Papers

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A
Acemoglu, D., & Restrepo, P.. (2018). Implications of technology for growth, factor shares, and employment. American Economic Review, 108(6), 1488 - 1542. https://doi.org/10.1257/aer.20160696
Araujo, T. (2018). The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions. Computers In Human Behavior, 85, 183 - 189. https://doi.org/10.1016/j.chb.2018.03.051
Arogyaswamy, B., & Hunter, J.. (2018). The impact of technology and globalization on employment and equity. International Journal Of Global Sustainability, 3(1), 49. https://doi.org/10.5296/ijgs.v3i1.14127
Avati, A., Jung, K., Harman, S., Downing, L., Ng, A., & Shah, N. H.. (2018). Improving palliative care with deep learning. Bmc Medical Informatics And Decision Making, 18(S4). https://doi.org/10.1186/s12911-018-0677-8
C
Caruana, R., Lou, Y., Gehrke, J., Koch, P., Sturm, M., & Elhadad, N.. (2015). Intelligible Models for HealthCare (L. Cao, Zhang, C., Joachims, T., Webb, G., Margineantu, D. D., & Williams, G., Trans.). In the 21th ACM SIGKDD International ConferenceProceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '15 (1721 - 1730). https://doi.org/10.1145/278325810.1145/2783258.2788613
Rücker, D., Hornfeck, R., & Paetzold, K.. (2018). Investigating ergonomics in the context of human-robot collaboration as a sociotechnical system (Vol. 784, pp. 127 - 135; J. Chen, Ed.). In (Vol. 784, pp. 127 - 135). https://doi.org/10.1007/978-3-319-94346-6_12
Cho, J., & Kim, J.. (2018). Identifying factors reinforcing robotization: Interactive forces of employment, working hour and wage. Sustainability, 10(2), 490. https://doi.org/10.3390/su10020490
Choi, D. Y., & Kang, J. Hyeung. (2019). Introduction: The Future of Jobs in an Increasingly Autonomous Economy. Journal Of Management Inquiry, 28(3), 298 - 299. https://doi.org/10.1177/1056492619827373
Duckworth, P., Graham, L., & Osborne, M.. (2019). Inferring work task automatability from AI expert evidence (V. Conitzer, Hadfield, G., & Vallor, S., Trans.). In the 2019 AAAI/ACM ConferenceProceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society - AIES '19 (485 - 491). https://doi.org/10.1145/330661810.1145/3306618.3314247
Crowston, K., & Bolici, F.. (2019). Impacts of machine learning on work. In Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52). Retrieved de http://hdl.handle.net/10125/60031
PDF icon Impacts_of_machine_learning_on_work__revision_.pdf (300.76 KB)
Crowston, K., & Bolici, F.. (2020). Impacts of Machine Learning on Work Design. Syracuse, NY: Syracuse University School of Information Studies.
PDF icon Impact of machine learning on work.pdf (604.31 KB)
H
J. Heberling, M., & Isaac, B. L.. (2018). iNaturalist as a tool to expand the research value of museum specimens. Applications In Plant Sciences, 6(11), e01193. https://doi.org/10.1002/aps3.1193

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