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Papers

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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
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., et al.. (2017). Artificial intelligence in healthcare: past, present and future. Stroke And Vascular Neurology, 2(4), 230 - 243. https://doi.org/10.1136/svn-2017-000101
Jha, S. (2020). Automation and Radiology—Part 1. In Academic Radiology (pp. 147–149). https://doi.org/10.1016/j.acra.2019.10.026
Jensen, B. M., Whyte, C., & Cuomo, S.. (2019). Algorithms at War: The Promise, Peril, and Limits of Artificial Intelligence. International Studies Review. https://doi.org/10.1093/isr/viz025
Jennings, N. R., Moreau, L., Nicholson, D., Ramchurn, S., Roberts, S., Rodden, T., & Rogers, A.. (2014). Human-agent collectives. Communications Of The Acm, 57(12), 80 - 88. https://doi.org/10.1145/269296510.1145/2629559
Jaume-Palasi, L. (2019). Why we are failing to understand the societal impact of artificial intelligence. Social Research: An International Quarterly, 86, pp. 477-498. Retrieved de https://muse.jhu.edu/article/732186
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)
Jarrahi, M. Hossein. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577 - 586. https://doi.org/10.1016/j.bushor.2018.03.007
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Gemmell, L., Wenham, L., & Hauert, S.. (2019). Educating those most impacted by artificial intelligence (Vol. 11626, pp. 344 - 349; S. Isotani, Millán, E., Ogan, A., Hastings, P., McLaren, B., & Luckin, R., Eds.). In (Vol. 11626, pp. 344 - 349). https://doi.org/10.1007/978-3-030-23207-8_63
Introna, L. D. (2016). Algorithms, governance, and governmentality. Science, Technology, & Human Values, 41(1), 17 - 49. https://doi.org/10.1177/0162243915587360
Iliadis, L., Maglogiannis, I., & Plagianakos, V.. (2018). Artificial Intelligence Applications and Innovations. In 14th IFIP WG 12.5 International Conference, AIAI 2018. Presented at the 14th IFIP WG 12.5 International Conference, AIAI 2018. Retrieved de https://www.springer.com/gp/book/9783319920153
Mlynar, J., Alavi, H. S., Verma, H., & Cantoni, L.. (2018). Lecture Notes in Computer ScienceArtificial General IntelligenceTowards a Sociological Conception of Artificial Intelligence (Vol. 10999, pp. 130 - 139; M. Iklé, Franz, A., Rzepka, R., & Goertzel, B., Eds.). In (Vol. 10999, pp. 130 - 139). https://doi.org/10.1007/978-3-319-97676-1
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Hwang, T. (2018). Computational power and the social impact of artificial intelligence. Ssrn Electronic Journal. https://doi.org/10.2139/ssrn.3147971
Hutchins, E., & Klausen, T.. (1996). Distributed cognition in an airline cockpit. Cognition And Communication At Workcognition And Communication At Work, 15–34.
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
Hukal, P., Berente, N., Germonprez, M., & Schecter, A.. (2019). Bots Coordinating Work in Open Source Software Projects. Computer, 52(9), 52 - 60. https://doi.org/10.1109/MC.2018.2885970
Huang, M. - H., & Rust, R. T.. (2018). Artificial Intelligence in Service. Journal Of Service Research, 21(2), 155 - 172. https://doi.org/10.1177/1094670517752459
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

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