Papers

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Journal Article
Hacker, P., Krestel, R., Grundmann, S., & Naumann, F.. (2020). Explainable AI under contract and tort law: legal incentives and technical challenges. Artificial Intelligence And Law. https://doi.org/10.1007/s10506-020-09260-6
Lopez, J. Amador Dia, Molina-Solana, M., & Kennedy, M. T.. (2018). foo.castr: visualising the future AI workforce. Big Data Analytics, 3(1). https://doi.org/10.1186/s41044-018-0034-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
Zevin, M., Coughlin, S., Bahaadini, S., Besler, E., Rohani, N., Allen, S., et al.. (2017). Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science. Classical And Quantum Gravity, 34, 064003. https://doi.org/10.1088/1361-6382/aa5cea
Zevin, M., Coughlin, S., Bahaadini, S., Besler, E., Rohani, N., Allen, S., et al.. (2017). Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science. Classical And Quantum Gravity, 34, 064003. https://doi.org/10.1088/1361-6382/aa5cea
Kokina, J., & Davenport, T. H.. (2017). How automation is changing auditing. Journal Of Emerging Technologies In Accounting, 14(1), 115 - 122. https://doi.org/10.2308/jeta-51730
Kao, Y. - F., & Venkatachalam, R.. (2018). Human and Machine Learning. Computational Economics. https://doi.org/10.1007/s10614-018-9803-z
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
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
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
Kernbach, J. M., & Staartjes, V. E.. (2020). Machine learning-based clinical prediction modeling – A practical guide for clinicians. Artificial Intelligence In Precision Health, 257–278. https://doi.org/10.1016/b978-0-12-817133-2.00011-2
Choi, D. Y., & Kang, J. Hyeung. (2019). Net job creation in an increasingly autonomous economy: The challenge of a generation. Journal Of Management Inquiry, 28(3), 300 - 305. https://doi.org/10.1177/1056492619827372
Davenport, T., & Kalakota, R.. (2019). The potential for artificial intelligence in healthcare. Future Healthcare Journal, 6(2), 94 - 98. https://doi.org/10.7861/futurehosp.6-2-94
Saba, L., Biswas, M., Kuppili, V., Godia, E. Cuadrado, Suri, H. S., Edla, D. Reddy, et al.. (2019). The present and future of deep learning in radiology. European Journal Of Radiology, 114, 14 - 24. https://doi.org/10.1016/j.ejrad.2019.02.038
Saba, L., Biswas, M., Kuppili, V., Godia, E. Cuadrado, Suri, H. S., Edla, D. Reddy, et al.. (2019). The present and future of deep learning in radiology. European Journal Of Radiology, 114, 14 - 24. https://doi.org/10.1016/j.ejrad.2019.02.038
Saba, L., Biswas, M., Kuppili, V., Godia, E. Cuadrado, Suri, H. S., Edla, D. Reddy, et al.. (2019). The present and future of deep learning in radiology. European Journal Of Radiology, 114, 14 - 24. https://doi.org/10.1016/j.ejrad.2019.02.038
Khan, S. Rafi. (2018). Reinventing capitalism to address automation: Sharing work to secure employment and income. Competition & Change, 22(4), 343 - 362. https://doi.org/10.1177/1024529418783579

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