Papers

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Hershbein, B. (2018). Discussion for JME special issue: APST paper. Journal Of Monetary Economics, 97, 68 - 70. https://doi.org/10.1016/j.jmoneco.2018.05.003
Herzenberg, S., & Alic, J.. (2019). Towards an AI economy that works for all. In Keystone Research Center Future of Work Project sponsored by The Heinz Endowments. Retrieved de https://www.keystoneresearch.org/sites/default/files/FOW_TowardAIEconomyForAllFinalEdit.pdf
Reddy, S. (2018). eHealth - Making Health Care SmarterUse of Artificial Intelligence in Healthcare Delivery (T. F. Heston, Ed.). https://doi.org/http://dx.doi.org/10.5772/intechopen.74714
Hill, J., W. Ford, R., & Farreras, I. G.. (2015). A comparison between human–human online conversations and human–chatbot conversations. Computers In Human Behavior, 49, 245 - 250. https://doi.org/10.1016/j.chb.2015.02.026
Hoc, J. - M. (2000). From human – machine interaction to human – machine cooperation. Ergonomics, 43(7), 833 - 843. https://doi.org/10.1080/001401300409044
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
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
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
Hutchins, E., & Klausen, T.. (1996). Distributed cognition in an airline cockpit. Cognition And Communication At Workcognition And Communication At Work, 15–34.
Hwang, T. (2018). Computational power and the social impact of artificial intelligence. Ssrn Electronic Journal. https://doi.org/10.2139/ssrn.3147971
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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
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
Introna, L. D. (2016). Algorithms, governance, and governmentality. Science, Technology, & Human Values, 41(1), 17 - 49. https://doi.org/10.1177/0162243915587360
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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