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Papers

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2020
Jha, S. (2020). Automation and Radiology—Part 1. In Academic Radiology (pp. 147–149). https://doi.org/10.1016/j.acra.2019.10.026
Johnson, R. D., Stone, D. L., & Lukaszewski, K. M.. (2020). The benefits of eHRM and AI for talent acquisition. Journal Of Tourism Futures. https://doi.org/10.1108/JTF-02-2020-0013
Roccetti, M., Delnevo, G., Casini, L., & Salomoni, P.. (2020). A Cautionary Tale for Machine Learning Design: why we Still Need Human-Assisted Big Data Analysis. Mobile Networks And Applications, 25, 1075–1083. https://doi.org/10.1007/s11036-020-01530-6
Kassens-Noor, E., & Hintze, A.. (2020). Cities of the Future? The Potential Impact of Artificial Intelligence. Ai, 1, 192–197. https://doi.org/10.3390/ai1020012
Acemoglu, D., Lelarge, C., & Restrepo, P.. (2020). Competing with Robots: Firm-Level Evidence from France. Aea Papers And Proceedings, 110, 383–388. https://doi.org/10.1257/pandp.20201003
Gerber, A., Derckx, P., Döppner, D. A., & Schoder, D.. (2020). Conceptualization of the Human-Machine Symbiosis – A Literature Review. In Proceedings of the 53rd Hawaii International Conference on System Sciences (3, 289–298). https://doi.org/10.24251/hicss.2020.036
Završnik, A.. (2020). Criminal justice, artificial intelligence systems, and human rights. Era Forum, 20, 567–583. https://doi.org/10.1007/s12027-020-00602-0
Mart'nez-Plumed, F., Tolan, S. 'l, Pesole, A., Hern'ndez-Orallo, J., Fern'ndez-Mac'as, E., & G'mez, E.. (2020). Does AI qualify for the job? A bidirectional model mapping labour and AI intensities. In AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (94–100). https://doi.org/10.1145/3375627.3375831
Huang, M. Hui, & Rust, R. T.. (2020). Engaged to a Robot? The Role of AI in Service. Journal Of Service Research. https://doi.org/10.1177/1094670520902266
de Ágreda, Á. Gómez. (2020). Ethics of autonomous weapons systems and its applicability to any AI systems. Telecommunications Policy, 5, 101953. https://doi.org/10.1016/j.telpol.2020.101953
Hacker, P., Krestel, R., Grundmann, S., & Naumann, F.. (2020). Explainable AI under contract and tort law: legal incentives and technical challenges. Artificial Intelligence And Law. https://doi.org/10.1007/s10506-020-09260-6
Dalgali, A., & Crowston, K.. (2020). Factors Influencing Approval of Wikipedia Bots. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.018
PDF icon HICSS_WikipediaPaper_3.9.new kc (2).pdf (473.63 KB)
Reid-musson, E., Cockayne, D., Frederiksen, L., & Worth, N.. (2020). Feminist economic geography and the future of work. Epa: Economy And Space, 1–12. https://doi.org/10.1177/0308518X20947101
Suran, S., Pattanaik, V., & Draheim, D.. (2020). Frameworks for collective intelligence: A systematic literature review. In ACM Computing Surveys (pp. 1–36). https://doi.org/10.1145/3368986
Abeliansky, A. L., Algur, E., Bloom, D. E., & Prettner, K.. (2020). The Future of Work: Meeting the Global Challenge of Demographic Change and Automation. International Labour Review, 1–28. https://doi.org/10.1111/ilr.12168
Harandi, M., Crowston, K., Jackson, C., & Østerlund, C.. (2020). The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning. In Hawai'i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.719
PDF icon Social_Construction_of_ML_in_GS_HICCS2020.pdf (124.3 KB)
H. Harvey, B., & Gowda, V.. (2020). How the FDA regulates AI. Academic Radiology, 27(1), 58 - 61. https://doi.org/10.1016/j.acra.2019.09.017
Bærøe, K., Miyata-Sturm, A., & Henden, E.. (2020). How to achieve trustworthy artificial intelligence for health. Bulletin Of The World Health Organization, 98, 257–262. https://doi.org/10.2471/BLT.19.237289
Delfanti, A., & Frey, B.. (2020). Humanly Extended Automation or the Future of Work Seen through Amazon Patents. Science, Technology, & Human Values, 016224392094366. https://doi.org/10.1177/0162243920943665
Crowston, K., & Bolici, F.. (2020). Impacts of the Use of Machine Learning on Work Design. In 8th International Conference on Human-Agent Interaction. https://doi.org/10.1145/3406499.3415070
PDF icon Impacts_of_ML_for_HAI_2020.pdf (453.59 KB)

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