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Cui, Y. (2020). Artificial Intelligence and Judicial Modernization.
Cruz-Roa, A., Gilmore, H., Basavanhally, A., Feldman, M., Ganesan, S., Shih, N. N. C., et al.. (2017). A deep learning approach for quantifying tumor extent. Scientific Reports, 7(1).
Crowston, K. (2020). Lessons for Supporting Data Science from the Everyday Automation Experience of Spell-Checkers. In Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual. Presented at the Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual, Virtual workshop.
PDF icon Everyday_automation camera ready.pdf (421.84 KB)
Crowston, K., Østerlund, C., & Lee, T. Kyoung. (2017). Blending machine and human learning processes. In Hawai'i International Conference on System Sciences.
PDF icon training v3 to share.pdf (245.57 KB)
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).
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Crowston, K., & Bolici, F.. (2020). Impacts of the Use of Machine Learning on Work Design. In 8th International Conference on Human-Agent Interaction.
PDF icon Impacts_of_ML_for_HAI_2020.pdf (453.59 KB)
Crone, T., & Zargar, M. Shafeie. (2018). How the anthropormorphization of virtual assistants influences user's trust. Academy Of Management Proceedings, 2018(1), 16328.
Croghan, S. M., Carroll, P., Reade, S., Gillis, A. E., & Ridgway, P. F.. (2018). Robot Assisted Surgical Ward Rounds: Virtually Always There. Journal Of Innovation In Health Informatics, 25(1), 041.
Crews, A. (2015). The big move toward big data in employment. In Employment& Labor Law Solutions Worldwide. Retrieved de
Nathan, L. F. (2018). Creativity, the arts, and the future of work (pp. 283 - 310; J. W. Cook, Ed.). In (pp. 283 - 310).
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).
Data Science for Undergraduates. (2018). Data Science for Undergraduates.
Colbert, A., Yee, N., & George, G.. (2016). The digital workforce and the workplace of the future. Academy Of Management Journal, 59(3), 731 - 739.
Coelho, H. (2018). Reflections on the meaning of automated education. Education Policy Analysis Archives, 26, 115.
Cockshott, P., & Renaud, K.. (2016). Humans, robots and values. Technology In Society, 45, 19 - 28.
Clifton, J., Clifton, J., Glasmeier, A., & Gray, M.. (2020). When machines think for us: The consequences for work and place. Cambridge Journal Of Regions, Economy And Society, 13, 3–23.
Clément, M., & Guitton, M. J.. (2015). Users’ reactions to actions of automated programs in Wikipedia. Computers In Human Behavior, 50, 66 - 75.