Main Content
“Adversarial attacks on medical Machine Learning” by Samuel Finlayson, John Bowers, Joi Ito, Jonathan Zittrain et al., preprint (2019)
3.3.2
https://arxiv.org/pdf/1804.05296.pdf
"Artificial Intelligence — The Revolution Hasn’t Happened Yet" by Michael Jordan, Medium (April 2018)
1.1
https://perma.cc/4JM9-E4HC
“Big Data’s Disparate Impact” by Solon Barocas and Andrew D. Selbst, California Law Review (2016)
3.1.1
http://www.cs.yale.edu/homes/jf/BarocasSelbst.pdf
[CIRCULATED VIA EMAIL] The Book of Why by Judea Pearl and Dana Mackenzie, Basic Books (2018). Read Introduction.
4.2.1
http:///
[CIRCULATED VIA EMAIL] “The Illusion of Algorithmic Fairness” by Rodrigo Ochigame, Preprint (2018)
4.1.2
https://
[COPIES TO BE DISTRIBUTED] Weapons of Math Destruction by Cathy O’Neil, Broadway Books (2016). Read Introduction and Chapter 1: “Bomb Parts: What Is a Model?”
2.1.1
http:///
“Counterfactual Explanations Without Opening the Black Box: Automated Decisions and the GDPR” by Sandra Wachter et al., Harvard Journal of Law and Technology (2018)
3.2.1
https://jolt.law.harvard.edu/assets/articlePDFs/v31/Counterfactual-Explanations-without-Opening-the-Black-Box-Sandra-Wachter-et-al.pdf
“Discrimination in the Age of Algorithms” by Jon Kleinberg, Jens Ludwig, Sendhil Mullainathan, and Cass Sunstein, NBER (2018)
4.1.1
https://www.nber.org/papers/w25548.pdf
“Hidden Technical Debt in Machine Learning Systems” by D. Sculley et al., NIPS (2015)
4.3.1
https://papers.nips.cc/paper/5656-hidden-technical-debt-in-machine-learning-systems.pdf
“Law and Adversarial Machine Learning” by Ram Shankar Siva Kumar et al., ArXiv (2018)
3.3.1
https://arxiv.org/pdf/1810.10731.pdf
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