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Machine Learning and the Rule of Law

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  • Chen, Daniel L.
Abstract
Predictive judicial analytics holds the promise of increasing the fairness of law. Much empirical work observes inconsistencies in judicial behavior. By predicting judicial decisions—with more or less accuracy depending on judicial attributes or case characteristics—machine learning offers an approach to detecting when judges most likely to allow extralegal biases to influence their decision making. In particular, low predictive accuracy may identify cases of judicial “indifference,” where case characteristics (interacting with judicial attributes) do no strongly dispose a judge in favor of one or another outcome. In such cases, biases may hold greater sway, implicating the fairness of the legal system.

Suggested Citation

  • Chen, Daniel L., 2018. "Machine Learning and the Rule of Law," TSE Working Papers 18-975, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:33149
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    References listed on IDEAS

    as
    1. Christina L. Boyd & Lee Epstein & Andrew D. Martin, 2010. "Untangling the Causal Effects of Sex on Judging," American Journal of Political Science, John Wiley & Sons, vol. 54(2), pages 389-411, April.
    2. Devin G. Pope & Joseph Price & Justin Wolfers, 2018. "Awareness Reduces Racial Bias," Management Science, INFORMS, vol. 64(11), pages 4988-4995, November.
    3. Ozkan Eren & Naci Mocan, 2018. "Emotional Judges and Unlucky Juveniles," American Economic Journal: Applied Economics, American Economic Association, vol. 10(3), pages 171-205, July.
    4. Chen, Daniel L. & Moskowitz, Tobias J. & Shue, Kelly, 2016. "Decision-Making Under the Gambler’s Fallacy: Evidence From Asylum Courts, Loan Officers, and Baseball Umpires," IAST Working Papers 16-43, Institute for Advanced Study in Toulouse (IAST).
    5. Chen, Daniel L. & Halberstam, Yosh & Yu, Alan, 2016. "Covering: Mutable Characteristics and Perceptions of Voice in the U.S. Supreme Court," TSE Working Papers 16-680, Toulouse School of Economics (TSE), revised Feb 2020.
    6. Mustard, David B, 2001. "Racial, Ethnic, and Gender Disparities in Sentencing: Evidence from the U.S. Federal Courts," Journal of Law and Economics, University of Chicago Press, vol. 44(1), pages 285-314, April.
    7. Daniel L. Chen & Tobias J. Moskowitz & Kelly Shue, 2016. "Decision Making Under the Gambler’s Fallacy: Evidence from Asylum Judges, Loan Officers, and Baseball Umpires," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(3), pages 1181-1242.
    8. Ozkan Eren & Naci Mocan, 2016. "Emotional Judges and Unlucky Juveniles," Working Papers id:11299, eSocialSciences.
    9. David S. Abrams & Marianne Bertrand & Sendhil Mullainathan, 2012. "Do Judges Vary in Their Treatment of Race?," The Journal of Legal Studies, University of Chicago Press, vol. 41(2), pages 347-383.
    10. Max Schanzenbach, 2005. "Racial and Sex Disparities in Prison Sentences: The Effect of District-Level Judicial Demographics," The Journal of Legal Studies, University of Chicago Press, vol. 34(1), pages 57-92, January.
    Full references (including those not matched with items on IDEAS)

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