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Machine Learning and 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 Rule of Law," TSE Working Papers 18-975, Toulouse School of Economics (TSE).
  • Handle: RePEc:tse:wpaper:33149
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    1. repec:wly:amposc:v:54:y:2010:i:2:p:389-411 is not listed on IDEAS
    2. Devin G. Pope & Joseph Price & Justin Wolfers, 2013. "Awareness Reduces Racial Bias," NBER Working Papers 19765, National Bureau of Economic Research, Inc.
    3. Chen, Daniel L. & Halberstam, Yosh & Yu, Alan, 2016. "Covering: Mutable Characteristics and Perceptions of (Masculine) Voice in the U.S. Supreme Court," IAST Working Papers 16-38, Institute for Advanced Study in Toulouse (IAST), revised Aug 2016.
    4. 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.
    5. Ozkan Eren & Naci Mocan, 2016. "Emotional Judges and Unlucky Juveniles," NBER Working Papers 22611, National Bureau of Economic Research, Inc.
    6. 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).
    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, Oxford University Press, vol. 131(3), pages 1181-1242.
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