Anton Korinek

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

Senior Researcher, Complexity Science Hub Vienna

Visiting 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

Bio

Anton is a Professor at the University of Virginia, Department of Economics and Darden School of Business as well as a Visiting Scholar at the Brookings Institution, a Senior Researcher at the Complexity Science Hub Vienna, 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 and has been featured in the New York Times, Washington Post, Wall Street Journal, the Economist, and TIME Magazine. 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 

Generative AI for Economic Research:  LLMs Learn to Collaborate and Reason [PDF  | Deep Dive Podcast (11 min)],  October 2024

Update of my original JEL piece on GenAI focusing on the advances of the past six months, with particular focus on LLM reasoning and collaborative workspaces

Economic Policy Challenges for the Age of AI [PDF | Deep Dive Podcast (11min)], Sep. 2024.

Discusses the paradigm shift that the Age of AI will generate and examines the resulting challenges for economics and economic policy

Concentrating Intelligence: Scaling and Market Structure in Artificial Intelligence [PDF | INET WP | Blog], with Jai Vipra, Aug. 2024, revised for Economic Policy.

Examines market concentration in AI, the potential for market tipping, and the risks from vertical integration 

Intelligent financial system: how AI is transforming finance [BIS Working Paper | X Thread | LM Podcast (15min)], 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

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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