@article {9998, title = {Making sense of AI systems development}, journal = {IEEE Transactions on Software Engineering}, volume = {50}, year = {2024}, month = {12/2023}, pages = {123{\textendash}140}, abstract = {We identify and describe episodes of sensemaking around challenges in modern Artificial-Intelligence (AI)-based systems development that emerged in projects carried out by IBM and client companies. All projects used IBM Watson as the development platform for building tailored AI-based solutions to support workers or customers of the client companies. Yet, many of the projects turned out to be significantly more challenging than IBM and its clients had expected. The analysis reveals that project members struggled to establish reliable meanings about the technology, the project, context, and data to act upon. The project members report multiple aspects of the projects that they were not expecting to need to make sense of yet were problematic. Many issues bear upon the current-generation AI{\textquoteright}s inherent characteristics, such as dependency on large data sets and continuous improvement as more data becomes available. Those characteristics increase the complexity of the projects and call for balanced mindfulness to avoid unexpected problems.}, doi = {10.1109/TSE.2023.3338857}, attachments = {https://waim.network/sites/crowston.syr.edu/files/sensemaking_tse_to_share.pdf}, author = {Mateusz Dolata and Kevin Crowston} } @conference {2024, title = {ReelFramer: Human-AI Co-Creation for News-to-Video Translation}, booktitle = {CHI {\textquoteright}24: CHI Conference on Human Factors in Computing SystemsProceedings of the CHI Conference on Human Factors in Computing Systems}, year = {2024}, pages = {1 - 20}, publisher = {ACM}, organization = {ACM}, address = {Honolulu HI USANew York, NY, USA}, isbn = {9798400703300}, doi = {10.1145/3613904.3642868}, author = {Wang, Sitong and Menon, Samia and Long, Tao and Henderson, Keren and Li, Dingzeyu and Crowston, Kevin and Hansen, Mark and Nickerson, Jeffrey V and Chilton, Lydia B}, editor = {Mueller, Florian Floyd and Kyburz, Penny and Williamson, Julie R. and Sas, Corina and Wilson, Max L. and Dugas, Phoebe Toups and Shklovski, Irina} } @proceedings {petridis2023anglekindling, title = {AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models}, year = {2023}, doi = {10.1145/3544548.3580907}, url = {https://savvaspetridis.github.io/papers/anglekindling.pdf}, author = {Petridis, Savvas and Diakopoulos, Nicholas and Crowston, Kevin and Hansen, Mark and Henderson, Keren and Jastrzebski, Stan and Nickerson, Jefrey V and Chilton, Lydia B} } @conference {9999, title = {Project archetypes: A blessing and a curse for AI development}, booktitle = {International Conference on Information Systems (ICIS)}, year = {2022}, address = {Copenhagen, Denmark}, abstract = {

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

}, url = {https://aisel.aisnet.org/icis2022/is_design/is_design/6 }, attachments = {https://waim.network/sites/crowston.syr.edu/files/icis_archetypes_rev1_v20_zora.pdf}, author = {Mateusz Dolata and Kevin Crowston and Gerhard Schwabe} } @article {2021, title = {Hybrid intelligence in business networks}, journal = {Electronic Markets}, year = {2021}, month = {Nov-06-2021}, issn = {1019-6781}, doi = {10.1007/s12525-021-00481-4}, attachments = {https://waim.network/sites/crowston.syr.edu/files/Ebel2021_Article_HybridIntelligenceInBusinessNe.pdf}, author = {Ebel, Philipp and S{\"o}llner, Matthias and Leimeister, Jan Marco and Crowston, Kevin and de Vreede, Gert-Jan} } @article {Dogru2020, title = {AI in operations management: applications, challenges and opportunities}, journal = {Journal of Data, Information and Management}, volume = {2}, number = {2}, year = {2020}, pages = {67{\textendash}74}, publisher = {Journal of Data, Information and Management}, abstract = {We have witnessed unparalleled progress in artificial intelligence (AI) and machine learning (ML) applications in the last two decades. The AI technologies have accelerated advancements in robotics and automation, which have significant implications on almost every aspect of businesses, and especially supply chain operations. Supply chains have widely adopted smart technologies that enable real-time automated data collection, analysis, and prediction. In this study, we review recent applications of AI in operations management (OM) and supply chain management (SCM). Specifically, we consider the innovations in healthcare, manufacturing, and retail operations, since collectively, these three areas represent a majority of the AI innovations in business as well as growing problem areas. We discuss primary challenges and opportunities for utilizing AI in those industries. We also discuss trending research topics with significant value potential in these areas.}, keywords = {AI, artificial intelligence, Artificial Intelligence (AI), automation, machine learning, machine learning (ML), ml, om, operations management, Operations Management (OM), Robotics, scm, supply chain management, Supply Chain Management (SCM)}, issn = {2524-6356}, doi = {10.1007/s42488-020-00023-1}, author = {Dogru, Ali K and Keskin, Burcu B} } @conference {2020, title = {Algorithmic Journalism and Its Impacts on Work}, booktitle = {Computation + Journalism Symposium }, year = {2020}, edition = {(cancelled due to COVID; presented in 2021)}, abstract = {

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

}, url = {https://cpb-us-w2.wpmucdn.com/express.northeastern.edu/dist/d/53/files/2020/02/CJ_2020_paper_26.pdf}, attachments = {https://waim.network/sites/crowston.syr.edu/files/CJ_2020_paper_26.pdf}, author = {Ayse Dalgali and Kevin Crowston} } @conference {Dietzmann2020, title = {Assessing the Business Impact of Artificial Intelligence}, booktitle = {Proceedings of the 53rd Hawaii International Conference on System Sciences}, volume = {3}, year = {2020}, pages = {5170{\textendash}5179}, abstract = {El autor propone la creaci{\'o}n de una agencia que certificque los procesos de IA. El no certificado RCO. Tambien habla de las caracter{\'\i}sticas de la IA y la dificutlad para regularlas. Sustenta cual debe ser el ente encargado de regular la IA. Tiene en cuenta la historia de la IA y su evaluci{\'o}n en el mercado.}, isbn = {9780998133133}, doi = {10.24251/hicss.2020.635}, author = {Dietzmann, Christian and Alt, Rainer} } @article {Roccetti2020, title = {A Cautionary Tale for Machine Learning Design: why we Still Need Human-Assisted Big Data Analysis}, journal = {Mobile Networks and Applications}, volume = {25}, number = {3}, year = {2020}, pages = {1075{\textendash}1083}, publisher = {Mobile Networks and Applications}, abstract = {Supervised Machine Learning (ML) requires that smart algorithms scrutinize a very large number of labeled samples before they can make right predictions. And this is not always true either. In our experience, in fact, a neural network trained with a huge database comprised of over fifteen million water meter readings had essentially failed to predict when a meter would malfunction/need disassembly based on a history of water consumption measurements. With a second step, we developed a methodology, based on the enforcement of a specialized data semantics, that allowed us to extract only those samples for training that were not noised by data impurities. With this methodology, we re-trained the neural network up to a prediction accuracy of over 80\%. Yet, we simultaneously realized that the new training dataset was significantly different from the initial one in statistical terms, and much smaller, as well. We had reached a sort of paradox: We had alleviated the initial problem with a better interpretable model, but we had changed the replicated form of the initial data. To reconcile that paradox, we further enhanced our data semantics with the contribution of field experts. This has finally led to the extrapolation of a training dataset truly representative of regular/defective water meters and able to describe the underlying statistical phenomenon, while still providing an excellent prediction accuracy of the resulting classifier. At the end of this path, the lesson we have learnt is that a human-in-the-loop approach may significantly help to clean and re-organize noised datasets for an empowered ML design experience.}, keywords = {Human-in-the-loop methods, Human-machine-Bigdata interaction loop, Machine learning design, Smart data, Water metering and consumption}, issn = {15728153}, doi = {10.1007/s11036-020-01530-6}, author = {Roccetti, Marco and Delnevo, Giovanni and Casini, Luca and Salomoni, Paola} } @conference {Gerber2020, title = {Conceptualization of the Human-Machine Symbiosis {\textendash} A Literature Review}, booktitle = {Proceedings of the 53rd Hawaii International Conference on System Sciences}, volume = {3}, year = {2020}, pages = {289{\textendash}298}, abstract = {The vision of a symbiotic partnership between humans and machines has existed since the 1960s. With this paper we provide the first conceptualization of the human-machine symbiosis (HMS) and make three important contributions: we present the fundamentals of HMS by focusing on objectives, requirements, and boundaries; we propose a framework for the design of HMS; and we review HMS research and, specifically, what the literature says with respect to whether HMS has already been achieved.}, isbn = {9780998133133}, doi = {10.24251/hicss.2020.036}, author = {Gerber, Alina and Derckx, Patrick and D{\"o}ppner, Daniel A and Schoder, Detlef} } @article {GomezdeAgreda2020, title = {Ethics of autonomous weapons systems and its applicability to any AI systems}, journal = {Telecommunications Policy}, volume = {5}, number = {5}, year = {2020}, pages = {101953}, publisher = {Elsevier Ltd}, abstract = {Most artificial intelligence technologies are dual-use. They are incorporated into both peaceful civilian applications and military weapons systems. Most of the existing codes of conduct and ethical principles on artificial intelligence address the former while largely ignoring the latter. But when these technologies are used to power systems specifically designed to cause harm, the question must be asked as to whether the ethics applied to military autonomous systems should also be taken into account for all artificial intelligence technologies susceptible of being used for those purposes. However, while a freeze in investigations is neither possible nor desirable, neither is the maintenance of the current status quo. Comparison between general-purpose ethical codes and military ones concludes that most ethical principles apply to human use of artificial intelligence systems as long as two characteristics are met: that the way algorithms work is understood and that humans retain enough control. In this way, human agency is fully preserved and moral responsibility is retained independently of the potential dual-use of artificial intelligence technology.}, keywords = {AI ethics, Autonomous weapons, CCW, Dual-use AI, Explainability, Meaningful human control}, issn = {03085961}, doi = {10.1016/j.telpol.2020.101953}, url = {https://doi.org/10.1016/j.telpol.2020.101953}, author = {G{\'o}mez de {\'A}greda, {\'A}ngel} } @proceedings {2020, title = {Factors Influencing Approval of Wikipedia Bots}, year = {2020}, address = {Wailea, HI}, abstract = {

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

}, doi = {10.24251/HICSS.2020.018}, attachments = {https://waim.network/sites/crowston.syr.edu/files/HICSS_WikipediaPaper_3.9.new\%20kc\%20\%282\%29.pdf}, author = {Ayse Dalgali and Kevin Crowston} } @booklet {Suran2020, title = {Frameworks for collective intelligence: A systematic literature review}, howpublished = {ACM Computing Surveys}, volume = {53}, number = {1}, year = {2020}, pages = {1{\textendash}36}, abstract = {Over the last few years, Collective Intelligence (CI) platforms have become a vital resource for learning, problem solving, decision-making, and predictions. This rising interest in the topic has to led to the development of several models and frameworks available in published literature. Unfortunately, most of these models are built around domain-specific requirements, i.e., they are often based on the intuitions of their domain experts and developers. This has created a gap in our knowledge in the theoretical foundations of CI systems and models, in general. In this article, we attempt to fill this gap by conducting a systematic review of CI models and frameworks, identified from a collection of 9,418 scholarly articles published since 2000. Eventually, we contribute by aggregating the available knowledge from 12 CI models into one novel framework and present a generic model that describes CI systems irrespective of their domains. We add to the previously available CI models by providing a more granular view of how different components of CI systems interact. We evaluate the proposed model by examining it with respect to six popular, ongoing CI initiatives available on the Web.}, keywords = {collective intelligence, Crowdsourcing, Human computer interaction, Systematic literature review, Web 2.0, Wisdom of crowds}, issn = {15577341}, doi = {10.1145/3368986}, author = {Suran, Shweta and Pattanaik, Vishwajeet and Draheim, Dirk} } @article {EganadelSol2020, title = {The Future of Work in Developing Economies}, journal = {MIT Sloan Management Review}, volume = {61}, number = {2}, year = {2020}, pages = {1{\textendash}3}, abstract = {

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

}, keywords = {Armenia, Asia, Austria, automation, Bolivia, Business And Economics{\textendash}Management, China, Developing countries{\textendash}LDCs, Employment, future, Georgia (country), Ghana, Impact analysis, Kenya, Kuala Lumpur Malaysia, Laos, Republic of North Macedonia, South Korea, Sri Lanka, United States{\textendash}US, Vietnam, Workers}, issn = {15329194}, author = {Egana del Sol, Pablo and Joyce, Connor and Del Sol, Pablo Ega{\~n}a and Joyce, Connor} } @article {Delfanti2020, title = {Humanly Extended Automation or the Future of Work Seen through Amazon Patents}, journal = {Science, Technology, \& Human Values}, year = {2020}, pages = {016224392094366}, abstract = {

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

}, issn = {0162-2439}, doi = {10.1177/0162243920943665}, url = {http://journals.sagepub.com/doi/10.1177/0162243920943665}, author = {Delfanti, Alessandro and Frey, Bronwyn} } @conference {Das2020, title = {Learning occupational task-shares dynamics for the future of work}, booktitle = {AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society}, year = {2020}, pages = {36{\textendash}42}, abstract = {The recent wave of AI and automation has been argued to differ from previous General Purpose Technologies (GPTs), in that it may lead to rapid change in occupations{\textquoteright} underlying task requirements and persistent technological unemployment. In this paper, we apply a novel methodology of dynamic task shares to a large dataset of online job postings to explore how exactly occupational task demands have changed over the past decade of AI innovation, especially across high, mid and low wage occupations. Notably, big data and AI have risen significantly among high wage occupations since 2012 and 2016, respectively. We built an ARIMA model to predict future occupational task demands and showcase several relevant examples in Healthcare, Administration, and IT. Such task demands predictions across occupations will play a pivotal role in retraining the workforce of the future.}, keywords = {AI, automation, future of work, Occupational Task Demands}, isbn = {9781450371100}, doi = {10.1145/3375627.3375826}, author = {Das, Subhro and Steffen, Sebastian and Clarke, Wyatt and Reddy, Prabhat and Brynjolfsson, Erik and Fleming, Martin} } @article {Seeber2020, title = {Machines as teammates: A research agenda on AI in team collaboration}, journal = {Information and Management}, volume = {57}, number = {2}, year = {2020}, pages = {103174}, publisher = {Elsevier}, abstract = {What if artificial intelligence (AI) machines became teammates rather than tools? This paper reports on an international initiative by 65 collaboration scientists to develop a research agenda for exploring the potential risks and benefits of machines as teammates (MaT). They generated 819 research questions. A subteam of 12 converged them to a research agenda comprising three design areas {\textendash} Machine artifact, Collaboration, and Institution {\textendash} and 17 dualities {\textendash} significant effects with the potential for benefit or harm. The MaT research agenda offers a structure and archetypal research questions to organize early thought and research in this new area of study.}, keywords = {artificial intelligence, Design, Duality, Research agenda, Team collaboration}, issn = {03787206}, doi = {10.1016/j.im.2019.103174}, url = {https://doi.org/10.1016/j.im.2019.103174}, author = {Seeber, Isabella and Bittner, Eva and Briggs, Robert O and de Vreede, Triparna and de Vreede, Gert Jan and Elkins, Aaron and Maier, Ronald and Merz, Alexander B and Oeste-Rei{\ss}, Sarah and Randrup, Nils and Schwabe, Gerhard and S{\"o}llner, Matthias} } @booklet {Dottori2020, title = {Robots and employment: evidence from Italy}, howpublished = {Questioni di Economia e Finanza}, number = {572}, year = {2020}, publisher = {Banca d{\textquoteright}Italia}, abstract = {The relocation of more polluting industries in poorer countries due to gaps in environmental standards is known as the pollution haven effect, whereby the scale and the composition of output change across countries. Changes in the composition of the output mix might translate into changes of comparative advantages across countries, as revealed by trade flows. This paper focus on this issue and looks at the changes of bilateral revealed comparative advantages (RCAs) in the last decade between China and the major fourteen EU countries (EU14). Using industry level data on bilateral trade, air pollution, water pollution and several measures of environmental stringency, we find that, controlling for other factors that may have affected RCAs, such as labor costs, on average our EU14 countries have kept or improved their advantages with respect to China in both water polluting industries (such as paper and agro-based industries) and air polluting industries (such as basic metals and chemicals), while they have lost competitiveness in the more clean industries (such as machinery and fabricated metals).}, author = {Dottori, Davide} } @article {Brundage2020, title = {Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims}, year = {2020}, pages = {1{\textendash}9}, abstract = {With the recent wave of progress in artificial intelligence (AI) has come a growing awareness of the large-scale impacts of AI systems, and recognition that existing regulations and norms in industry and academia are insufficient to ensure responsible AI development. In order for AI developers to earn trust from system users, customers, civil society, governments, and other stakeholders that they are building AI responsibly, they will need to make verifiable claims to which they can be held accountable. Those outside of a given organization also need effective means of scrutinizing such claims. This report suggests various steps that different stakeholders can take to improve the verifiability of claims made about AI systems and their associated development processes, with a focus on providing evidence about the safety, security, fairness, and privacy protection of AI systems. We analyze ten mechanisms for this purpose{\textendash}spanning institutions, software, and hardware{\textendash}and make recommendations aimed at implementing, exploring, or improving those mechanisms.}, url = {http://arxiv.org/abs/2004.07213}, author = {Brundage, Miles and Avin, Shahar and Wang, Jasmine and Belfield, Haydn and Krueger, Gretchen and Hadfield, Gillian and Khlaaf, Heidy and Yang, Jingying and Toner, Helen and Fong, Ruth and Maharaj, Tegan and Koh, Pang Wei and Hooker, Sara and Leung, Jade and Trask, Andrew and Bluemke, Emma and Lebensold, Jonathan and O{\textquoteright}Keefe, Cullen and Koren, Mark and Ryffel, Th{\'e}o and Rubinovitz, JB and Besiroglu, Tamay and Carugati, Federica and Clark, Jack and Eckersley, Peter and de Haas, Sarah and Johnson, Maritza and Laurie, Ben and Ingerman, Alex and Krawczuk, Igor and Askell, Amanda and Cammarota, Rosario and Lohn, Andrew and Krueger, David and Stix, Charlotte and Henderson, Peter and Graham, Logan and Prunkl, Carina and Martin, Bianca and Seger, Elizabeth and Zilberman, Noa and H{\'E}igeartaigh, Se{\'a}n {\'O} and Kroeger, Frens and Sastry, Girish and Kagan, Rebecca and Weller, Adrian and Tse, Brian and Barnes, Elizabeth and Dafoe, Allan and Scharre, Paul and Herbert-Voss, Ariel and Rasser, Martijn and Sodhani, Shagun and Flynn, Carrick and Gilbert, Thomas Krendl and Dyer, Lisa and Khan, Saif and Bengio, Yoshua and Anderljung, Markus} } @conference {Ferreira2020, title = {Understanding the Impact of Artificial Intelligence on Services}, booktitle = {International Conference on Exploring Services Science}, series = {Lecture Notes in Business Information Processing}, volume = {1}, number = {January}, year = {2020}, pages = {202{\textendash}213}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {The service sector is changing drastically due the use of robotics and other technologies, such as Artificial Intelligence (AI), Internet of things (IoT), Big Data and Biometrics. Consequently, further research opportunities in the service industry domain are also expected. In light of the above, the purpose of this paper is to explore the potentialities and limitations of service robots in the hospitality industry. To this end, this paper uses a conceptual approach based on a literature review. As a result, we found that in contexts of high customer contact, service robots should be considered to perform standardized tasks due to social/emotional and cognitive/analytical complexity. The hospitality industry is therefore considered closely related to empathic intelligence, as the integration of service robots has not yet reached the desired stage of service delivery. In a seemingly far-fetched context of our reality, organizations will have to decide whether the AI will allow the complete replacement of humans with robots capable of performing the necessary cognitive and emotional tasks. Or investing in balanced capacities by integrating robot-human systems that seems a rea- sonable option these days. Keywords:}, keywords = {{\'a} servitization {\'a} design, science research, service design}, isbn = {9783030387242}, doi = {10.1007/978-3-030-38724-2}, url = {http://link.springer.com/10.1007/978-3-030-38724-2}, author = {Ferreira, Pedro and Teixeira, Jorge Grenha and Teixeira, Lu{\'\i}s F.}, editor = {N{\'o}voa, Henriqueta and Dr{\u a}goicea, Monica and K{\"u}hl, Niklas} } @article {2019, title = {Are robots stealing our jobs? }, journal = {Socius: Sociological Research for a Dynamic World}, volume = {5}, year = {2019}, month = {Oct-01-2019}, pages = {237802311984624}, issn = {2378-0231}, doi = {10.1177/2378023119846249}, author = {Dahlin, Eric} } @article {2019, title = {Artificial Intelligence and the Future of the Drug Safety Professional}, journal = {Drug Safety}, volume = {42}, year = {2019}, month = {Jan-04-2019}, pages = {491 - 497}, issn = {0114-5916}, doi = {10.1007/s40264-018-0746-z}, author = {Danysz, Karolina and Cicirello, Salvatore and Mingle, Edward and Assuncao, Bruno and Tetarenko, Niki and Mockute, Ruta and Abatemarco, Danielle and Widdowson, Mark and Desai, Sameen} } @book {2019, title = {Benefits and risks of artificial intelligence tools in workplaces}, volume = {11581}, year = {2019}, pages = {292 - 315}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-22215-4}, issn = {0302-9743}, doi = {10.1007/978-3-030-22216-1_22}, author = {Moore, Phoebe V.}, editor = {Duffy, Vincent G.} } @article {2019, title = {A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task}, journal = {European Journal of Cancer}, volume = {111}, year = {2019}, month = {Jan-04-2019}, pages = {148 - 154}, issn = {09598049}, doi = {10.1016/j.ejca.2019.02.005}, author = {Brinker, Titus J. and Hekler, Achim and Alexander Enk and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Fr{\"o}hling, Stefan and Jochen Sven Utikal and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenh{\"o}fer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Sondermann, Wiebke and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Alexander Enk and Gholam, Patrick and H{\"a}n{\ss}le, Holger and Salzmann, Martin and Sch{\"a}fer, Sarah and Sch{\"a}kel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Hauschild, Axel and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and St{\"o}lzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and B{\"a}r, Claudia Maria and Bender-S{\"a}belkampf, Sophia and Horbr{\"u}gger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, J{\"o}rg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and M{\"u}ller, Verena and Thomas, Benjamin and Jochen Sven Utikal and Alamri, Ali Saeed M. and Baczako, Andrea and Berking, Carola and Betke, Matthias and Haas, Carolin and Hartmann, Daniela and Heppt, Markus V. and Kilian, Katharina and Krammer, Sebastian and Lapczynski, Natalie Lidia and Mastnik, Sebastian and Nasifoglu, Suzan and Ruini, Cristel and Sattler, Elke and Schlaak, Max and Wolff, Hans and Achatz, Birgit and Bergbreiter, Astrid and Drexler, Konstantin and Ettinger, Monika and Haferkamp, Sebastian and Halupczok, Anna and Hegemann, Marie and Dinauer, Verena and Maagk, Maria and Mickler, Marion and Philipp, Biance and Wilm, Anna and Wittmann, Constanze and Gesierich, Anja and Glutsch, Valerie and Kahlert, Katrin and Kerstan, Andreas and Schilling, Bastian and Schr{\"u}fer, Philipp} } @article {2019, title = {Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task}, journal = {European Journal of Cancer}, volume = {113}, year = {2019}, month = {Jan-05-2019}, pages = {47 - 54}, issn = {09598049}, doi = {10.1016/j.ejca.2019.04.001}, author = {Brinker, Titus J. and Hekler, Achim and Alexander Enk and Klode, Joachim and Hauschild, Axel and Berking, Carola and Schilling, Bastian and Haferkamp, Sebastian and Schadendorf, Dirk and Holland-Letz, Tim and Jochen Sven Utikal and von Kalle, Christof and Ludwig-Peitsch, Wiebke and Sirokay, Judith and Heinzerling, Lucie and Albrecht, Magarete and Baratella, Katharina and Bischof, Lena and Chorti, Eleftheria and Dith, Anna and Drusio, Christina and Giese, Nina and Gratsias, Emmanouil and Griewank, Klaus and Hallasch, Sandra and Hanhart, Zdenka and Herz, Saskia and Hohaus, Katja and Jansen, Philipp and Jockenh{\"o}fer, Finja and Kanaki, Theodora and Knispel, Sarah and Leonhard, Katja and Martaki, Anna and Matei, Liliana and Matull, Johanna and Olischewski, Alexandra and Petri, Maximilian and Placke, Jan-Malte and Raub, Simon and Salva, Katrin and Schlott, Swantje and Sody, Elsa and Steingrube, Nadine and Stoffels, Ingo and Ugurel, Selma and Zaremba, Anne and Gebhardt, Christoffer and Booken, Nina and Christolouka, Maria and Buder-Bakhaya, Kristina and Bokor-Billmann, Therezia and Alexander Enk and Gholam, Patrick and H{\"a}n{\ss}le, Holger and Salzmann, Martin and Sch{\"a}fer, Sarah and Sch{\"a}kel, Knut and Schank, Timo and Bohne, Ann-Sophie and Deffaa, Sophia and Drerup, Katharina and Egberts, Friederike and Erkens, Anna-Sophie and Ewald, Benjamin and Falkvoll, Sandra and Gerdes, Sascha and Harde, Viola and Hauschild, Axel and Jost, Marion and Kosova, Katja and Messinger, Laetitia and Metzner, Malte and Morrison, Kirsten and Motamedi, Rogina and Pinczker, Anja and Rosenthal, Anne and Scheller, Natalie and Schwarz, Thomas and St{\"o}lzl, Dora and Thielking, Federieke and Tomaschewski, Elena and Wehkamp, Ulrike and Weichenthal, Michael and Wiedow, Oliver and B{\"a}r, Claudia Maria and Bender-S{\"a}belkampf, Sophia and Horbr{\"u}gger, Marc and Karoglan, Ante and Kraas, Luise and Faulhaber, J{\"o}rg and Geraud, Cyrill and Guo, Ze and Koch, Philipp and Linke, Miriam and Maurier, Nolwenn and M{\"u}ller, Verena and Thomas, Benjamin and Jochen Sven Utikal and Alamri, Ali Saeed M. and Baczako, Andrea and Berking, Carola and Betke, Matthias and Haas, Carolin and Hartmann, Daniela and Heppt, Markus V. and Kilian, Katharina and Krammer, Sebastian and Lapczynski, Natalie Lidia and Mastnik, Sebastian and Nasifoglu, Suzan and Ruini, Cristel and Sattler, Elke and Schlaak, Max and Wolff, Hans and Achatz, Birgit and Bergbreiter, Astrid and Drexler, Konstantin and Ettinger, Monika and Haferkamp, Sebastian and Halupczok, Anna and Hegemann, Marie and Dinauer, Verena and Maagk, Maria and Mickler, Marion and Philipp, Biance and Wilm, Anna and Wittmann, Constanze and Gesierich, Anja and Glutsch, Valerie and Kahlert, Katrin and Kerstan, Andreas and Schilling, Bastian and Schr{\"u}fer, Philipp} } @conference {2019, title = {Does automation influence career decisions among South African students?}, booktitle = {the South African Institute of Computer Scientists and Information Technologists 2019Proceedings of the South African Institute of Computer Scientists and Information Technologists 2019 on ZZZ - SAICSIT {\textquoteright}19}, year = {2019}, pages = {1 - 10}, publisher = {ACM Press}, organization = {ACM Press}, address = {Skukuza, South AfricaNew York, New York, USA}, isbn = {9781450372657}, doi = {10.1145/335110810.1145/3351108.3351137}, author = {Mbilini, Sakhumzi N. and le Roux, Daniel B. and Parry, Douglas A.} } @article {2019, title = {Economic, Social Impacts and Operation of Smart Factories in Industry 4.0 Focusing on Simulation and Artificial Intelligence of Collaborating Robots}, journal = {Social Sciences}, volume = {8}, year = {2019}, month = {Jan-05-2019}, pages = {143}, doi = {10.3390/socsci8050143}, author = {Benotsmane, Rabab and Kov{\'a}cs, Gy{\"o}rgy and Dud{\'a}s, L{\'a}szl{\'o}} } @article {2019, title = {Emotional processes in human-robot interaction during brief cognitive testing}, journal = {Computers in Human Behavior}, volume = {90}, year = {2019}, month = {Jan-01-2019}, pages = {331 - 342}, issn = {07475632}, doi = {10.1016/j.chb.2018.08.013}, author = {Desideri, Lorenzo and Ottaviani, Cristina and Malavasi, Massimiliano and di Marzio, Roberto and Bonifacci, Paola} } @conference {2019, title = {Fairer but not fair enough on the equitability of knowledge tracing}, booktitle = {the 9th International ConferenceProceedings of the 9th International Conference on Learning Analytics \& Knowledge - LAK19}, year = {2019}, pages = {335 - 339}, publisher = {ACM Press}, organization = {ACM Press}, address = {Tempe, AZ, USANew York, New York, USA}, isbn = {9781450362566}, doi = {10.1145/3303772.3303838}, author = {Doroudi, Shayan and Brunskill, Emma} } @article {2019, title = {The future of health care: Protocol for measuring the potential of task automation grounded in the national health service primary care system}, journal = {JMIR Research Protocols}, volume = {8}, year = {2019}, month = {Jan-01-2019}, pages = {e11232}, doi = {10.2196/11232}, author = {Willis, Matthew and Duckworth, Paul and Coulter, Angela and Meyer, Eric T and Osborne, Michael} } @conference {2019, title = {The future of human-AI collaboration: A taxonomy of design knowledge for hybrid intelligence systems}, booktitle = {Hawaii International Conference on System Sciences (HICSS)}, year = {2019}, month = {09/2018}, abstract = {Recent technological advances, especially in the field of machine learning, provide astonishing progress on the road towards artificial general intelligence. However, tasks in current real-world business applications cannot yet be solved by machines alone. We, therefore, identify the need for developing socio-technological ensembles of humans and machines. Such systems possess the ability to accomplish complex goals by combining human and artificial intelligence to collectively achieve superior results and continuously improve by learning from each other. Thus, the need for structured design knowledge for those systems arises. Following a taxonomy development method, this article provides three main contributions: First, we present a structured overview of interdisciplinary research on the role of humans in the machine learning pipeline. Second, we envision hybrid intelligence systems and conceptualize the relevant dimensions for system design for the first time. Finally, we offer useful guidance for system developers during the implementation of such applications.}, url = {https://www.alexandria.unisg.ch/publications/254994}, author = {Dominik Dellermann and Adrian Calma and Nikolaus Lipusch and Thorsten Weber and Sascha Weigel and Philipp Ebel} } @article {2019, title = {The future of the work in America}, year = {2019}, month = {07/2019}, keywords = {consulting reports}, url = {https://www.mckinsey.com/featured-insights/future-of-work/the-future-of-work-in-america-people-and-places-today-and-tomorrow}, author = {Susan Lund and James Manyika and Liz Hilton Segal and Andre Dua and Bryan Hancock and Scott Rutherford and Brent Macon} } @article {2019, title = {Governance of artificial intelligence and personal health information}, journal = {Digital Policy, Regulation and Governance}, volume = {21}, year = {2019}, month = {Jan-05-2020}, pages = {280 - 290}, issn = {2398-5038}, doi = {10.1108/DPRG-08-2018-0048}, author = {Winter, Jenifer Sunrise and Davidson, Elizabeth} } @article {2019, title = {Hybrid Intelligence}, journal = {Business \& Information Systems Engineering}, volume = {61}, year = {2019}, month = {Jan-10-2019}, pages = {637 - 643}, issn = {2363-7005}, doi = {10.1007/s12599-019-00595-2}, author = {Dellermann, Dominik and Ebel, Philipp and S{\"o}llner, Matthias and Leimeister, Jan Marco} } @conference {2019, title = {Inferring work task automatability from AI expert evidence}, booktitle = {the 2019 AAAI/ACM ConferenceProceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society - AIES {\textquoteright}19}, year = {2019}, pages = {485 - 491}, publisher = {ACM Press}, organization = {ACM Press}, address = {Honolulu, HI, USANew York, New York, USA}, isbn = {9781450363242}, doi = {10.1145/330661810.1145/3306618.3314247}, author = {Duckworth, Paul and Graham, Logan and Osborne, Michael} } @article {2019, title = {Physician perspectives on integration of artificial intelligence into diagnostic pathology}, journal = {npj Digital Medicine}, volume = {2}, year = {2019}, month = {Jan-12-2019}, doi = {10.1038/s41746-019-0106-0}, author = {Sarwar, Shihab and Dent, Anglin and Faust, Kevin and Richer, Maxime and Djuric, Ugljesa and Van Ommeren, Randy and Diamandis, Phedias} } @article {2019, title = {The potential for artificial intelligence in healthcare}, journal = {Future Healthcare Journal}, volume = {6}, year = {2019}, month = {Jan-06-2020}, pages = {94 - 98}, issn = {2514-6645}, doi = {10.7861/futurehosp.6-2-94}, author = {Davenport, Thomas and Kalakota, Ravi} } @book {2019, title = {Toward a conceptual framework for understanding AI action and legal reaction}, volume = {11489}, year = {2019}, pages = {453 - 459}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-030-18304-2}, issn = {0302-9743}, doi = {10.1007/978-3-030-18305-9_44}, author = {Dahya, Raheena and Morris, Alexis}, editor = {Meurs, Marie-Jean and Rudzicz, Frank} } @article {Frank2019, title = {Toward understanding the impact of artificial intelligence on labor}, journal = {Proceedings of the National Academy of Sciences}, volume = {116}, year = {2019}, month = {apr}, pages = {6531{\textendash}6539}, abstract = {

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

}, issn = {0027-8424}, doi = {10.1073/pnas.1900949116}, url = {http://www.pnas.org/lookup/doi/10.1073/pnas.1900949116}, author = {Frank, Morgan R and Autor, David and Bessen, James E and Brynjolfsson, Erik and Cebrian, Manuel and Deming, David J and Feldman, Maryann and Groh, Matthew and Lobo, Jos{\'e} and Moro, Esteban and Wang, Dashun and Youn, Hyejin and Rahwan, Iyad} } @article {2019, title = {Towards a smart automated society: Cognitive technologies, knowledge production, and economic growth}, journal = {Economics, Management, and Financial Markets}, volume = {14}, year = {2019}, month = {Jan-01-2019}, pages = {44}, issn = {1842-3191}, doi = {10.22381/EMFM14120195}, author = {Mitchell Udell and Vojtech Stehel and Tomas Kliestik and Jana Kliestikova and Pavol Durana} } @article {2018, title = {Accounting for the neglected dimensions of AI progress}, journal = {data-efficient ML}, year = {2018}, url = {https://arxiv.org/abs/1806.00610}, author = {Fernando Martine-Plumed and Shahar Avin and Miles Brundage and Allan Dafoe and Sean O hEigeartaigh and Jos{\'e} Hern{\'a}ndez-Orallo} } @article {2018, title = {Artificial intelligence and privacy in the fourth industrial revolution}, year = {2018}, institution = {Institute for Philosophy \& Public Policy}, url = {https://www.wilsoncenter.org/sites/default/files/ai_and_privacy.pdf}, author = {Sarah W. Denton and Eleonore Pauwels} } @article {2018, title = {Artificial Intelligence in Cardiology}, journal = {Journal of the American College of Cardiology}, volume = {71}, year = {2018}, month = {Jan-06-2018}, pages = {2668 - 2679}, issn = {07351097}, doi = {10.1016/j.jacc.2018.03.521}, author = {Johnson, Kipp W. and Torres Soto, Jessica and Glicksberg, Benjamin S. and Shameer, Khader and Miotto, Riccardo and Ali, Mohsin and Ashley, Euan and Joel T. Dudley} } @article {2018, title = {As s essing the impact of machine intelligence on human behaviour: an interdisciplinary endeavour}, year = {2018}, url = {https://arxiv.org/ftp/arxiv/papers/1806/1806.03192.pdf}, author = {Emilia G{\'o}mez and Carlos Castillo and Vicky Charisi and Ver{\'o}nica Dahl and Gustavo Deco and Blagoj Delipetrev and Nicole Dewandre and Miguel {\'A}ngel Gonz{\'a}lez-Ballester and Fabien Gouyon and Jos{\'e} Hern{\'a}ndez-Orallo and Perfecto Herrera and Anders Jonsson and Ansgar Koene and Martha Larson and Ram{\'o}n L{\'o}pez de M{\'a}ntaras and Bertin Martens and Marius Miron and Rub{\'e}n Moreno-Bote and Nuria Oliver and Antonio Puertas Gallardo and Heike Schweitzer and Nuria Sebastian and Xavier Serra and Joan Serr{\`a} and Song{\"u}l Tolan and Karina Vold} } @article {2018, title = {Collaborative intelligence: Humans and AI are joining forces}, year = {2018}, url = {https://hbr.org/2018/07/collaborative-intelligence-humans-and-ai-are-joining-forces}, author = {H. James Wilson and Paul R. Daugherty} } @article {2018, title = {A critical approach to human helping in information systems: Heteromation in the Brazilian correspondent banking system}, journal = {Information and Organization}, volume = {28}, year = {2018}, month = {Jan-09-2018}, pages = {111 - 128}, issn = {14717727}, doi = {10.1016/j.infoandorg.2018.08.002}, author = {Diane E. Bailey and Eduardo H. Diniz and Bonnie A. Nardi and Paul M. Leonardi and Dan Sholler} } @book {2018, title = {A critical review of the politics of artificial intelligent machines, alienation and the existential risk threat to America{\textquoteright}s labour force}, volume = {10963}, year = {2018}, pages = {217 - 232}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-95170-6}, issn = {0302-9743}, doi = {10.1007/978-3-319-95171-3_18}, author = {Wogu, Ikedinachi Ayodele and Misra, Sanjay and Assibong, Patrick and Adewumi, Adewole and Damasevicius, Robertas and Maskeliunas, Rytis}, editor = {Gervasi, Osvaldo and Murgante, Beniamino and Misra, Sanjay and Stankova, Elena and Torre, Carmelo M. and Rocha, Ana Maria A.C. and Taniar, David and Apduhan, Bernady O. and Tarantino, Eufemia and Ryu, Yeonseung} } @book {2018, title = {Data Science for Undergraduates}, year = {2018}, publisher = {National Academies Press}, organization = {National Academies Press}, address = {Washington, D.C.}, isbn = {978-0-309-47559-4}, doi = {10.17226/25104}, url = {https://www.nap.edu/catalog/25104} } @article {2018, title = {Digital economy and the models of income distribution in the society}, journal = {SHS Web of Conferences}, volume = {44}, year = {2018}, month = {Jan-01-2018}, pages = {00005}, doi = {10.1051/shsconf/20184400005}, author = {Akaev, Askar and Rudskoi, Andrew and Devezas, Tessaleno}, editor = {Sarygulov, A. and Sergeev, V. and Ungv{\'a}ri, L. and Semmler, W.} } @article {2018, title = {The discourse approach to boundary identification and corpus construction for theory review articles}, journal = {Journal of the Association for Information Systems}, year = {2018}, keywords = {article identification, boundary identification, citation search, keyword search, literature review, machine learning, research review, review article}, url = {https://www.researchgate.net/publication/325215971_Understanding_the_Elephant_The_Discourse_Approach_to_Boundary_Identification_and_Corpus_Construction_for_Theory_Review_Articles}, author = {Kai R. Larsen and Dirik S. Hovorka and Alan R. Dennis and Jevin D. West} } @article {2018, title = {The evolving role of ICT in the economy}, year = {2018}, month = {06/2018}, keywords = {consulting reports}, url = {http://www.lse.ac.uk/business-and-consultancy/consulting/consulting-reports/the-evolving-role-of-ict-in-the-economy}, author = {Mirko Draca and Ralf Martin and Rosa Sanchis-Guarner} } @article {2018, title = {Exploiting ability for human adaptation to facilitate improved human-robot interaction and acceptance}, journal = {The Information Society}, volume = {34}, year = {2018}, month = {Mar-05-2020}, pages = {153 - 165}, issn = {0197-2243}, doi = {10.1080/01972243.2018.1444255}, author = {Caleb-Solly, Praminda and Dogramadzi, Sanja and Huijnen, Claire A.G.J. and Heuvel, Herjan van den} } @conference {2018, title = {A framework for understanding chatbots and their future}, booktitle = {the 11th International WorkshopProceedings of the 11th International Workshop on Cooperative and Human Aspects of Software Engineering - CHASE {\textquoteright}18}, year = {2018}, pages = {13 - 16}, publisher = {ACM Press}, organization = {ACM Press}, address = {Gothenburg, SwedenNew York, New York, USA}, isbn = {9781450357258}, doi = {10.1145/3195836.3195859}, author = {Paikari, Elahe and van der Hoek, Andr{\'e}} } @article {2018, title = {The future of work in the light of technological change}, volume = {UDC: 005.32:005.95/.96}, year = {2018}, type = {Original Scientific Paper}, abstract = {Abstract: Technological unemployment, a phenomenon that has been relevant for decades, is now reaching a new dimension. There is a growing number of discussions about whether technology is the main culprit for the rising trend of unemployment rates around the world, therefore, the paper discusses the impact of technological changes on the labour market. We conducted a survey in Slovenian companies with more than 100 employees in order to find out their view on replacing workers with technology, as well as the reasons and consequences of new technology. We discussed the results of our research and the views, findings and suggestions of various authors. We have found that technological unemployment is not a simple problem, as this phenomenon is intertwined with various issues, and that technology presents various dangers which may at first seem less visible.}, keywords = {Impact of technology on the labour market, Labour market, Technological unemployment}, url = {http://media3.novi.economicsandlaw.org/2017/07/Vol23/IJEAL-23-09.pdf}, author = {Vesna Novak and Denis Dizdarevic} } @article {2018, title = {How do machine learning, robotic process automation, and blockchains affect the human factor in business process management? }, journal = {Communications of the Association for Information Systems}, year = {2018}, month = {Jan-01-2018}, pages = {297 - 320}, doi = {10.17705/1CAIS.04319}, author = {Mendling, Jan and Decker, Gero and Hull, Richard and Reijers, Hajo A. and Weber, Ingo} } @article {2018, title = {How does the digital transformation affect organizations? Key themes of change in work design and leadership}, journal = {management revu}, volume = {29}, year = {2018}, month = {Jan-01-2018}, pages = {114 - 138}, issn = {0935-9915}, doi = {10.5771/0935-9915-2018-2-114}, author = {Schwarzm{\"u}ller, Tanja and Brosi, Prisca and Duman, Denis and Welpe, Isabell M.} } @conference {2018, title = {Image Recognition of Disease-Carrying Insects: A System for Combating Infectious Diseases Using Image Classification Techniques and Citizen Science}, booktitle = {Hawaii International Conference on System SciencesProceedings of the 51st Hawaii International Conference on System Sciences}, year = {2018}, publisher = {Hawaii International Conference on System Sciences}, organization = {Hawaii International Conference on System Sciences}, doi = {10.24251/HICSS.2018.00010.24251/HICSS.2018.359}, url = {http://hdl.handle.net/10125/49887http://hdl.handle.net/10125/50247}, author = {Munoz, J. Pablo and Boger, Rebecca and Dexter, Scott and Low, Russanne and Li, Justin} } @article {2018, title = {Improving palliative care with deep learning}, journal = {BMC Medical Informatics and Decision Making}, volume = {18}, year = {2018}, month = {Jan-12-2018}, doi = {10.1186/s12911-018-0677-8}, author = {Avati, Anand and Jung, Kenneth and Harman, Stephanie and Downing, Lance and Ng, Andrew and Shah, Nigam H.} } @proceedings {2018, title = {A literature Analysis of Research on Artificial Intelligence in Management Information System (MIS)}, year = {2018}, abstract = {This article presents an overview of Artificial Intelligence (AI) research applied in the Management Information System field by analyzing the databases of the AIS journal basket list representing the major international journal on MIS. AN initial set of 438 published papers was identified based on our search criteria. From those, 74 were selected because of their appropriate fit with the research questions. They were organized into domains, type of research, data collection strategy and AI techniques. We found; (1) MIS Quarterly published 42\% of the papers; (2) 50\% of studies were on Information Systems applications, followed by 15\% on Knowledge Management; and (3) 7 AI techniques were presented. This paper provides an overview of applied AI in Management, highlights the most studies related topics and techniques and contributes to a research agenda on the subject.}, keywords = {artificial intelligence, Information Systems, Literature Analysis}, author = {Alexandre Moreira Nascimento and Maria Alexandra V. C. da Cunha and Fernando de Souza Meirelles and Eusebio Scornavacca and Vinicius Veloso de Melo} } @conference {2018, title = {Machines as Teammates: A Collaboration Research Agenda}, booktitle = {Hawaii International Conference on System Sciences}, year = {2018}, publisher = {Hawaii International Conference on System Sciences}, organization = {Hawaii International Conference on System Sciences}, doi = {10.24251/HICSS.2018.055}, url = {http://hdl.handle.net/10125/49887}, attachments = {https://waim.network/sites/crowston.syr.edu/files/SeeberEtAl_2018_MachinesAsTeammates.pdf}, author = {Seeber, Isabella and Bittner, Eva and Briggs, Robert O. and de Vreede, Gert-Jan and de Vreede, Triparna and Druckenmiller, Doug and Maier, Ronald and Merz, Alexander B. and Oeste-Rei{\ss}, Sarah and Randrup, Nils and Gerhard Schwabe and S{\"o}llner, Matthias} } @article {2018, title = {Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR)}, journal = {Systematic Reviews}, year = {2018}, month = {2018}, publisher = {Springer}, type = {Review}, abstract = {Systematic reviews (SR) are vital to health care, but have become complicated and time-consuming, due to the rapid expansion of evidence to be synthesised. Fortunately, many tasks of systematic reviews have the potential to be automated or may be assisted by automation. Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. Automation tools need to be able to work together, to exchange data and results. Therefore, we initiated the International Collaboration for the Automation of Systematic Reviews (ICASR), to successfully put all the parts of automation of systematic review production together. The first meeting was held in Vienna in October 2015. We established a set of principles to enable tools to be developed and integrated into toolkits. This paper sets out the principles devised at that meeting, which cover the need for improvement in efficiency of SR tasks, automation across the spectrum of SR tasks, continuous improvement, adherence to high quality standards, flexibility of use and combining components, the need for a collaboration and varied skills, the desire for open source, shared code and evaluation, and a requirement for replicability through rigorous and open evaluation. Automation has a great potential to improve the speed of systematic reviews. Considerable work is already being done on many of the steps involved in a review. The {\textquoteright}Vienna Principles{\textquoteright} set out in this paper aim to guide a more coordinated effort which will allow the integration of work by separate teams and build on the experience, code and evaluations done by the many teams working across the globe.}, keywords = {automation, Collaboration, Systematic review}, doi = {10.1186/s13643-018-0740-7}, author = {Elaine Beller and Justin Clark and Guy Tsafnat and Clive Adams and Heinz Diehl and Hans Lund and Mourad Ouzzani and Kristina Thayer and James Thomas and Tari Turner and Jun Xia and Karen Robinson and Paul Glasziou} } @article {2018, title = {Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR)}, journal = {Systematic Reviews}, volume = {7}, year = {2018}, month = {Jan-12-2018}, keywords = {science}, doi = {10.1186/s13643-018-0740-7}, author = {Elaine Beller and Justin Clark and Guy Tsafnat and Clive Adams and Heinz Diehl and Hans Lund and Mourad Ouzzani and Kristina Thayer and James Thomas and Tari Turner and Jun Xia and Karen Robinson and Paul Glasziou} } @article {2018, title = {The nordic future of work drivers, institutions, and politics}, year = {2018}, institution = {Nordic Council of Ministers}, url = {https://norden.diva-portal.org/smash/get/diva2:1265618/FULLTEXT01.pdf}, author = {Jon Erik D{\o}lvik and Johan R{\o}ed Steen} } @article {2018, title = {A principled machine learning framework improves accuracy of stage II colorectal cancer prognosis}, journal = {npj Digital Medicine}, volume = {1}, year = {2018}, month = {Jan-12-2018}, doi = {10.1038/s41746-018-0057-x}, author = {Dimitriou, Neofytos and Arandjelovi{\'c}, Ognjen and Harrison, David J. and Caie, Peter D.} } @article {aroyo2018reports, title = {Reports of the Workshops Held at the Sixth AAAI Conference on Human Computation and Crowdsourcing}, journal = {AI Magazine}, volume = {39}, year = {2018}, pages = {57{\textendash}63}, author = {Aroyo, Lora and Dumitrache, Anca and Jeffrey V Nickerson and Lease, Matthew and Michelucci, Pietro} } @article {2018, title = {Robots and computers enhance us more than they replace us}, journal = {The American Economist}, year = {2018}, month = {Oct-08-2018}, pages = {056943451879267}, issn = {0569-4345}, doi = {10.1177/0569434518792674}, author = {Diamond, Arthur M.} } @article {2018, title = {Skill shift automation and the future of the workforce}, year = {2018}, month = {05/2018}, url = {https://www.mckinsey.com/featured-insights/future-of-work/skill-shift-automation-and-the-future-of-the-workforce}, author = {Jaccques Bughin and Eric Hazan and Susan Lund and Peter Dahlstrom and Anna Wiesinger and Amresh Subramaniam} } @article {2018, title = {System architecture of a driverless electric car in the grand cooperative driving challenge}, journal = {IEEE Intelligent Transportation Systems Magazine}, volume = {10}, year = {2018}, month = {Jan-21-2018}, pages = {47 - 59}, issn = {1939-1390}, doi = {10.1109/MITS.2017.2776135}, author = {Xu, Philippe and Dherbomez, Gerald and Hery, Elwan and Abidli, Abderrahmen and Bonnifait, Philippe} } @article {2018, title = {When Will AI Exceed Human Performance? Evidence from AI Experts}, year = {2018}, url = {https://jair.org/index.php/jair/article/download/11222/26431/}, author = {Katja Grace and John Salvatier and Allan Dafoe and Baobao Zhang and Owain Evans} } @inbook {2017, title = {Agents as collaborating team members}, year = {2017}, month = {09/2017}, publisher = {EBSCO}, organization = {EBSCO}, keywords = {bots}, url = {https://www.taylorfrancis.com/books/e/9781315593166/chapters/10.1201/9781315593166-7}, author = {Abhijit V. Deshmukh and Sara A.McComb and Christian Wernz} } @article {2017, title = {Artificial Intelligence For Social Good}, year = {2017}, note = {Sponsored by the Computing Community Consortium (CCC)}, url = {https://cra.org/ccc/wp-content/uploads/sites/2/2016/04/AI-for-Social-Good-Workshop-Report.pdf}, author = {Gregory D. Hager and Ann Drobnis and Fei Fang and Rayid Ghani and Amy Greenwald and Terah Lyons and David C. Parkes and Jason Schultz and Suchi Saria and Stephen F. Smith and Milind Tambe} } @article {2017, title = {Artificial intelligence in healthcare: past, present and future}, journal = {Stroke and Vascular Neurology}, volume = {2}, year = {2017}, month = {Aug-12-2018}, pages = {230 - 243}, issn = {2059-8688}, doi = {10.1136/svn-2017-000101}, author = {Jiang, Fei and Jiang, Yong and Zhi, Hui and Dong, Yi and Li, Hao and Ma, Sufeng and Wang, Yilong and Dong, Qiang and Shen, Haipeng and Wang, Yongjun} } @article {2017, title = {Artificial intelligence in research}, journal = {Science}, volume = {357}, year = {2017}, month = {Jul-07-2017}, pages = {28 - 30}, issn = {0036-8075}, doi = {10.1126/science.357.6346.28}, author = {Musib, Mrinal and Wang, Feng and Tarselli, Michael A. and Yoho, Rachel and Yu, Kun-Hsing and Andr{\'e}s, Rigoberto Medina and Greenwald, Noah F. and Pan, Xubin and Lee, Chien-Hsiu and Zhang, Jian and Dutton-Regester, Ken and Johnston, Jake Wyatt and Sharafeldin, Icell Mahmoud} } @article {2017, title = {Artificial Intelligence: The next digital frontier}, year = {2017}, url = {https://www.mckinsey.com/~/media/McKinsey/Industries/Advanced\%20Electronics/Our\%20Insights/How\%20artificial\%20intelligence\%20can\%20deliver\%20real\%20value\%20to\%20companies/MGI-Artificial-Intelligence-Discussion-paper.ashx}, author = {Jaccques Bughin and Eric Hazan and Sree Ramaswamy and Michael Chui and Tera Allas and Peter Dahlstrom and Nicolaus Henke and Monica Trench} } @proceedings {2017, title = {Chatbots as assistants, an architectural framework}, year = {2017}, url = {https://dl.acm.org/citation.cfm?id=3172805}, author = {Adam Di Prospera and Nojan norouzi and Morios Fokaefs and Marin Litoiu} } @article {2017, title = {Computer technology and probable job destructions in Japan: An evaluation}, journal = {Journal of the Japanese and International Economies}, volume = {43}, year = {2017}, month = {Jan-03-2017}, pages = {77 - 87}, issn = {08891583}, doi = {10.1016/j.jjie.2017.01.001}, author = {David, Benjamin} } @article {2017, title = {Deep learning for healthcare: review, opportunities and challenges}, journal = {Briefings in Bioinformatics}, volume = {19}, year = {2017}, month = {Jun-05-2017}, pages = {1236 - 1246}, issn = {1467-5463}, doi = {10.1093/bib/bbx044}, author = {Miotto, Riccardo and Wang, Fei and Wang, Shuang and Jiang, Xiaoqian and Joel T. Dudley} } @article {2017, title = {A future that works: Automation, employment and productivity}, year = {2017}, url = {https://www.mckinsey.com/mgi/overview}, author = {James Manyika and Michael Chui and Mehdi Miremadi and Jaccques Bughin and Katy George and Paul Willmott and Martin Dewhurst} } @article {2017, title = { How automation is changing auditing}, journal = {Journal of Emerging Technologies in Accounting}, volume = {14}, year = {2017}, month = {Jan-03-2017}, pages = {115 - 122}, issn = {1554-1908}, doi = {10.2308/jeta-51730}, author = {Kokina, Julia and Davenport, Thomas H.} } @book {2017, title = {Information Technology and the U.S. Workforce}, year = {2017}, publisher = {National Academies Press}, organization = {National Academies Press}, address = {Washington, D.C.}, isbn = {978-0-309-45402-5}, doi = {10.17226/24649}, url = {https://www.nap.edu/catalog/24649} } @conference {Malone:2017:PPB:2998181.2998343, title = {Putting the Pieces Back Together Again: Contest Webs for Large-Scale Problem Solving}, booktitle = {Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing}, year = {2017}, pages = {1661{\textendash}1674}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {climate change, collective intelligence, contest webs, contests, Coordination, incentives, knowledge reuse}, isbn = {978-1-4503-4335-0}, doi = {10.1145/2998181.2998343}, url = {http://doi.acm.org/10.1145/2998181.2998343}, author = {Malone, Thomas W. and Jeffrey V Nickerson and Laubacher, Robert J. and Fisher, Laur Hesse and de Boer, Patrick and Han, Yue and Towne, W. Ben} } @book {2017, title = {Refining the concept of scientific inference when working with big data}, year = {2017}, publisher = {National Academies Press}, organization = {National Academies Press}, address = {Washington, D.C.}, isbn = {978-0-309-45444-5}, doi = {10.17226/24654}, editor = {Wender, Ben A.} } @article {2017, title = {Service Robotics and Human Labor: A first technology assessment of substitution and cooperation}, journal = {Robotics and Autonomous Systems}, volume = {87}, year = {2017}, month = {Jan-01-2017}, pages = {348 - 354}, issn = {09218890}, doi = {10.1016/j.robot.2016.09.017}, author = {Decker, Michael and Fischer, Martin and Ott, Ingrid} } @conference {2017, title = {SPIE ProceedingsBuilding a framework to manage trust in automation}, booktitle = {SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications IX}, volume = {10194}, year = {2017}, pages = {101941U}, publisher = {SPIE}, organization = {SPIE}, address = {Anaheim, California, United States}, doi = {10.1117/12.2264245}, author = {Metcalfe, J. S. and Amar R. Marathe and Haynes, B. and Paul, V. J. and Gremillion, G. M. and Drnec, K. and Atwater, C. and Estepp, J. R. and Lukos, J. R. and Carter, E. C. and W. D. Nothwang}, editor = {George, Thomas and Dutta, Achyut K. and Islam, M. Saif} } @article {2017, title = {Will Life Be Worth Living in a World Without Work? Technological Unemployment and the Meaning of Life}, journal = {Science and Engineering Ethics}, volume = {23}, year = {2017}, publisher = {Springer}, chapter = {41-64}, abstract = {Suppose we are about to enter an era of increasing technological unemployment. What implications does this have for society? Two distinct ethical/social issues would seem to arise. The first is one of distributive justice: how will the (presumed) efficiency gains from automated labour be distributed through society? The second is one of personal fulfillment and meaning: if people no longer have to work, what will they do with their lives? In this article, I set aside the first issue and focus on the second. In doing so, I make three arguments. First I argue that there are good reasons to embrace non-work and that these reasons become more compelling in an era of technological unemployment. Second, I argue that the technological advances that make widespread technological unemployment possible could still threaten or undermine human flourishing and meaning, especially if (as is to be expected) they do not remain confined to the economic sphere. And third, I argue that this threat could be contained if we adopt an integrative approach to our relationship with technology. In advancing these arguments, I draw on three distinct literatures: (1) the literature on technological unemployment and workplace automation; (2) the antiwork critique - which I argue gives reasons to embrace technological unemployment; and (3) the philosophical debate about the conditions for meaning in life - which I argue gives reasons for concern.}, keywords = {Antiwork, automation, Egalitarianism, Freedom, Meaning of life, Technological unemployment, Transhumanism}, doi = {10.1007s/11948-016-9770-5}, author = {John Danaher} } @article {2017, title = {Will Life Be Worth Living in a World Without Work? Technological Unemployment and the Meaning of Life}, journal = {Science and Engineering Ethics}, volume = {23}, year = {2017}, month = {Jan-02-2017}, pages = {41 - 64}, issn = {1353-3452}, doi = {10.1007/s11948-016-9770-5}, author = {Danaher, John} } @article {2016, title = {Citizen science on a smartphone: Participants{\textquoteright} motivations and learning}, journal = {Public Understanding of Science}, volume = {25}, year = {2016}, month = {Mar-01-2017}, pages = {45 - 60}, issn = {0963-6625}, doi = {10.1177/0963662515602406}, author = {Land-Zandstra, Anne M. and Devilee, Jeroen L. A. and Snik, Frans and Buurmeijer, Franka and van den Broek, Jos M.} } @conference {2016, title = {Degree of Automation in Command and Control Decision Support Systems}, booktitle = {IEEE International Conference on Systems, Man and Cybernetics}, year = {2016}, url = {https://ieeexplore.ieee.org/document/7844402}, author = {Ryan M. Robinson and Michael J. McCount and Amar R. Marathe and W. D. Nothwang and Emily A. Doucette} } @mastersthesis {2016, title = {Exploring design principles for human-machine symbiosis: Insights from constructing an air transportation logistics artifact}, year = {2016}, keywords = {air transportation logistics, design science research, heuristic theorizing, huma n - machine symbiosis}, url = {https://www.semanticscholar.org/paper/Artificial-Intelligence-and-its-Role-in-Near-Future-Shabbir-Anwer/b93d9995f9ce3b15f4c4855ae62f0bf6f9bc041f}, author = {Daniel A. D{\"o}ppner and Detlef Schoder and Robert Wayne Gregory and Honorata Siejka} } @article {2016, title = {The Future of Artificial Intelligence}, journal = {Big Data}, volume = {4}, year = {2016}, month = {Jan-03-2016}, pages = {5 - 9}, issn = {2167-6461}, doi = {10.1089/big.2016.29004.vda}, author = {Dhar, Vasant} } @article {2016, title = {IT drinking its own automation champagne}, journal = {Data Informed }, year = {2016}, month = {11/2016}, url = {https://www.linkedin.com/pulse/drinking-its-own-automation-champagne-tom-davenport/}, author = {Thomas H. Davenport} } @article {2016, title = {The return of the chatbots}, journal = {Natural Language Engineering}, volume = {22}, year = {2016}, month = {Jan-09-2016}, pages = {811 - 817}, issn = {1351-3249}, doi = {10.1017/S1351324916000243}, url = {https://www.cambridge.org/core/product/identifier/S1351324916000243/type/journal_articlehttps://www.cambridge.org/core/services/aop-cambridge-core/content/view/S1351324916000243}, author = {Robert Dale} } @article {2016, title = {The rise of social bots}, journal = {Communications of the ACM}, volume = {59}, year = {2016}, month = {Dec-06-2017}, pages = {96 - 104}, issn = {00010782}, doi = {10.1145/2818717}, author = {Ferrara, Emilio and Varol, Onur and Davis, Clayton and Menczer, Filippo and Flammini, Alessandro} } @article {2016, title = {Robots and humans {\textendash} complements or substitutes?}, journal = {Journal of Macroeconomics}, volume = {49}, year = {2016}, month = {Jan-09-2016}, pages = {280 - 291}, issn = {01640704}, doi = {10.1016/j.jmacro.2016.08.003}, author = {DeCanio, Stephen J.} } @conference {2016, title = {SPIE ProceedingsAn efficient fusion approach for combining human and machine decisions}, booktitle = {SPIE Defense + SecurityMicro- and Nanotechnology Sensors, Systems, and Applications VIII}, volume = {9836}, year = {2016}, pages = {983621}, publisher = {SPIE}, organization = {SPIE}, address = {Baltimore, Maryland, United States}, doi = {10.1117/12.2220788}, url = {http://proceedings.spiedigitallibrary.org/proceeding.aspx?doi=10.1117/12.2220788}, author = {Lee, Hyungtae and Kwon, Heesung and Ryan M. Robinson and W. D. Nothwang and Amar R. Marathe}, editor = {George, Thomas and Dutta, Achyut K. and Islam, M. Saif} } @article {2015, title = {Artificial intelligence for the real world: Don{\textquoteright}t start with moon shots}, year = {2015}, keywords = {consulting reports}, url = {https://hbr.org/2018/01/artificial-intelligence-for-the-real-world}, author = {Thomas H. Davenport and Rajeev Ronanki} } @booklet {RN30629, title = {The growing importance of social skills in the labor market}, year = {2015}, publisher = {National Bureau of Economic Research}, type = {Report}, author = {Deming, David J} } @article {2015, title = {Hybrid human{\textendash}machine information systems: Challenges and opportunities}, journal = {Computer Networks}, volume = {90}, year = {2015}, month = {Jan-10-2015}, pages = {5 - 13}, issn = {13891286}, doi = {10.1016/j.comnet.2015.05.018}, author = {Demartini, Gianluca} } @book {2015, title = {Mining programming activity to promote help}, year = {2015}, pages = {23 - 42}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-20498-7}, doi = {10.1007/978-3-319-20499-4_2}, author = {Carter, Jason and Dewan, Prasun}, editor = {Boulus-R{\o}dje, Nina and Ellingsen, Gunnar and Bratteteig, Tone and Aanestad, Margunn and Bj{\o}rn, Pernille} } @article {2015, title = {Research Priorities for Robust and Beneficial Artificial Intelligence}, journal = {Association for the Advancement of Artificial Intelligence}, volume = {4}, year = {2015}, pages = {105-114}, abstract = {

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

}, url = {https://futureoflife.org/data/documents/research_priorities.pdf}, author = {Stuart Russell and Daniel Dewey and Max Tegmark} } @article {2012, title = {A few useful things to know about machine learning}, journal = {Communications of the ACM}, volume = {55}, year = {2012}, month = {Jan-10-2012}, pages = {78}, issn = {00010782}, doi = {:10.1145/2347736.2347755}, author = {Domingos, Pedro} } @article {2010, title = {Understanding the role of occupational and organizational context}, journal = {Journal of Organizational Behavior}, volume = {31}, year = {2010}, month = {Jan-02-2010}, pages = {351 - 360}, issn = {08943796}, doi = {10.1002/job.642}, author = {Morgeson, Frederick P. and Dierdorff, Erich C. and Hmurovic, Jillian L.}, editor = {Grant, Adam and Fried, Yitzhak and Parker, Sharon and Frese, Michael} } @article {2003, title = {A Preliminary Analysis of Occupational Task Statements from the O*NET Data Collection Program}, year = {2003}, institution = {National Center for O*NET Development}, isbn = {FR-02-52}, author = {Van Iddekinge, Chad and Suzanne Tsacoumis and Jamie Donsbach} }