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Dahya, R., & Morris, A.. (2019). Toward a conceptual framework for understanding AI action and legal reaction (Vol. 11489, pp. 453 - 459; M. - J. Meurs & Rudzicz, F., Eds.). In (Vol. 11489, pp. 453 - 459). https://doi.org/10.1007/978-3-030-18305-9_44
N. Meyer, D. (1982). Office automation: A progress report. Office Technology And People, 1(1), 107 - 121. https://doi.org/10.1108/eb022608
Mikhaylov, S. Jankin, Esteve, M., & Campion, A.. (2018). Artificial intelligence for the public sector: opportunities and challenges of cross-sector collaboration. Philosophical Transactions Of The Royal Society A: Mathematical, Physical And Engineering Sciences, 376(2128), 20170357. https://doi.org/10.1098/rsta.2017.0357
Miotto, R., Wang, F., Wang, S., Jiang, X., & Dudley, J. T.. (2017). Deep learning for healthcare: review, opportunities and challenges. Briefings In Bioinformatics, 19(6), 1236 - 1246. https://doi.org/10.1093/bib/bbx044
Mishel, L., & Bivens, J.. (2017). The zombie robot argument lurches on. Economy Policy Institute. Retrieved de http://epi.org/126750
Mlynar, J., Alavi, H. S., Verma, H., & Cantoni, L.. (2018). Towards a Sociological Conception of Artificial Intelligence. In Artificial General Intelligence (AGI). Presented at the Artificial General Intelligence (AGI). https://doi.org/10.1007/978-3-319-97676-1_13
Moffitt, K. C., Rozario, A. M., & Vasarhelyi, M. A.. (2018). Robotic Process Automation for Auditing. Journal Of Emerging Technologies In Accounting, 15(1), 1 - 10. https://doi.org/10.2308/jeta-10589
Mohr, J. W., Wagner-Pacifici, R., & Breiger, R. L.. (2015). Toward a computational hermeneutics. Big Data & Society, 2(2), 205395171561380. https://doi.org/10.1177/2053951715613809
Mokyr, J., Vickers, C., & Ziebarth, N. L.. (2015). The history of technological anxiety and the future of economic growth: Is this time different?. Journal Of Economic Perspectives, 29(3), 31 - 50. https://doi.org/10.1257/jep.29.3.31
Moniz, A., & Krings, B. - J.. (2016). Robots working with humans or humans working with robots?. Societies, 6(3), 23. https://doi.org/10.3390/soc6030023
Moody, K. (2018). High tech, low growth: Robots and the future of work abstract. Historical Materialism, 26(4), 3 - 34. https://doi.org/10.1163/1569206X-00001745
Moore, M. M., Slonimsky, E., Long, A. D., Sze, R. W., & Iyer, R. S.. (2019). Machine learning concepts, concerns and opportunities for a pediatric radiologist. Pediatric Radiology, 49(4), 509 - 516. https://doi.org/10.1007/s00247-018-4277-7
Morgeson, F. P., & Humphrey, S. E.. (2008). Job and team design: Toward a more integrative conceptualization of work design. Research In Personnel And Human Resources Managementresearch In Personnel And Human Resources Management, 27, 39–91.
Morgeson, F. P., & Campion, M. A.. (2003). Work design. In W. Borman, Ilgen, D., & Klimoski, R. (Eds.), Handbook of Psychology: Industrial and Organizational Psychology (pp. 423–452). Hoboken, NY: Wiley.
Morgeson, F. P., & Humphrey, S. E.. (2006). The Work Design Questionnaire (WDQ): Developing and validating a comprehensive measure for assessing job design and the nature of work. Journal Of Applied Psychology, 91(6), 1321 - 1339. https://doi.org/10.1037/0021-9010.91.6.1321
Mou, Y., & Xu, K.. (2017). Comparing the initial human-human and human-AI social interactions. Computers In Human Behavior, 72, 432 - 440. https://doi.org/10.1016/j.chb.2017.02.067
Mukhalipi, A. (2018). Human capital management and future of work; job creation and unemployment: a literature review. Oalib, 05(09), 1 - 17. https://doi.org/10.4236/oalib.1104859
Mumford, E. (2006). The story of socio‐technical design: Reflections on its successes, failures and potential. Information Systems Journalinformation Systems Journal, 16, 317-342.
Murphy, R. R., & Schreckenghost, D.. (2013). Survey of metrics for human-robot interaction. In IEEE International Conference. Presented at the IEEE International Conference. Retrieved de https://ieeexplore.ieee.org/document/6483569

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