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
Email: anton [at] korinek [dot] com
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 areas of expertise include macroeconomics, international finance, and inequality. His most recent research investigates the effects of progress in automation and artificial intelligence for macroeconomic dynamics and inequality. Korinek also focuses on capital controls and macroprudential regulation as policy instruments to reduce the risk of financial crises. He investigates the global spillover effects of such policy measures as well as their implications for income inequality. He has won several fellowships and awards for this work, including from the Institute for New Economic Thinking.
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
Sept 2020 Joined Steering Committee of Partnership on AI's Shared Prosperity Initiative
Mar 2020 Organized 2nd INET/IMF Conference on "Macroeconomics in the Age of AI"
Language Models and Cognitive Automation for Economic Research [PDF], Feb. 2023Lays 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. 2022If 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 2021Develops 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. 2021Labor-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. 2020Analyzes 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 2020Complementing market incentives with ethical values is crucial to steer progress in AI in a direction that is beneficial for humanity at large