cover image: How Learning About Harms Impacts the Optimal Rate of Artificial Intelligence Adoption

20.500.12592/d51cb8j

How Learning About Harms Impacts the Optimal Rate of Artificial Intelligence Adoption

2 Feb 2024

This paper examines recent proposals and research suggesting that AI adoption should be delayed until its potential harms are properly understood. It is shown that conclusions regarding the social optimality of delayed AI adoption are sensitive to assumptions regarding the process by which regulators learn about the salience of particular harms. When such learning is by doing -- based on the real-world adoption of AI -- this generally favours acceleration of AI adoption to surface and react to potential harms more quickly. This case is strengthened when AI adoption is potentially reversible. The paper examines how different conclusions regarding the optimality of accelerated or delayed AI adoption influence and are influenced by other policies that may moderate AI harm.
industrial organization regulatory economics development and growth productivity, innovation, and entrepreneurship innovation and r&d

Authors

Joshua S. Gans

Acknowledgements & Disclosure
Joshua Gans has drawn on the findings of his research for both compensated speaking engagements and consulting engagements. He has written the books Prediction Machines, Power & Prediction, and Innovation + Equality on the economics of AI for which he receives royalties. He is also chief economist of the Creative Destruction Lab, a University of Toronto-based program that helps seed stage companies, from which he receives compensation. He conducts consulting on anti-trust and intellectual property matters with an association with Charles River Associates and his ownership of Core Economic Research Ltd. He also has equity and advisory relationships with a number of startup firms. The views expressed herein are those of the author and do not necessarily reflect the views of the National Bureau of Economic Research. Joshua S. Gans Joshua Gans has drawn on the findings of his research for both compensated speaking engagements and consulting engagements. He is also chief economist of the Creative Destruction Lab, a University of Toronto-based program that helps seed-stage companies, from which he receives compensation. He conducts consulting on cryptocurrency and payments matters with an association with Charles River Associates and his ownership of Core Economic Research Ltd. He also has equity and advisory relationships with a number of startup firms.
DOI
https://doi.org/10.3386/w32105
Published in
United States of America

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