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Regulating Transformative Technologies

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  • Daron Acemoglu
  • Todd Lensman

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.

Suggested Citation

  • Daron Acemoglu & Todd Lensman, 2023. "Regulating Transformative Technologies," NBER Working Papers 31461, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:31461
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    Cited by:

    1. Steven Callander & Hongyi Li, 2024. "Regulating an Innovative Industry," Discussion Papers 2024-07, School of Economics, The University of New South Wales.
    2. Francesco Bogliacino & Paolo Buonanno & Francesco Fallucchi & Marcello Puca, 2023. "Trust in times of AI," CSEF Working Papers 689, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.

    More about this item

    JEL classification:

    • H21 - Public Economics - - Taxation, Subsidies, and Revenue - - - Efficiency; Optimal Taxation
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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