I am a political economist currently working as a Ph.D. student in economics at UCLA. I am interested in the governance implications of new technologies, especially computing and AI. I do this work at the intersection of international relations, growth theory, and industrial organization. I am a member of the MIT FutureTech Project and a 2023 Global Priorities Fellow at Oxford University.
MA in Economics, 2023
UCLA
BA in Economics, Russian, 2018
University of Pennsylvania
A formal model reveals how the information environment affects international races to implement a powerful, dangerous new military technology, which may cause a ‘‘disaster’’ affecting all states. States implementing the technology face a tradeoff between the safety of the technology and performance in the race. We study the role of information and uncertainty on the probability of a disaster.
We assess the impact of deep learning on the economy by estimating the idea production function for AI in two computer vision tasks that are considered key test-beds for deep learning and show that AI idea production is notably more capital-intensive than traditional R&D and suggests that AI-augmented R&D has the potential to speed up technological change and economic growth.
Using new data and a battery of causal inference methodologies, we verify earlier studies that show that market economic reforms did not have a significant impact on long-run growth. Instead, we show that variation in growth rates can be ascribed to rising oil and gas revenues and lower government spending, which have allowed slow reforming countries to converge with or surpass the growth rates of reform leaders.