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In this article, I discuss how technological development could change the way that we think about the essential features of legality. In particular, I focus on the strengths and weaknesses of machine learning in the context of legislation and adjudication. I argue that the content of those essential features could depend upon our willingness to make tradeoffs between intelligibility and results. These tradeoffs might lead us to reject a concept that requires critical officials (HLA Hart), reason-based tests of legitimacy (Joseph Raz), or deep justifications for coercion (Ronald Dworkin). I conclude that our concept of law will likely be shaped by our willingness to accept a growing disconnect between the way that we decide and the way that the system does.
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B. L. Sheppard (2018) studied this question.
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