Regulating Transformative Technologies

Daron Acemoğlu, Todd Lensman · American Economic Review Insights · 30 Aug 2024

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Abstract

Transformative technologies like generative AI promise to accelerate productivity growth across many sectors, but they also present new risks from potential misuse. We develop a multisector technology adoption model to study the optimal regulation of transformative technologies when society can learn about these risks over time. Socially optimal adoption is gradual and typically convex. If social damages are large and proportional to the new technology’s productivity, a higher growth rate paradoxically leads to slower optimal adoption. Equilibrium adoption is inefficient when firms do not internalize all social damages, and sector-independent regulation is helpful but generally not sufficient to restore optimality. (JEL D21, H21, H25, O31, O33)

About this publication

Leading field journal. A leading journal in economics or a neighbouring field (on the Tinbergen Institute’s A list or near the top of the RePEc ranking), or a top-rated computer-science venue.

Placed by: Leading field journal. How sources are ranked.

Published: 2024 (26 months ago)
Citations: 16 (OpenAlex)

Citations in context

16 citations — 22nd percentile among the 23 indexed papers from 2024 in this collection. Citation counts favor older papers; this compares only same-year papers here, not the whole literature.

□ added to this collection in 2026.

Daron Acemoglu signed the wemustactnow.ai letter · author affiliation matches seed institution massachusetts institute of technology — part of why this paper is in the collection.

Regulating Transformative Technologies

Abstract

About this publication

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