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Musib, M., Wang, F., Tarselli, M. A., Yoho, R., Yu, K. - H., Andrés, R. Medina, et al.. (2017). Artificial intelligence in research. Science, 357(6346), 28 - 30.
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
Mumford, E. (2006). The story of socio‐technical design: Reflections on its successes, failures and potential. Information Systems Journalinformation Systems Journal, 16, 317-342.
Mukhalipi, A. (2018). Human capital management and future of work; job creation and unemployment: a literature review. Oalib, 05(09), 1 - 17.
Mou, Y., & Xu, K.. (2017). Comparing the initial human-human and human-AI social interactions. Computers In Human Behavior, 72, 432 - 440.
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.
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.
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.
Moody, K. (2018). High tech, low growth: Robots and the future of work abstract. Historical Materialism, 26(4), 3 - 34.
Moniz, A., & Krings, B. - J.. (2016). Robots working with humans or humans working with robots?. Societies, 6(3), 23.
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.
Mohr, J. W., Wagner-Pacifici, R., & Breiger, R. L.. (2015). Toward a computational hermeneutics. Big Data & Society, 2(2), 205395171561380.
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.
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).
Mishel, L., & Bivens, J.. (2017). The zombie robot argument lurches on. Economy Policy Institute. Retrieved de
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.
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.
N. Meyer, D. (1982). Office automation: A progress report. Office Technology And People, 1(1), 107 - 121.
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).