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References Amodei, Dario, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, and Dan Mané, “Concrete Problems in AI Safety,” Ithaca, N.Y.: Cornell University Library, 2016. As of February 2, 2017: https://arxiv.org/abs/1606.06565 Angwin, Julia, Jeff Larson, Surya Mattu, and Lauren Kirchner, “Machine Bias: There’s Software Used Across the Country to Predict Future Criminals. And It’s Biased Against Blacks,” ProPublica, May 23, 2016. As of December 5, 2016: https://www.propublica.org/article/ machine-bias-risk-assessments-in-criminal-sentencing Arndt, A. B., “Al-Khwarizmi,” Mathematics Teacher, Vol. 76, No. 9, 1983, pp. 668–670. Athey, Susan, “Machine Learning and Causal Inference for Policy Evaluation,” Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, Australia, August 10–13, 2015, pp. 5–6. Autor, David, “The Polarization of Job Opportunities in the U.S. Labor Market: Implications for Employment and Earnings,” Washington, D.C.: Center for American Progress and the Hamilton Project, April 2010. Baldus, David C., Charles Pulaski, and George Woodworth, “Comparative Review of Death Sentences: An Empirical Study of the Georgia Experience,” Journal of Criminal Law and Criminology, Vol. 74, No. 3, Autumn 1983, pp. 661–753. Baldus, David C., Charles A. Pulaski, George Woodworth, and Frederick D. Kyle, “Identifying Comparatively Excessive Sentences of Death: A Quantitative Approach,” Stanford Law Review, Vol. 33, No. 1, November 1980, pp. 1–74. Barocas, Solon, and Helen Nissenbaum, “Big Data’s End Run Around Procedural Privacy Protections,” Communications of the ACM, Vol. 57, No. 11, 2014, pp. 31–33. Barocas, Solon, and Andrew D. Selbst, “Big Data’s Disparate Impact,” California Law Review, Vol. 104, 2016, pp. 671–732. 29PDF Image | Intelligence in Our Image Risks of Bias and Errors in Artificial Intelligence
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