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Papers

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Orlikowski, W. J., & C. Iacono, S.. (2001). Desperately seeking "IT" in IT research: A call to theorizing the IT artifact. Information Systems Researchinformation Systems Research, 12, 121–134.
PDF icon GAI_and_skills.pdf (281.94 KB)
Gill, K. S. (2019). Designing AI futures: A symbiotic vision (Vol. 1083, pp. 3 - 18; A. G. Kravets, Groumpos, P. P., Shcherbakov, M., & Kultsova, M., Eds.). In (Vol. 1083, pp. 3 - 18). https://doi.org/10.1007/978-3-030-29743-5_1
Burden, D. J. H. (2009). Deploying embodied AI into virtual worlds. Knowledge-Based Systems, 22(7), 540 - 544. https://doi.org/10.1016/j.knosys.2008.10.001
Robinson, R. M., McCount, M. J., Marathe, A. R., Nothwang, W. D., & Doucette, E. A.. (2016). Degree of Automation in Command and Control Decision Support Systems. In IEEE International Conference on Systems, Man and Cybernetics. Presented at the IEEE International Conference on Systems, Man and Cybernetics. Retrieved de https://ieeexplore.ieee.org/document/7844402
Cai, L., Fan, L., Lai, W., LONG, Y., Wang, P., & Xin, X.. (2018). DEFINITION, APPLICATION AND INFLUENCE OF ARTI FICIAL INTELLIGENCE ON DESIGN INDUSTRIES. Landscape Architecture Frontiers, 6(2), 56. https://doi.org/10.15302/J-LAF-20180207
Miotto, R., Wang, F., Wang, S., Jiang, X., & Dudley, J. T.. (2017). Deep learning for healthcare: review, opportunities and challenges. Briefings In Bioinformatics, 19(6), 1236 - 1246. https://doi.org/10.1093/bib/bbx044
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). https://doi.org/10.1038/srep46450
Günther, W. Arianne, Mehrizi, M. H. Rezazad, Huysman, M., & Feldberg, F.. (2017). Debating big data: A literature review on realizing value from big data. The Journal Of Strategic Information Systems, 26(3), 191 - 209. https://doi.org/10.1016/j.jsis.2017.07.003
Markus, L. M. (2017). Datification, organizational strategy, and is research: What’s the score? . The Journal Of Strategic Information Systems, 26(3), 233 - 241. https://doi.org/10.1016/j.jsis.2017.08.003
Møller, N. L. Holten, Bjørn, P., Villumsen, J. Christoffe, Hancock, T. C. Hansen, Aritake, T., & Tani, S.. (2017). Data tracking in search of workflows (C. P. Lee, Poltrock, S., Barkhuus, L., Borges, M., & Kellogg, W., Trans.). In the 2017 ACM ConferenceProceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW '17 (2153 - 2165). https://doi.org/10.1145/2998181.2998296
Data Science for Undergraduates. (2018). Data Science for Undergraduates. https://doi.org/10.17226/25104
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Bohannon, J. (2017). The cyberscientist. Science, 357(6346), 18 - 21. https://doi.org/10.1126/science.357.6346.18
Sopilnyk, L., Shevchuk, A., & Kopytko, V.. (2018). Cryptocurrency, Artificial Intelligence and basic income as innovative technological system. Path Of Science, 4(8), 2024 - 2030. https://doi.org/10.22178/pos10.22178/pos.37-6
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
Nathan, L. F. (2018). Creativity, the arts, and the future of work (pp. 283 - 310; J. W. Cook, Ed.). In (pp. 283 - 310). https://doi.org/10.1007/978-3-319-78580-6_9

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