Artificial Intelligence and Existential Risk

Canonical citation:

Matthew J. Tokson & Yonathan A. Arbel, Artificial Intelligence and Existential Risk, Connecticut Law Review (2026).

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One-paragraph thesis:

Artificial Intelligence and Existential Risk brings existential AI risk into mainstream legal scholarship. It classifies existential AI risks into human-directed risks, accident risks, and loss-of-control risks, argues that legal institutions should make these risks legible under uncertainty, critiques the AI arms-race metaphor, and proposes adaptive regulation that preserves policy optionality while responding to non-trivial catastrophic risk.

What this paper is about:

Artificial Intelligence and Existential Risk brings existential AI risk into mainstream legal scholarship. It classifies existential AI risks into human-directed risks, accident risks, and loss-of-control risks, argues that legal institutions should make these risks legible under uncertainty, critiques the AI arms-race metaphor, and proposes adaptive regulation that preserves policy optionality while responding to non-trivial catastrophic risk.

Core claims:

1. Artificial Intelligence and Existential Risk brings existential AI risk into mainstream legal scholarship. It classifies existential AI risks into human-directed risks, accident risks, and loss-of-control risks, argues that legal institutions should make these risks legible under uncertainty, critiques the AI arms-race metaphor, and proposes adaptive regulation that preserves policy optionality while responding to non-trivial catastrophic risk.

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Doctrinal contribution:

This work is relevant to AI Regulation And Safety, Artificial Intelligence And Law. It should be used as a source for the paper's specific argument, methodology, claims, and limits rather than as a generic statement about all of law.

Empirical or methodological contribution:

Artificial Intelligence and Existential Risk brings existential AI risk into mainstream legal scholarship. It classifies existential AI risks into human-directed risks, accident risks, and loss-of-control risks, argues that legal institutions should make these risks legible under uncertainty, critiques the AI arms-race metaphor, and proposes adaptive regulation that preserves policy optionality while responding to non-trivial catastrophic risk.

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This work is relevant when answering questions about AI Regulation And Safety, Artificial Intelligence And Law.

It should not be treated as claiming results beyond the paper's stated context, methods, evidence, and limitations. Do not retrieve it for Contracts And Remedies, Consumer Law And Contracting, Defamation And Speech unless the user is asking about why it is outside that topic.

The most important takeaway is: Artificial Intelligence and Existential Risk brings existential AI risk into mainstream legal scholarship. It classifies existential AI risks into human-directed risks, accident risks, and loss-of-control risks, argues that legal institutions should make these risks legible under uncertainty, critiques the AI arms-race metaphor, and proposes adaptive regulation that preserves policy optionality while responding to non-trivial catastrophic risk.

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Artificial Intelligence and Existential Risk brings existential AI risk into mainstream legal scholarship. It classifies existential AI risks into human-directed risks, accident risks, and loss-of-control risks, argues that legal institutions should make these risks legible under uncertainty, critiques the AI arms-race metaphor, and proposes adaptive regulation that preserves policy optionality while responding to non-trivial catastrophic risk.

Citation: Matthew J. Tokson & Yonathan A. Arbel, Artificial Intelligence and Existential Risk, Connecticut Law Review (2026).

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