Punishing Artificial Intelligence: Legal Fiction or Science Fiction

UC Davis Law Review 53:323-384 (2019)
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Abstract

Whether causing flash crashes in financial markets, purchasing illegal drugs, or running over pedestrians, AI is increasingly engaging in activity that would be criminal for a natural person, or even an artificial person like a corporation. We argue that criminal law falls short in cases where an AI causes certain types of harm and there are no practically or legally identifiable upstream criminal actors. This Article explores potential solutions to this problem, focusing on holding AI directly criminally liable where it is acting autonomously and irreducibly. Conventional wisdom holds that punishing AI is incongruous with basic criminal law principles such as the capacity for culpability and the requirement of a guilty mind. Drawing on analogies to corporate and strict criminal liability, as well as familiar imputation principles, we show how a coherent theoretical case can be constructed for AI punishment. AI punishment could result in general deterrence and expressive benefits, and it need not run afoul of negative limitations such as punishing in excess of culpability. Ultimately, however, punishing AI is not justified, because it might entail significant costs and it would certainly require radical legal changes. Modest changes to existing criminal laws that target persons, together with potentially expanded civil liability, are a better solution to AI crime.

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Author Profiles

Ryan Abbott
University of Surrey
Alexander Sarch
University of Surrey

Citations of this work

Definitions of intent suitable for algorithms.Hal Ashton - 2022 - Artificial Intelligence and Law 31 (3):515-546.

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References found in this work

[Introduction].T. K. Abbott - 1884 - Mind 9 (33):163-165.

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