Papers

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Journal Article
Goos, M. (2018). The impact of technological progress on labour markets: policy challenges. Oxford Review Of Economic Policy, 34(3), 362 - 375. https://doi.org/10.1093/oxrep/gry002
Arogyaswamy, B., & Hunter, J.. (2018). The impact of technology and globalization on employment and equity. International Journal Of Global Sustainability, 3(1), 49. https://doi.org/10.5296/ijgs.v3i1.14127
Acemoglu, D., & Restrepo, P.. (2018). Implications of technology for growth, factor shares, and employment. American Economic Review, 108(6), 1488 - 1542. https://doi.org/10.1257/aer.20160696
Avati, A., Jung, K., Harman, S., Downing, L., Ng, A., & Shah, N. H.. (2018). Improving palliative care with deep learning. Bmc Medical Informatics And Decision Making, 18(S4). https://doi.org/10.1186/s12911-018-0677-8
Jarrahi, M. Hossein. (2019). In the age of the smart artificial intelligence: AI’s dual capacities for automating and informating work. Business Information Review, 026638211988399. https://doi.org/10.1177/0266382119883999
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J. Heberling, M., & Isaac, B. L.. (2018). iNaturalist as a tool to expand the research value of museum specimens. Applications In Plant Sciences, 6(11), e01193. https://doi.org/10.1002/aps3.1193
Mehic, A. (2018). Industrial employment and income inequality: Evidence from panel data. Structural Change And Economic Dynamics, 45, 84 - 93. https://doi.org/10.1016/j.strueco.2018.02.006
Jung, J. Hwa, & Lim, D. Geon. (2020). Industrial robots, employment growth, and labor cost: A simultaneous equation analysis. Technological Forecasting And Social Change, 159, 120202. https://doi.org/10.1016/j.techfore.2020.120202
Araujo, T. (2018). The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Computers In Human Behavior, 85, 183 - 189. https://doi.org/10.1016/j.chb.2018.03.051
Choi, D. Y., & Kang, J. Hyeung. (2019). Introduction: The Future of Jobs in an Increasingly Autonomous Economy. Journal Of Management Inquiry, 28(3), 298 - 299. https://doi.org/10.1177/1056492619827373
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.
Oldham, G. R., & Fried, Y.. (2016). Job design research and theory: Past, present and future. Organizational Behavior And Human Decision Processes, 136, 20 - 35. https://doi.org/10.1016/j.obhdp.2016.05.002
Cirillo, V., & Zayas, J. Molero. (2019). Labor, technology and work organization: An introduction to the forum. Journal Of Industrial And Business Economics, 46(3), 313 - 321. https://doi.org/10.1007/s40812-019-00126-w
Gill, K. S. (2018). Looking though the Pygmalion Lens. Ai & Society, 33(4), 459 - 465. https://doi.org/10.1007/s00146-018-0866-0
Pereira, L. Moniz. (2019). A machine is cheaper than a human for the same task. Ai & Society. https://doi.org/10.1007/s00146-018-0874-0
Johnson, A. E. W., Ghassemi, M. M., Nemati, S., Niehaus, K. E., Clifton, D., & Clifford, G. D.. (2016). Machine learning and decision support in critical care. Proceedings Of The Ieee, 104(2), 444 - 466. https://doi.org/10.1109/JPROC.2015.2501978
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

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