Papers

Export 10 results:
Filters: First Letter Of Title is M  [Clear All Filters]
2019
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
Kühl, N., Goutier, M., Hirt, R., & Satzger, G.. (2019). Machine learning in Artificial Intelligence: Towards a common understanding (T. Bui, Tran.). In Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences. Presented at the Hawaii International Conference on System SciencesProceedings of the 52nd Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2019.630
van Esch, P., J. Black, S., & Ferolie, J.. (2019). Marketing AI recruitment: The next phase in job application and selection. Computers In Human Behavior, 90, 215 - 222. https://doi.org/10.1016/j.chb.2018.09.009
Chomanski, B. (2019). Massive technological unemployment without redistribution: A case for cautious optimism. Science And Engineering Ethics, 25(5), 1389 - 1407. https://doi.org/10.1007/s11948-018-0070-0
Li, J. (Justin), Bonn, M. A., & Ye, B. Haobin. (2019). The moderating roles of perceived organizational support and competitive psychological climate. Tourism Management, 73, 172 - 181. https://doi.org/10.1016/j.tourman.2019.02.006
2018
Helbing, D. (2018). Machine intelligence: Blessing or curse? It depends on us! (pp. 25 - 39; D. Helbing, Ed.). In (pp. 25 - 39). https://doi.org/10.1007/978-3-319-90869-4_4
Humphries, G., & Huettmann, F.. (2018). Machine Learning in Wildlife Biology: Algorithms, Data Issues and Availability, Workflows, Citizen Science, Code Sharing, Metadata and a Brief Historical Perspective. In G. Humphries, Magness, D. R., & Huettmann, F. (Eds.), Machine Learning for Ecology and Sustainable Natural Resource Management (pp. 3 - 26). https://doi.org/10.1007/978-3-319-96978-7_1
Stilgoe, J. (2018). Machine learning, social learning and the governance of self-driving cars. Social Studies Of Science, 48, 25-56. https://doi.org/10.1177/0306312717741687
Seeber, I., Bittner, E., Briggs, R. O., de Vreede, G. - J., de Vreede, T., Druckenmiller, D., et al.. (2018). Machines as Teammates: A Collaboration Research Agenda. In Hawaii International Conference on System Sciences. Presented at the Hawaii International Conference on System Sciences. https://doi.org/10.24251/HICSS.2018.055
PDF icon SeeberEtAl_2018_MachinesAsTeammates.pdf (949.98 KB)
Winn, A. N., & Neuner, J. M.. (2018). Making Sure We Don’t Forget the Basics When Using Machine Learning. Jnci: Journal Of The National Cancer Institute, 111(6), 529 - 530. https://doi.org/10.1093/jnci/djy179
Haryadi, H., Anggraeni, A. Irma, & Ibrahim, D. Nasir. (2018). Managing talented worker in the era of new psychological contract. Jurnal Aplikasi Manajemen, 16(1), 20 - 26. https://doi.org/10.21776/ub.jam.2018.016.01.03
Loh, E. (2018). Medicine and the rise of the robots: a qualitative review of recent advances of artificial intelligence in health. Bmj Leader, 2(2), 59 - 63. https://doi.org/10.1136/leader-2018-000071

Pages