Analogies and Disanalogies Between Machine-Driven and Human-Driven Legal Judgement

Authors

  • Reuben Binns

Keywords:

Algorithmic decision-making, normativity, rule of law, discretion, feedback loops

Abstract

Are there certain desirable properties from text-driven law, which have parallels in data-driven law? As a preliminary exercise, this article explores a range of analogies and disanalogies between text-driven normativity and its data-driven counterparts. Ultimately, the conclusion is that the analogies are weaker than the disanalogies. But the hope is that, in the process of drawing them, we learn something more about the comparison between text and data-driven normativities and the (im?)possibility of data-driven law.

Reply by Emily M. Bender, Professor of Computational Linguistics, University of Washington.

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Published

10 December 2020
Total downloads
696

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Section

Online first

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How to Cite

Binns, Reuben. 2020. “Analogies and Disanalogies Between Machine-Driven and Human-Driven Legal Judgement”. Journal of Cross-Disciplinary Research in Computational Law 1 (1). https://journalcrcl.org/crcl/article/view/5.