Regulating Transformative Technologies

Daron Acemoglu and Todd Lensman

No 31461, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: Transformative technologies like generative artificial intelligence promise to accelerate productivity growth across many sectors, but they also present new risks from potential misuse. We develop a multi-sector 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 convex. If social damages are proportional to the productivity gains from the new technology, a higher growth rate 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-codes: H21 O33 O41 (search for similar items in EconPapers)
Date: 2023-07
New Economics Papers: this item is included in nep-ain, nep-reg and nep-tid
Note: EFG PR
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Citations: View citations in EconPapers (1)

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Journal Article: Regulating Transformative Technologies (2024)
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