Anton Korinek

David M. Rubenstein Fellow, The Brookings Institution 

Professor, Department of Economics and Darden School of Business, University of Virginia

Economics of AI Lead, Centre for the Governance of AI

Research Associate, NBER and CEPR

Google Scholar

Email: anton [at] korinek [dot] com 

Twitter: @akorinek

Bio

Anton is a David M. Rubenstein Fellow at the Brookings Institution, a Professor at the University of Virginia, Department of Economics and Darden School of Business as well as a Research Associate at the NBER, a Research Fellow at the CEPR and the Economics of AI Lead at the Centre for the Governance of AI. He received his PhD from Columbia University in 2007 after several years of work experience in the IT and financial sectors. He has also worked at Johns Hopkins and at the University of Maryland and has been a visiting scholar at Harvard University, the World Bank, the IMF, the BIS and numerous central banks.

His research analyzes how to prepare for a world of transformative AI systems. He investigates the implications of advanced AI for economic growth, labor markets, inequality, and the future of our society. In his past research, he investigated the mechanics of financial crises and developed policy measures to prevent future crises, including an influential framework for capital flow regulation in emerging economies. 

Latest News   

Apr 2023     Presentation at the IMF/WB Spring Meetings on Generative AI: Four Messages to Economic Policymakers

Sep 2022     Organized Brookings/GovAI Conference on the Governance of Transformative AI

Apr 2022     Online Launch of the Oxford Handbook of AI Governance

Dec 2021     Launched Coursera Online Course on the Economics of AI

Sept 2021    Awarded David M. Rubenstein Fellowship by the Brookings Institution

June 2021    Promoted to Full Professor, University of Virginia

Mar 2020    Organized 2nd INET/IMF Conference on "Macroeconomics in the Age of AI"


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Latest Research 

Language Models and Cognitive Automation for Economic Research [PDF], Feb. 2023

Lays out 25 use cases for large language models in economics and discusses the implications for the future of economic research 

Preparing for the  (Non-Existent?) Future of Work [PDF], with Megan Juelfs, forthcoming in the Oxford Handbook of AI Governance, Mar. 2022

If transformative AI makes human labor redundant, what are the economic and social implications, and how can we prepare for it? 

AI and Shared Prosperity [Publication | WP], with Katya Klinova, Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society (AIES ’21), pp. 645-651, July 2021

Develops a framework for AI developers to take into account the impact of their inventions on workers 

Artificial Intelligence, Globalization, and Strategies for Economic Development [PDF], with Joseph Stiglitz, Jan. 2021

Labor-saving advances in AI may undo the gains from globalization and pose new challenges for economic development 

Steering Technological Progress [PDF | Slides], with Joseph Stiglitz, Oct. 2020

Analyzes how to steer technological progress in directions that complement labor rather than displacing it - cited by The Economist's Free Exchange

Integrating Ethical Values and Economic Value to Steer Progress in Artificial Intelligence [Publication | WP], in Markus Dubber, Frank Pasquale and Sunit Das (eds.), Oxford Handbook of Ethics of Artificial Intelligence, Oxford University Press, July 2020

Complementing market incentives with ethical values is crucial to steer progress in AI in a direction that is beneficial for humanity at large

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