Papers

Export 11 results:
Filters: First Letter Of Last Name is N  [Clear All Filters]
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
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
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
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
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
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, 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
Winn, A. N., & Neuner, J. M.. (2018). Making Sure We Don’t Forget the Basics When Using Machine Learning. Jnci: Journal Of The National Cancer Institute, 111(6), 529 - 530. https://doi.org/10.1093/jnci/djy179
Nelson, A. J., & Irwin, J.. (2014). Occupational identity, technological change, and the librarian/internet-search relationship. Academy Of Management Journal, 57(3), 892 - 928. https://doi.org/10.5465/amj.2012.0201
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
Kittur, A., Yu, L., Hope, T., Chan, J., Lifshitz-Assaf, H., Gilon, K., et al.. (2019). Scaling up analogical innovation with crowds and AI. Proceedings Of The National Academy Of Sciences, 116(6), 1870-1877. https://doi.org/10.1073/pnas.1807185116
Galliers, R. D., Newell, S., Shanks, G., & Topi, H.. (2017). The strategic opportunities and challenges of algorithmic decision-making. The Journal Of Strategic Information Systems, 26(3), 185 - 190. https://doi.org/10.1016/j.jsis.2017.08.002
Working paper
Gries, T., & Naude, W.. (2018). Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter. In Maastricht Economic and social Research institute on Innovation and Technology. Retrieved de http://ftp.iza.org/dp12005.pdf

Pages