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SUMMARY:Competing Algorithms for Law: Sentencing\, Admissions\, and Employment
DESCRIPTION:Frank Fagan (EDHEC Business School) presented on his recent paper with Saul Levmore\, “Competing Algorithms for Law: Sentencing\, Admissions\, and Employment.” Algorithms increasingly pervade economic and social organization but their legal applications are just emerging. Fagan’s research explores the growing nexus of artificial intelligence and law\, specifically the use of sentencing algorithms to predict rates of recidivism. He argues that state-run competitions for sentencing algorithms could mitigate problems with retrofitting and disclosure. Fagan postulates that the powerful synthesis of competitive advantages for algorithms and human judges will guide innovation in law.
URL:https://cgm.pitt.edu/event/competing-algorithms-for-law-sentencing-admissions-and-employment/
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ATTACH;FMTTYPE=image/png:https://cgm.pitt.edu/wp-content/uploads/2025/10/Screenshot-2025-10-28-at-1.14.00-PM.png
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