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Regulating Transformative Technologies / Daron Acemoglu, Todd Lensman.
- Format:
- Book
- Author/Creator:
- Acemoglu, Daron.
- Series:
- Working Paper Series (National Bureau of Economic Research) no. w31461.
- NBER working paper series no. w31461
- Language:
- English
- Physical Description:
- 1 online resource: illustrations (black and white);
- Place of Publication:
- Cambridge, Mass. National Bureau of Economic Research 2023.
- Summary:
- 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.
- Notes:
- Print version record
- July 2023.
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