Alumni Spotlight: Anton Korinek, Professor, Department of Economics and Darden School of Business, University of Virginia
We had the honor to speak with Professor Anton Korinek, a Columbia Economics PhD alumnus. He reflects on his time at Columbia, shares how AI is reshaping economic research, and offers advice for current PhD students navigating this rapidly changing landscape.
Could you start by briefly introducing yourself and what you’re currently working on?
I am a Professor of Economics at the University of Virginia and at the Darden School of Business, and I serve as the Faculty Director of the Economics of Transformative AI Initiative, a research group I recently founded. My current work centers on two main themes: what transformative advances in AI will mean for the economy and society, and how economists can harness AI tools to improve research methods and economic analysis.
What led you to Columbia for your PhD, and how did that experience shape your path?
Columbia was a very natural choice for me—academically and personally. I was drawn to the strength of the department as well as the energy of New York City. I started the PhD program in 2001, which turned out to be an intense year in many ways, from the world-changing events of 9/11 to academic milestones. My first-year macroeconomics professor, Joseph Stiglitz, who later became my advisor, won the Nobel Prize that year. Overall, Columbia offered an excellent intellectual environment. I had the freedom to pursue questions I considered important and to learn from faculty across different fields. That combination of rigor and openness really helped shape my trajectory as a researcher.
Were there particular professors or courses at Columbia that influenced your research direction?
My dissertation advisor, Joe Stiglitz, had the most formative influence on my development as an economist. I took his course, worked as his research assistant, co-authored papers with him, and benefited enormously from his mentorship. We remain in touch and continue to collaborate. I also learned a great deal from other faculty, including Donald Davis, Patrick Bolton, and David Weinstein. There was a strong network of scholars whose work and teaching left a lasting imprint on how I think about economic questions.
You were recently named to the TIME100 AI list. What is your current research agenda, and why is AI such an important topic for economists?
When people talk about AI today, they often think of tools like chatbots or code assistants. Those are valuable, but my research is focused on what comes next: AI systems that may surpass human cognitive capabilities across a broad range of tasks. Leading AI labs project that systems of this kind could emerge within a relatively short time horizon. If that happens, the consequences for the economy will be profound. This goes beyond incremental productivity gains—it touches labor markets, income distribution, macroeconomic stability, and even how we organize research and innovation. Economists need to start taking these possibilities seriously now, rather than treating them as science fiction.
How do you see the field of economics evolving in response to rapid advances in AI and automation?
Economic research is already changing. Not long ago, AI tools were mainly useful for editing or rephrasing text. Today, I routinely use AI to help draft sections of papers, generate code, and explore alternative modeling choices. Under human supervision, these systems can function almost like co-authors. This will inevitably influence how we train economists and what skills we value. The comparative advantage of human researchers is shifting toward problem selection, interpretation, and judgment. Meanwhile, more routine analytical or coding tasks can be increasingly automated. Being able to use AI effectively will become a core skill for anyone who wants to do cutting-edge work.
What advice would you give to current Columbia Economics PhD students, especially those interested in AI and policy-facing research?
First, take seriously the possibility that truly transformative AI systems could arrive within the next few years. That would not just tweak existing models, but it would fundamentally reshape the environment in which our theories and empirical work operate. Whatever your field, labor, development, macro, or finance, you should be asking how the world would be altered if AI systems exceeded human capabilities.
Second, for now, treat AI as a force multiplier rather than something to fear or ignore. Tools that help with coding, data analysis, and even aspects of writing can dramatically increase your research productivity. We work in a competitive profession, and those who are comfortable integrating these tools into their workflow will have a significant advantage. At the same time, it’s essential to remain thoughtful about what comes after, when AI systems exceed our cognitive capabilities across the board.
What does it mean to you to be part of the Columbia Economics alumni community? How can we strengthen connections between alumni and current students?
I’m very proud to be a Columbia Economics alum. My time in the program was a pivotal period in my life, and many of my closest friends and collaborators today are people I met at Columbia.
