Papers

Export 9 results:
2019
Winter, J. Sunrise, & Davidson, E.. (2019). Governance of artificial intelligence and personal health information. Digital Policy, Regulation And Governance, 21(3), 280 - 290. https://doi.org/10.1108/DPRG-08-2018-0048
Sudlow, B. (2019). Higher education in the age of Artificial Intelligence. Postdigital Science And Education, 1(1), 236 - 239. https://doi.org/10.1007/s42438-018-0005-8
Agrawal, A., Gans, J., & Goldfarb, A.. (2019). How artificial intelligence and machine learning can impact market design (pp. 567 - 586). In (pp. 567 - 586). https://doi.org/10.7208/chicago/9780226613475.003.0023
Mcmahon, M., Mumper, D., Ihaza, M., & Farrar, D.. (2019). How Smart is your Manufacturing? Build Smarter with AI. In 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC)2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC) (55 - 60). https://doi.org/10.1109/COMPSAC.2019.10183
Tursunbayeva, A. (2019). Human resource technology disruptions and their implications for human resources management in healthcare organizations. Bmc Health Services Research, 19(1). https://doi.org/10.1186/s12913-019-4068-3
Dellermann, D., Ebel, P., Söllner, M., & Leimeister, J. Marco. (2019). Hybrid Intelligence. Business & Information Systems Engineering, 61(5), 637 - 643. https://doi.org/10.1007/s12599-019-00595-2
Reis, J., Santo, P. Espírito, Lisbon, P., & Melão, N.. (2019). Impacts of Artificial Intelligence on Public Administration: A Systematic Literature Review. In 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). Presented at the 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). Retrieved de https://ieeexplore.ieee.org/document/8760778
Crowston, K., & Bolici, F.. (2019). Impacts of machine learning on work. In Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52). Retrieved de http://hdl.handle.net/10125/60031
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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
PDF icon In the Age of the Smart Artificial Intelligence AI’s Dual Capacities for Automating and Informating.pdf (317.68 KB)
Duckworth, P., Graham, L., & Osborne, M.. (2019). Inferring work task automatability from AI expert evidence (V. Conitzer, Hadfield, G., & Vallor, S., Trans.). In the 2019 AAAI/ACM ConferenceProceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society - AIES '19 (485 - 491). https://doi.org/10.1145/330661810.1145/3306618.3314247
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
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
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
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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