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Papers

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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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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
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
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
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
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
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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