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Papers

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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
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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
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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
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
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
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
Jha, S. (2020). Automation and Radiology—Part 1. In Academic Radiology (pp. 147–149). https://doi.org/10.1016/j.acra.2019.10.026
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
Johnson, K. W., Soto, J. Torres, Glicksberg, B. S., Shameer, K., Miotto, R., Ali, M., et al.. (2018). Artificial Intelligence in Cardiology. Journal Of The American College Of Cardiology, 71(23), 2668 - 2679. https://doi.org/10.1016/j.jacc.2018.03.521
Johnson, A. E. W., Ghassemi, M. M., Nemati, S., Niehaus, K. E., Clifton, D., & Clifford, G. D.. (2016). Machine learning and decision support in critical care. Proceedings Of The Ieee, 104(2), 444 - 466. https://doi.org/10.1109/JPROC.2015.2501978
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
Jokisch, O., & Huber, M.. (2018). Advances in the development of a cognitive user interface. Matec Web Of Conferences, 161, 01003. https://doi.org/10.1051/matecconf/201816101003
Jones, L. D., Golan, D., Hanna, S. A., & Ramachandran, M.. (2018). Artificial intelligence, machine learning and the evolution of healthcare. Bone & Joint Research, 7(3), 223 - 225. https://doi.org/10.1302/2046-3758.73.BJR-2017-0147.R1
Jung, J. Hwa, & Lim, D. Geon. (2020). Industrial robots, employment growth, and labor cost: A simultaneous equation analysis. Technological Forecasting And Social Change, 159, 120202. https://doi.org/10.1016/j.techfore.2020.120202
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Kamali, K., Fan, X., & Yen, J. O. H. N. John. (2007). Towards a theory for multiparty proactive communication in agent teams. International Journal Of Cooperative Information Systems, 16(02), 271 - 298. https://doi.org/10.1142/S0218843007001640
Kao, Y. - F., & Venkatachalam, R.. (2018). Human and Machine Learning. Computational Economics. https://doi.org/10.1007/s10614-018-9803-z
Karabarbounis, L., & Neiman, B.. (2014). The global decline of the labor share. The Quarterly Journal Of Economics, 129(1), 61 - 103. https://doi.org/10.1093/qje/qjt032
Karwowski, Ain Intelli. (2018). Advances in intelligent systems and computing. In Proceedings of the 1st International Conference on Intelligent Human Systems Integration. Retrieved de https://link.springer.com/book/10.1007/978-3-030-11051-2?page=2
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

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