We talk with our colleague Sandy Mayson about the use of algorithms in criminal law decisionmaking - and especially their troubling and difficult to disentangle incorporation of race. From bail to sentencing to policing effort to hiring and admitting to college, we subject different social groups to different risks of erroneous treatment, predicting, for example, that an individual is likely to commit another crime when in fact he or she will not reoffend. What should we do? Reject the use of algorithms - is that even possible? Attempt to "correct" the algorithms? Sandy teaches us about the difficulty of achieving algorithmic fairness.
This show’s links:
Sandy Mayson's faculty profile (http://www.law.uga.edu/profile/sandra-g-mayson) and writing (https://papers.ssrn.com/sol3/cf_dev/AbsByAuth.cfm?per_id=714728)
Sandra Mayson, Bias In, Bias Out (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3257004)
Malcolm Feeley and Jonathan Simon, The New Penology: Notes on the Emerging Strategy of Corrections and Its Implications (https://scholarship.law.berkeley.edu/cgi/viewcontent.cgi?article=1717&context=facpubs)
Robert Martinson, What Works? Questions and Answers about Prison Reform (https://www.pbpp.pa.gov/research_statistics/Documents/Martinson-What%20Works%201974.pdf)
Adam Kolber, Punishment and Moral Risk (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2896948)
Douglas Husak, Kinds of Punishment (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2979458); Douglas Husak, What Do Criminals Deserve? (https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2788152)
Special Guest: Sandy Mayson.