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Dyuti Pandya European Centre for International Political Economy
Devesh Narayanan Stanford University
Bas Becker Vrije Universiteit Amsterdam
Luciana Dadderio Edinburgh University
Jocelyn Cranefield Victoria University of Wellington

Recent publications

Taming artificial intelligence: A theory of control–accountability alignment among AI developers and users , Gudela Grote; Sharon Parker; Kevin Crowston
Supporting and augmenting human and machine learning in citizen science: Lessons from Gravity Spy , Carsten Østerlund; Kevin Crowston; Corey B. Jackson; Yunan Wu; Alexander O. Smith; Aggelos K. Katsaggelos
Deskilling and upskilling with generative AI systems , Kevin Crowston; Francesco Bolici
The task matters: The effect of perceived similarity to AI on intention to use in different task types , Qingyu Liang; Kevin Crowston; Sangseok You
ReelFramer: Human-AI Co-Creation for News-to-Video Translation , Sitong Wang; Samia Menon; Tao Long; Keren Henderson; Dingzeyu Li; Kevin Crowston; Mark Hansen; Jeffrey V. Nickerson; Lydia B. Chilton

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Liang, H. - F., Wu, K. - M., Weng, C. - H., & Hsieh, H. - W.. (2019). Nurses' Views on the Potential Use of Robots in the Pediatric Unit. Journal Of Pediatric Nursing, 47, e58 - e64. https://doi.org/10.1016/j.pedn.2019.04.027

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Ikudo, A., Lane, J., Staudt, J., & Weinberg, B. A.. (2018). Occupational Classifications With A Machine Learning Approach. In IZA DP No. 11738. Retrieved de https://www.iza.org/publications/dp/11738/occupational-classifications-a-machine-learning-approach

Nelson, A. J., & Irwin, J.. (2014). Occupational identity, technological change, and the librarian/internet-search relationship. Academy Of Management Journal, 57(3), 892 - 928. https://doi.org/10.5465/amj.2012.0201

Miller, F. A., Katz, J. H., & Gans, R.. (2018). The OD imperative to add inclusion to the algorithms of artificial intelligence. Researchgate. Retrieved de https://www.researchgate.net/publication/323830092_AI_x_I_AI2_The_OD_imperative_to_add_inclusion_to_the_algorithms_of_artificial_intelligence

Phan, P., Wright, M., & Lee, S. - H.. (2017). Of robots, Artificial Intelligence, and work. Academy Of Management Perspectives, 31(4), 253 - 255. https://doi.org/10.5465/amp.2017.0199

N. Meyer, D. (1982). Office automation: A progress report. Office Technology And People, 1(1), 107 - 121. https://doi.org/10.1108/eb022608

Parker, S. K., Morgeson, F. P., & Johns, G.. (2017). One hundred years of work design research: Looking back and looking forward. Journal Of Applied Psychology, 102(3), 403 - 420. https://doi.org/10.1037/apl0000106

Anagnoste, S. (2018). The operating system for the digital enterprise. Proceedings Of The International Conference On Business Excellence, 12(1), 54 - 69. https://doi.org/10.2478/picbe-2018-0007

An overview of autonomous vehicles safety. (2018). An overview of autonomous vehicles safety. In IEEE. Retrieved de https://ieeexplore.ieee.org/document/8353618

Freeman, R. B. (2018). Ownership when AI robots do more of the work and earn more of the income. Journal Of Participation And Employee Ownership, 1(1), 74 - 95. https://doi.org/10.1108/JPEO-04-2018-0015

Van den Broeck, A., Parker, S. K., Van den Broeck, A., & Parker, S. K.. (2017). Oxford research encyclopedia of psychology. https://doi.org/10.1093/acrefore/9780190236557.013.15

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Anani, N. (2018). Paving the way for the future of work. Canadian Public Policy, 1 - 10. https://doi.org/10.3138/cpp.2018-012

Sarwar, S., Dent, A., Faust, K., Richer, M., Djuric, U., Van Ommeren, R., & Diamandis, P.. (2019). Physician perspectives on integration of artificial intelligence into diagnostic pathology. Npj Digital Medicine, 2(1). https://doi.org/10.1038/s41746-019-0106-0

Ajunwa, I., & Greene, D.. (2018). Platforms at work: Automated hiring platforms and other new intermediaries in the organization of work. Retrieved de http://dmgreene.net/wp-content/uploads/2018/09/Ajunwa-Greene-Platforms-at-Work-Accepted-Version.pdf

Metcalf, L., Askay, D. A., & Rosenberg, L. B.. (2019). Pooling knowledge through artificial swarm intelligence to improve business decision making. California Management Review, 61(4), 84 - 109. https://doi.org/10.1177/0008125619862256

Davenport, T., & Kalakota, R.. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94 - 98. https://doi.org/10.7861/futurehosp.6-2-94

Pugh, A. J. (2019). Precarious lives: Job insecurity and well-being in rich democracies. Social Forces, 97(4), e1 - e3. https://doi.org/10.1093/sf/soz022

Sampson, S. (2020). Predicting Automation of Professional Jobs in Healthcare. In Proceedings of the 53rd Hawaii International Conference on System Sciences (3, 3529–3537). https://doi.org/10.24251/hicss.2020.433

Obermeyer, Z., & Emanuel, E. J.. (2016). Predicting the Future — Big Data, Machine Learning, and Clinical Medicine. New England Journal Of Medicine, 375(13), 1216 - 1219. https://doi.org/10.1056/NEJMp1606181

Wu, J., Ray, J., & Stewart, W. F.. (2010). Prediction modeling using EHR data: Challenges, strategies, and a comparison of machine learning approaches. Medical Care, 48. Retrieved de https://www.jstor.org/stable/20720782

Rotila, V. (2018). The predictions on the future of labour are not grounded; some arguments for a bayesian approach. Postmodern Openings, 9(3), 36 - 63. https://doi.org/10.18662/po/35

Van Iddekinge, C., Tsacoumis, S., & Donsbach, J.. (2003). A Preliminary Analysis of Occupational Task Statements from the O*NET Data Collection Program. National Center for O*NET Development.

Executive Office of the President National Science and Technology Council Committee on Technology, Preparing for the future of Artificial intelligence. (2016). Preparing for the future of Artificial intelligence. Retrieved de https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.pdf

Saba, L., Biswas, M., Kuppili, V., Godia, E. Cuadrado, Suri, H. S., Edla, D. Reddy, et al.. (2019). The present and future of deep learning in radiology. European Journal Of Radiology, 114, 14 - 24. https://doi.org/10.1016/j.ejrad.2019.02.038

Raj, M., & Seamans, R.. (2019). Primer on artificial intelligence and robotics. Journal Of Organization Design, 8(1). https://doi.org/10.1186/s41469-019-0050-0

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