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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., & 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.
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.
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).