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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
Natale, S., & Ballatore, A.. (2017). Imagining the thinking machine. Convergence: The International Journal Of Research Into New Media Technologies, 135485651771516. https://doi.org/10.1177/1354856517715164
Vermeulen, B., Kesselhut, J., Pyka, A., & Saviotti, P.. (2018). The impact of automation on employment: Just the usual structural change?. Sustainability, 10(5), 1661. https://doi.org/10.3390/su10051661
Goos, M. (2018). The impact of technological progress on labour markets: policy challenges. Oxford Review Of Economic Policy, 34(3), 362 - 375. https://doi.org/10.1093/oxrep/gry002
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
Reis, J., Santo, P. Espírito, Lisbon, P., & Melão, N.. (2019). Impacts of Artificial Intelligence on Public Administration: A Systematic Literature Review. In 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). Presented at the 2019 14th Iberian Conference on Information Systems and Technologies (CISTI). Retrieved de https://ieeexplore.ieee.org/document/8760778
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
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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)
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
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
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)
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
Mehic, A. (2018). Industrial employment and income inequality: Evidence from panel data. Structural Change And Economic Dynamics, 45, 84 - 93. https://doi.org/10.1016/j.strueco.2018.02.006
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

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