[Luojia Forum]Professor Thomas Sargent Discusses the Prospects and Challenges of Machine Learning in Economics

On November 30, Nobel laureate in economics in 2011, current Professor of Economics at New York University, Senior Research Fellow at the Hoover Institution at Stanford University, and a Fellow of the National Academy of Sciences and the American Academy of Arts and Sciences, Professor Thomas J. Sargent, visited Wuhan University as a guest speaker at the Luojia Forum.

Before the forum, President Zhang Pingwen met with Professor Sargent. President Zhang expressed sincere gratitude for Professor Sargent's special participation in Wuhan University's 130th-anniversary celebration activities. He hoped that Professor Sargent could engage in extensive and in-depth academic exchanges with Wuhan University faculty and students, contributing to the university's talent cultivation and scientific research. President Zhang and Professor Sargent delved into issues such as digital economy, big data research, and the application of mathematics in artificial intelligence.

Subsequently, Professor Sargent delivered an academic lecture titled "Promises and Limits of Machine Learning in Economics" to Wuhan University faculty and students. President Zhang Pingwen awarded Professor Sargent the Luojia Forum Commemorative Certificate. The forum was chaired by Professor Nie Jun, Dean of the School of Economics and Management.

Starting with the definition of human intelligence, Professor Sargent systematically discussed practical difficulties and solutions encountered by great figures such as Kepler, Galileo, and Darwin in their scientific exploration. Using this as a reference, he elucidated the broad prospects of artificial intelligence and machine learning as new statistical tools in various fields, including economic game theory, distributed computing, and dynamic programming. He argued that modern artificial intelligence and machine learning have effectively divided statistical methods into descriptive and structural models, using metaphors from von Neumann and Morgenstern to compare them to the work done by Kepler and Newton in physics. This classification effectively addressed the fundamental question of what parameters are in statistics.

During the Q&A session, Professor Sargent engaged in in-depth discussions with the faculty and students on topics such as the application of machine learning, the interpretability of estimated models, and the ethical risks involved in practical operations. Professor Sargent emphasized the importance of machine learning in economic research. Machine learning, as imperfect as it is now, remains an excellent research tool worth systematic learning by students.

This forum was one of the activities of Wuhan University's 130th-anniversary celebration and was jointly organized by the Institute of Humanities and Social Sciences and the School of Economics and Management of Wuhan University. Over two hundred faculty and students attended the forum.

It is worth noting that as a leader in the rational expectations school, Professor Sargent has made significant contributions to macroeconomics, dynamic economic theory, and time series analysis. He has authored fifteen works, including Rational Expectations Econometrics. His textbooks, such as Macroeconomic Theory and Recursive Macroeconomic Theory are exemplary teaching materials for graduate students in economics in Europe and the United States. He has published over two hundred papers in top international academic journals, with a profound academic influence and high academic prestige. In 2011, he and Professor Sims jointly received the Nobel Prize in Economics for their outstanding contributions to empirical research in macroeconomics.

(Photography: Jin Xin, Editing: Zhao Jifan)