingsAn efficient fusion approach for combining human and machine decisions %A Lee, Hyungtae %A Kwon, Heesung %A Ryan M. Robinson %A W. D. Nothwang %A Amar R. Marathe %E George, Thomas %E Dutta, Achyut K. %E Islam, M. Saif %B SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications VIII %I SPIE %C Baltimore, Maryland, United States %V 9836 %P 983621 %G eng %U http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2220788 %R 10.1117/12.2220788 %0 Report %D 2016 %T Structural transformation in the OECD %A Thor Berger %A Carl Benedikt Frey %B OECD Social, Employment and Migration %V 193 %G eng %R 10.1787/5jlr068802f7-en %0 Journal Article %J Computer %D 2016 %T Will computers put us out of work? %A King, John Leslie %A Grudin, Jonathan %B Computer %V 49 %P 82 - 85 %8 Jan-05-2016 %G eng %N 5 %R 10.1109/MC.2016.126 %0 Journal Article %J International weekly journal of science %D 2016 %T A world where everyone has a robot: Why 2040 could blow your mind %A Declan Butler %B International weekly journal of science %G eng %U https://www.nature.com/news/a-world-where-everyone-has-a-robot-why-2040-could-blow-your-mind-1.19431 %0 Generic %D 2015 %T Artificial Intelligence and its Role in Near Future %A Jahanzaib Shabbir %A Tarique Anwer %V JOURNAL OF L A T E X CLASS FILES, VOL. 14, NO. 8, AUGUST 2015 %G eng %U https://www.semanticscholar.org/paper/Artificial-Intelligence-and-its-Role-in-Near-Future-Shabbir-Anwer/b93d9995f9ce3b15f4c4855ae62f0bf6f9bc041f %0 Report %D 2015 %T Artificial intelligence for the real world: Don't start with moon shots %A Thomas H. Davenport %A Rajeev Ronanki %K consulting reports %B Harvard Business Review %G eng %U https://hbr.org/2018/01/artificial-intelligence-for-the-real-world %0 Book %B Employment& Labor Law Solutions Worldwide %D 2015 %T The big move toward big data in employment %A Aaron Crews %B Employment& Labor Law Solutions Worldwide %I Littler Mendelson, P.C. %G eng %U https://www.littler.com/files/wp_big_data_8-04-15.pdf %0 Journal Article %J Journal of Economic Perspectives %D 2015 %T Is a Cambrian Explosion Coming for Robotics? %A Pratt, Gill A. %B Journal of Economic Perspectives %V 29 %P 51 - 60 %8 Jan-08-2015 %G eng %U http://pubs.aeaweb.org/doi/10.1257/jep.29.3.51http://pubs.aeaweb.org/doi/pdf/10.1257/jep.29.3.51 %N 3 %R 10.1257/jep.29.3.51 %0 Journal Article %J Computers in Human Behavior %D 2015 %T A comparison between human–human online conversations and human–chatbot conversations %A Hill, Jennifer %A Randolph Ford, W. %A Farreras, Ingrid G. %B Computers in Human Behavior %V 49 %P 245 - 250 %8 Jan-08-2015 %G eng %R 10.1016/j.chb.2015.02.026 %0 Journal Article %J Autonomous Robots %D 2015 %T Decision-making authority, team efficiency and human worker satisfaction in mixed human–robot teams %A Gombolay, Matthew C. %A Gutierrez, Reymundo A. %A Clarke, Shanelle G. %A Sturla, Giancarlo F. %A Shah, Julie A. %B Autonomous Robots %V 39 %P 293 - 312 %8 Jan-10-2015 %G eng %N 3 %R 10.1007/s10514-015-9457-9 %0 Book %B Release 0.1 %D 2015 %T Deep Learning Tutorial %A LISA lab, University of Montreal %B Release 0.1 %G eng %U http://deeplearning.net/tutorial/deeplearning.pdf %0 Journal Article %J McKinsey Quarterly %D 2015 %T An executive’s guide to machine learning %A Dorian Pyle %A Cristina San Jose %B McKinsey Quarterly %G eng %U https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/an-executives-guide-to-machine-learning %9 Technology, Media & Telecommunications %0 Magazine Article %D 2015 %T Facebook launches M, its bold answer to Siri and Cortana %A Jessi Hempel %G eng %U https://www.wired.com/2015/08/facebook-launches-m-new-kind-virtual-assistant/ %0 Journal Article %J McKinsey Quarterly %D 2015 %T Four fundamentals of workplace automation %A Chui, Michael %A Manyika, James %A Miremadi, Mehdi %B McKinsey Quarterly %P 1–9 %8 November %G eng %9 Magazine Article %0 Generic %D 2015 %T The growing importance of social skills in the labor market %A Deming, David J %I National Bureau of Economic Research %G eng %9 Report %0 Journal Article %J Journal of Economic Perspectives %D 2015 %T The history of technological anxiety and the future of economic growth: Is this time different? %A Mokyr, Joel %A Vickers, Chris %A Ziebarth, Nicolas L. %B Journal of Economic Perspectives %V 29 %P 31 - 50 %8 Jan-08-2015 %G eng %N 3 %R 10.1257/jep.29.3.31 %0 Report %D 2015 %T How new digital technologies are making smart people and businesses smarter by automating rote work %B Cognizant %I Keep Challenging %8 01/2015 %G eng %U https://www.cognizant.com/whitepapers/the-robot-and-I-how-new-digital-technologies-are-making-smart-people-and-businesses-smarter-codex1193.pdf %0 Journal Article %J Nature %D 2015 %T Human-level control through deep reinforcement learning %A Mnih, Volodymyr %A Kavukcuoglu, Koray %A Silver, David %A Rusu, Andrei A %A Veness, Joel %A Bellemare, Marc G %A Graves, Alex %A Riedmiller, Martin %A Fidjeland, Andreas K %A Ostrovski, Georg %B Nature %V 518 %P 529-533 %G eng %9 Journal Article %0 Journal Article %J Computer Networks %D 2015 %T Hybrid human–machine information systems: Challenges and opportunities %A Demartini, Gianluca %B Computer Networks %V 90 %P 5 - 13 %8 Jan-10-2015 %G eng %R 10.1016/j.comnet.2015.05.018 %0 Conference Paper %B the 21th ACM SIGKDD International ConferenceProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15 %D 2015 %T Intelligible Models for HealthCare %A Caruana, Rich %A Lou, Yin %A Gehrke, Johannes %A Koch, Paul %A Sturm, Marc %A Elhadad, Noemie %Y Cao, Longbing %Y Zhang, Chengqi %Y Joachims, Thorsten %Y Webb, Geoff %Y Margineantu, Dragos D. %Y Williams, Graham %B the 21th ACM SIGKDD International ConferenceProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15 %I ACM Press %C Sydney, NSW, AustraliaNew York, New York, USA %P 1721 - 1730 %@ 9781450336642 %G eng %R 10.1145/278325810.1145/2783258.2788613 %0 Book %D 2015 %T Mining programming activity to promote help %A Carter, Jason %A Dewan, Prasun %E Boulus-Rødje, Nina %E Ellingsen, Gunnar %E Bratteteig, Tone %E Aanestad, Margunn %E Bjørn, Pernille %I Springer International Publishing %C Cham %P 23 - 42 %@ 978-3-319-20498-7 %G eng %R 10.1007/978-3-319-20499-4_2 %0 Journal Article %J Journal of latex class files %D 2015 %T Norms, institutions and robots %A Stevan Tomic %A Federico Pecora %A Alessandro Saffotti %B Journal of latex class files %V 14 %8 08/2015 %G eng %U https://arxiv.org/abs/1807.11456 %6 8 %0 Journal Article %J Association for the Advancement of Artificial Intelligence %D 2015 %T Research Priorities for Robust and Beneficial Artificial Intelligence %A Stuart Russell %A Daniel Dewey %A Max Tegmark %X

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.

%B Association for the Advancement of Artificial Intelligence %V 4 %P 105-114 %G eng %U https://futureoflife.org/data/documents/research_priorities.pdf %0 Conference Paper %B the 24th International ConferenceProceedings of the 24th International Conference on World Wide Web - WWW '15 Companion %D 2015 %T Science bot: a model for the future computation %A Kuhn, Tobias %Y Gangemi, Aldo %Y Leonardi, Stefano %Y Panconesi, Alessandro %B the 24th International ConferenceProceedings of the 24th International Conference on World Wide Web - WWW '15 Companion %I ACM Press %C Florence, ItalyNew York, New York, USA %P 1061 - 1062 %@ 9781450334730 %G eng %R 10.1145/2740908.2742014 %0 Journal Article %J Big Data & Society %D 2015 %T Toward a computational hermeneutics %A Mohr, John W %A Wagner-Pacifici, Robin %A Breiger, Ronald L %B Big Data & Society %V 2 %P 205395171561380 %8 Mar-12-2017 %G eng %N 2 %R 10.1177/2053951715613809 %0 Journal Article %J Computers in Human Behavior %D 2015 %T Users’ reactions to actions of automated programs in Wikipedia %A Clément, Maxime %A Guitton, Matthieu J. %B Computers in Human Behavior %V 50 %P 66 - 75 %8 Jan-09-2015 %G eng %R 10.1016/j.chb.2015.03.078 %0 Journal Article %J IZA World of Labor %D 2015 %T Who owns the robots rules the world %A Freeman, Richard %B IZA World of Labor %8 Jan-01-2015 %G eng %R 10.15185/izawol.5 %0 Journal Article %J Journal of Economic Perspectives %D 2015 %T Why Are There Still So Many Jobs? The History and Future of Workplace Automation %A Autor, David H. %B Journal of Economic Perspectives %V 29 %P 3-30 %G eng %U http://pubs.aeaweb.org/doi/10.1257/jep.29.3.3 %N 3 %R 10.1257/jep.29.3.3 %0 Journal Article %J Foreign Affairs %D 2015 %T Will humans go the way of horses %A Erik Brynjolfsson %A McAfee, Andrew %B Foreign Affairs %V 94 %P 8 %G eng %9 Journal Article %0 Journal Article %J Annual Review of Psychology %D 2014 %T Beyond motivation: Job and work design for development, health, ambidexterity, and more %A Parker, Sharon K. %B Annual Review of Psychology %V 65 %P 661 - 691 %8 Mar-01-2014 %G eng %N 1 %R 10.1146/annurev-psych-010213-115208 %0 Report %D 2014 %T Four scenarios exploring the future of youth employment %A Caroline Budhan %A Abigail Carlton %A Evan O'Donnel %B Institute for the future %8 12/2014 %G eng %U https://assets.rockefellerfoundation.org/app/uploads/20141201215005/FutureofYouthEmployment.pdf %0 Journal Article %J The Quarterly Journal of Economics %D 2014 %T The global decline of the labor share %A Karabarbounis, L. %A Neiman, B. %B The Quarterly Journal of Economics %V 129 %P 61 - 103 %8 Jan-02-2014 %G eng %N 1 %R 10.1093/qje/qjt032 %0 Journal Article %J Communications of the ACM %D 2014 %T Human-agent collectives %A Jennings, N. R. %A Moreau, L. %A Nicholson, D. %A Ramchurn, S. %A Roberts, S. %A Rodden, T. %A Rogers, A. %B Communications of the ACM %V 57 %P 80 - 88 %8 Feb-11-2016 %G eng %N 12 %R 10.1145/269296510.1145/2629559 %0 Journal Article %J Safety and Health at Work %D 2014 %T The impact of robotics on employment and motivation of employees in the service sector, with special reference to health care %A Qureshi, Mohammed Owais %A Syed, Rumaiya Sajjad %B Safety and Health at Work %V 5 %P 198 - 202 %8 Jan-12-2014 %G eng %N 4 %R 10.1016/j.shaw.2014.07.003 %0 Conference Paper %B European 10th Conference on Management Leadership and Governance %D 2014 %T Leveraging the cross-cultural capacities of artificial agents as leaders of human virtual teams %A Matthew Gladden %B European 10th Conference on Management Leadership and Governance %G eng %U https://www.researchgate.net/publication/268982256_Leveraging_the_Cross-Cultural_Capacities_of_Artificial_Agents_as_Leaders_of_Human_Virtual_Teams %0 Journal Article %J Academy of Management Journal %D 2014 %T Occupational identity, technological change, and the librarian/internet-search relationship %A Nelson, Andrew J. %A Irwin, Jennifer %B Academy of Management Journal %V 57 %P 892 - 928 %8 Jan-06-2014 %G eng %N 3 %R 10.5465/amj.2012.0201 %0 Journal Article %J Computers in Human Behavior %D 2014 %T Testing the differences in perceptions of communication quality for a human agent and a bot agent on Twitter %A Edwards, Chad %A Edwards, Autumn %A Spence, Patric R. %A Shelton, Ashleigh K. %B Computers in Human Behavior %V 33 %P 372 - 376 %8 Jan-04-2014 %G eng %R 10.1016/j.chb.2013.08.013 %0 Journal Article %J Journal of Human-Robot Interaction %D 2014 %T Toward a Framework for Levels of Robot Autonomy in Human-Robot Interaction %A Beer, Jenay M %A Fisk, Arthur D %A Rogers, Wendy A %B Journal of Human-Robot Interaction %V 3 %P 74 %8 Jan-06-2014 %G eng %U http://dl.acm.org/citation.cfm?id=3109833http://dl.acm.org/ft_gateway.cfm?id=3109833&ftid=1883786&dwn=1 %N 2 %R 10.5898/JHRI.3.2.Beer %0 Magazine Article %D 2014 %T A transdisciplinary perspective on hedonomic sustainability design %A Stephen M. Fiore %A Elizabeth Philips %A Brittany C. Sellers %K environmental efficacy %K environmental sustainability %K hedonomics %K sustainable design %K transdisciplinary research %B Economics in design %G eng %U https://journals.sagepub.com/doi/abs/10.1177/1064804613516762?journalCode=erga %R 10.1177%2F1064804613516762 %0 Generic %D 2013 %T Beyond Big Data %A Hal R. Varian %B NABE Annual Meeting %G eng %U http://people.ischool.berkeley.edu/~hal/Papers/2013/BeyondBigDataPaperFINAL.pdf %0 Report %D 2013 %T Beyond convergence of Nano-Bio-Info-Cognitive technologies %A Mihail C. Roco %A William S. Bainbridge %A Bruce Tonn %A George Whitesides %B WTEC Study on Convergence of Knowledge, Technology, and Society %8 07/2013 %G eng %U http://www.wtec.org/NBIC2/Docs/FinalReport/Pdf-secured/NBIC2-FinalReport-WEB.pdf %0 Journal Article %D 2013 %T A Comprehensive Survey of Data Mining-based Fraud Detection Research %A Clifton Phua %A Vincent Lee %A Kate Smith %A Ross Gayler %K adversarial detection %K automated fraud detection %K Data mining applications %G eng %U https://arxiv.org/ftp/arxiv/papers/1009/1009.6119.pdf %0 Journal Article %J National Academy of Engineering %D 2013 %T The convergence of engineering and the life sciences %A Pjilip A. Sharp %A Robert Langer %B National Academy of Engineering %V 43 %8 10/2013 %G eng %U https://www.nae.edu/88364/The-Convergence-of-Engineering-and-the-Life-Sciences %N 3 %0 Magazine Article %D 2013 %T Ethical algorithms %A R.J. Anderson %A W.W. Sharrock %B —Horizon Digital Economy %G eng %U https://www.sharrockandanderson.co.uk/wp-content/uploads/2017/04/Ethical-Algorithms.pdf %N Post Modernism, Technology and Social Science %0 Conference Paper %B Proceedings of the 2013 conference on Computer supported cooperative work %D 2013 %T The future of crowd work %A Kittur, Aniket %A Jeffrey V Nickerson %A Michael S. Bernstein %A Gerber, Elizabeth %A Shaw, Aaron %A Zimmerman, John %A Lease, Matt %A Horton, John %B Proceedings of the 2013 conference on Computer supported cooperative work %I ACM %P 1301–1318 %G eng %0 Report %D 2013 %T The great reversal in the demand for skill and cognitive tasks %A Beaudry, Paul %A Green, David %A Sand, Benjamin %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w18901 %0 Book %D 2013 %T Integration and implementation sciences for researching complex real-world problems %A Bammer %A Gabriele %@ 9781922144270 %G eng %U https://www.jstor.org/stable/j.ctt2jbkj5 %0 Journal Article %J Journal of Nanoparticle Research %D 2013 %T The new world of discovery, invention, and innovation: convergence of knowledge, technology, and society %A Roco, Mihail C. %A Bainbridge, William S. %B Journal of Nanoparticle Research %V 15 %8 Jan-09-2013 %G eng %U 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 %N 9 %R 10.1007/s11051-013-1946-1 %0 Journal Article %J Journal of Informetrics %D 2013 %T Quantifying the interdisciplinarity of scientific journals and fields %A Silva, F.N. %A Rodrigues, F.A. %A Oliveira, O.N. %A da F. Costa, L. %B Journal of Informetrics %V 7 %P 469 - 477 %8 Jan-04-2013 %G eng %U 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 %N 2 %R 10.1016/j.joi.2013.01.007 %0 Journal Article %J Research Policy %D 2013 %T The rise and fall of interdisciplinary research: The case of open source innovation %A Raasch, Christina %A Lee, Viktor %A Spaeth, Sebastian %A Herstatt, Cornelius %B Research Policy %V 42 %P 1138 - 1151 %8 Jan-06-2013 %G eng %N 5 %R 10.1016/j.respol.2013.01.010 %0 Conference Paper %B IEEE International Conference %D 2013 %T Survey of metrics for human-robot interaction %A Robin R. Murphy %A Debra Schreckenghost %K bots %B IEEE International Conference %G eng %U https://ieeexplore.ieee.org/document/6483569 %0 Journal Article %J Communications of the ACM %D 2012 %T A few useful things to know about machine learning %A Domingos, Pedro %B Communications of the ACM %V 55 %P 78 %8 Jan-10-2012 %G eng %N 10 %R :10.1145/2347736.2347755 %0 Journal Article %J Journal of Informetrics %D 2011 %T Approaches to understanding and measuring interdisciplinary scientific research (IDR): A review of the literature %A Wagner, Caroline S. %A Roessner, J. David %A Bobb, Kamau %A Klein, Julie Thompson %A Boyack, Kevin W. %A Keyton, Joann %A Rafols, Ismael %A Börner, Katy %B Journal of Informetrics %V 5 %P 14 - 26 %8 Jan-01-2011 %G eng %N 1 %R 10.1016/j.joi.2010.06.004 %0 Conference Paper %B the 2011 iConferenceProceedings of the 2011 iConference on - iConference '11 %D 2011 %T No sense of distance %A Aragon, Cecilia R. %A Poon, Sarah %B the 2011 iConferenceProceedings of the 2011 iConference on - iConference '11 %I ACM Press %C Seattle, WashingtonNew York, New York, USA %P 159 - 165 %@ 9781450301213 %G eng %R 10.1145/1940761.1940783 %0 Journal Article %J Ethics and Information Technology %D 2011 %T Is there an ethics of algorithms? %A Kraemer, Felicitas %A van Overveld, Kees %A Peterson, Martin %B Ethics and Information Technology %V 13 %P 251 - 260 %8 Jan-09-2011 %G eng %N 3 %R 10.1007/s10676-010-9233-7 %0 Journal Article %J Journal of Organizational Behavior %D 2010 %T Not what it was and not what it will be: The future of job design research %A Oldham, Greg R. %A Hackman, J. Richard %E Grant, Adam %E Fried, Yitzhak %E Parker, Sharon %E Frese, Michael %B Journal of Organizational Behavior %V 31 %P 463 - 479 %8 Jan-02-2010 %G eng %N 2-3 %R 10.1002/job.v31:2/310.1002/job.678 %0 Journal Article %J Medical Care %D 2010 %T Prediction modeling using EHR data: Challenges, strategies, and a comparison of machine learning approaches %A Jionglin Wu %A Jason Ray %A Walter F. Stewart %B Medical Care %I Lippincott Williams & Wilkins %V 48 %G eng %U https://www.jstor.org/stable/20720782 %9 Emerging Methods and Policy Applications %6 6 %0 Journal Article %J Journal of Organizational Behavior %D 2010 %T Understanding the role of occupational and organizational context %A Morgeson, Frederick P. %A Dierdorff, Erich C. %A Hmurovic, Jillian L. %E Grant, Adam %E Fried, Yitzhak %E Parker, Sharon %E Frese, Michael %B Journal of Organizational Behavior %V 31 %P 351 - 360 %8 Jan-02-2010 %G eng %N 2-3 %R 10.1002/job.642 %0 Conference Paper %D 2010 %T Using machine learning for network intrusion detection %A R. Sommer %A V. 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S. %B International Journal for Quality in Health Care %V 16 %P 125 - 132 %8 Jan-04-2004 %G eng %N 2 %R 10.1093/intqhc/mzh026 %0 Book %D 2003 %T Handbook of psychology work design %A Morgeson, Frederick P. %A Campion, Michael A. %E Weiner, Irving B. %I John Wiley & Sons, Inc. %C Hoboken, NJ, USA %G eng %R 10.1002/0471264385.wei1217 %0 Report %D 2003 %T A Preliminary Analysis of Occupational Task Statements from the O*NET Data Collection Program %A Van Iddekinge, Chad %A Suzanne Tsacoumis %A Jamie Donsbach %I National Center for O*NET Development %@ FR-02-52 %G eng %0 Journal Article %J Quarterly Journal of Economics %D 2003 %T The skill content of recent technological change: An empirical exploration %A Autor, D. H. %A Levy, F. %A Murnane, R. J. %B Quarterly Journal of Economics %V 118 %P 1279–1333 %G eng %U http://apps.isiknowledge.com/InboundService.do?Func=Frame&product=WOS&action=retrieve&SrcApp=EndNote&Init=Yes&SrcAuth=ResearchSoft&mode=FullRecord&UT=WOS:000186624900004 %9 Journal Article %R 10.1162/003355303322552801 %0 Book Section %B Handbook of Psychology: Industrial and Organizational Psychology %D 2003 %T Work design %A Frederick P. Morgeson %A Campion, Michael A. %E W. Borman %E Ilgen, D. %E Klimoski, R. %B Handbook of Psychology: Industrial and Organizational Psychology %I Wiley %C Hoboken, NY %V 12 %P 423–452 %G eng %0 Journal Article %J Cognition, Technology & Work %D 2002 %T Can we ever escape from data overload? A cognitive systems diagnosis %A Woods, D. D. %A Patterson, E. S. %A Roth, E. M. %B Cognition, Technology & Work %V 4 %P 22 - 36 %8 Jan-04-2002 %G eng %N 1 %R 10.1007/s101110200002 %0 Journal Article %J Journal of Nanoparticle Research %D 2002 %T Converging technologies for improving human performance: Integrating from the nanoscale %A M. C. Roco %A W. S. Bainbridge %B Journal of Nanoparticle Research %V 4 %P 281-295 %8 07/2002 %G eng %U https://link.springer.com/article/10.1023/A:1021152023349 %N 4 %0 Journal Article %J Organization Science %D 2001 %T Bringing work back in %A Stephen R. Barley %A Kunda, Gideon %B Organization Science %V 12 %P 76–95 %G eng %9 Journal Article %R 10.1287/orsc.12.1.76.10122 %0 Journal Article %J Information Systems ResearchInformation Systems Research %D 2001 %T Desperately seeking "IT" in IT research: A call to theorizing the IT artifact %A Wanda J. Orlikowski %A C. Suzanne Iacono %B Information Systems ResearchInformation Systems Research %V 12 %P 121–134 %G eng %0 Journal Article %J Computer Supported Cooperative Work (CSCW) %D 2001 %T Shift changes, updates, and the on-call architecture in space shuttle mission control %A Patterson, Emily S. %A Woods, David D. %B Computer Supported Cooperative Work (CSCW) %V 10 %P 317 - 346 %8 Jan-09-2001 %G eng %N 3-4 %R 10.1023/A:1012705926828 %0 Journal Article %J Ergonomics %D 2000 %T From human – machine interaction to human – machine cooperation %A Hoc, Jean-Michel %B Ergonomics %V 43 %P 833 - 843 %8 Oct-07-2000 %G eng %N 7 %R 10.1080/001401300409044 %0 Report %D 2000 %T Technical change, inequality, and the labor market %A Acemoglu, Daron %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w7800 %0 Report %D 1999 %T Information technology, workplace organization and the demand for skilled labor %A Bresnahan, Timothy %A Brynjolfsson, Erik %A Hitt, Lorin %I National Bureau of Economic Research %C Cambridge, MA %G eng %R 10.3386/w7136 %0 Book Section %B Handbook of Human Factors and Ergonomics %D 1997 %T Automation surprises %A Sarter, Nadine B. %A Woods, David D. %A Billings, Charles E. %B Handbook of Human Factors and Ergonomics %V 2 %P 1926–1943 %G eng %9 Book Section %0 Book %D 1997 %T Computer Science and Artificial Intelligence %A Panel on Computer Science and Artificial Intelligence %G eng %U https://www.nap.edu/read/5812/chapter/1 %0 Journal Article %J Cognition and Communication at WorkCognition and communication at work %D 1996 %T Distributed cognition in an airline cockpit %A Hutchins, Edwin %A Klausen, Tove %B Cognition and Communication at WorkCognition and communication at work %P 15–34 %G eng %0 Report %D 1995 %T Application of Machine Learning and Rule Induction %A Pat Langley %B Technical Report 95-1 %G eng %U https://dl.acm.org/citation.cfm?id=219768 %0 Conference Proceedings %B International Conference on Human-Computer Interaction (HCI International) %D 1995 %T Complementary allocation of functions in automated work systems %A G. Grote %A S. Weik %A T. Wafler %A M. Zolch %B International Conference on Human-Computer Interaction (HCI International) %I Elsevier %V 20 %P 989-994 %G eng %0 Conference Proceedings %B International Conference on Human-Computer Interaction (HCI International) %D 1995 %T Integration of people, technology and organization: the european approach %A Christina Kirsch %A Peter Troxier %A Eberhard Ulich %X 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. %B International Conference on Human-Computer Interaction (HCI International) %I Elsevier %C Tokyo, Japan %V 20 %P 957-961 %G eng %0 Journal Article %J International Journal of Industrial Ergonomics %D 1994 %T Design concepts of computer-aided integrated manufacturing systems: Work-psychological concepts and empirical findings %A C. Kirsh %A O. Strohm %A E. Ulich %K Computer-Integrated-Manufacturing CIM %K Organizational design %K Production design concepts %K Socio-technical system approach %K Work psychology %K Work-orientation %X 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. %B International Journal of Industrial Ergonomics %I Elsevier %V 17 %G eng %& 11-19 %0 Journal Article %J Journal of Applied Psychology %D 1991 %T Development and test of a task level model of motivational job design %A Wong, Chi-sum %A Campion, Michael A. %B Journal of Applied Psychology %V 76 %P 825–837 %G eng %0 Journal Article %J Administrative science quarterly %D 1990 %T The alignment of technology and structure through roles and networks %A Stephen R. Barley %B Administrative science quarterly %P 61-103 %G eng %9 Journal Article %0 Case %D 1989 %T Expert systems for configuration at digital: xcon and beyond %A Virginia E. Barker %A Dennis E. 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R. %I Addison-Wesley %C Reading, MA %G eng %0 Journal Article %J Communications of the ACM %D 1966 %T “Algorithm” and “formula” %A Wangsness, T. %A Franklin, J. %B Communications of the ACM %V 9 %P 243 %8 Jan-04-1966 %G eng %N 4 %R 10.1145/365278.365286 %0 Journal Article %J Social Problems %D 1965 %T Automation and the Division of Labor %A Faunce, William A. %B Social Problems %V 13 %P 149 - 160 %8 Jan-10-1965 %G eng %N 2 %R 10.2307/798900 %0 Journal Article %J Human relationsHuman Relations %D 1951 %T 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 %A Trist, Eric Lansdowne %A Bamforth, Ken W %B Human relationsHuman Relations %V 4 %P 3-38 %@ 0018-7267 %G eng %0 Book %D 1911 %T The Principles of Scientific Management %A Taylor, F. W. %K Productionmanagement %I Norton & Company %C New York %G eng