The Extended Corporate Mind: When Corporations Use AI to Break the Law

North Carolina Law Review 98:893-932 (2020)
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Abstract

Algorithms may soon replace employees as the leading cause of corporate harm. For centuries, the law has defined corporate misconduct — anything from civil discrimination to criminal insider trading — in terms of employee misconduct. Today, however, breakthroughs in artificial intelligence and big data allow automated systems to make many corporate decisions, e.g., who gets a loan or what stocks to buy. These technologies introduce valuable efficiencies, but they do not remove (or even always reduce) the incidence of corporate harm. Unless the law adapts, corporations will become increasingly immune to civil and criminal liability as they transfer responsibility from employees to algorithms. This Article is the first to tackle the full extent of the growing doctrinal gap left by algorithmic corporate misconduct. To hold corporations accountable, the law must sometimes treat them as if they “know” information stored on their servers and “intend” decisions reached by their automated systems. Cognitive science and the philosophy of mind offer a path forward. The “extended mind thesis” complicates traditional views about the physical boundaries of the mind. The thesis states that the mind encompasses any system that sufficiently assists thought, e.g. by facilitating recall or enhancing decision-making. For natural people, the thesis implies that minds can extend beyond the brain to include external cognitive aids, like rolodexes and calculators. This Article adapts the thesis to corporate law. It motivates and proposes a doctrinal framework for extending the corporate mind to the algorithms that are increasingly integral to corporate thought. The law needs such an innovation if it is to hold future corporations to account for their most serious harms.

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Mihailis E. Diamantis
University of Iowa

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Liability for Robots: Sidestepping the Gaps.Bartek Chomanski - 2021 - Philosophy and Technology 34 (4):1013-1032.

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