Anton Korinek

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

Senior Researcher, Complexity Science Hub Vienna

Nonresident Fellow, The Brookings Institution 

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


Anton is a Professor at the University of Virginia, Department of Economics and Darden School of Business as well as a Nonresident Fellow at the Brookings Institution, 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 2024     Profile of my research on transformative AI published in TIME Magazine

Apr 2024     Publication of the Oxford Handbook of AI Governance (see Intro)

Nov 2023     My Testimony for the Senate's AI Insight Forum: Preparing the Workforce for an Uncertain AI Future

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

Dec 2021     Launched Coursera graduate course on the Economics of AI

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Latest Research 

LLMs Level Up—Better, Faster, Cheaper [PDF | WP  | Website],  June 2024 Update to Section 3 of  "Generative AI for Economic Research: Use Cases and Implications for Economists," Journal of Economic Literature.

Provides updated use cases for large language models in economics as of June 2024

Intelligent financial system: how AI is transforming finance [BIS Working Paper | X Thread], with Iñaki Aldasoro et al., June 2024

Analyzes how AI Agents and AGI will transform four main functions of the financial system, examines the risk of disruption, and evaluates regulatory responses

Concentrating Intelligence: Scaling Laws and Market Structure in Generative AI [PDF], with Jai Vipra, Feb. 2024, revised for Economic Policy.

Examines the tendency towards market concentration in foundation models and how to balance competition and safety

Scenarios for the Transition to AGI [PDF | Slides], with Donghyun Suh, March 2024.

Analyzes what the transition to artificial general intelligence would imply for output and wages

Preparing for the  (Non-Existent?) Future of Work [WP | Publication], with Megan Juelfs, Oxford Handbook of AI Governance, pp. 746-776, Apr. 2024

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

Scenario Planning for an A(G)I Future [Link | PDF], IMF Finance & Development Magazine 60(4), pp. 30-33, Dec. 2023

Makes the case that economists and policymakers need to prepare for the possibility of human-level artificial intelligence

AI's Economic Peril to Democracy [PDF | Publication], with Stephanie A. Bell, Journal of Democracy, Oct. 2023

Examines how AI could erode democracy by amplifying inequality and offers countervailing solutions 

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 et al. (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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