Artificial intelligence (AI) tools will not replace historians anytime soon, but AI tools are increasingly being used in researching economic history, providing both new methodologies and efficiencies for historians, economists, and data analysts. From text recognition to natural language processing, sentiment analysis, entity recognition and topic modeling, historians are finding novel applications for AI tools. These new methods are creating new efficiencies in the research methods and helping students of history uncover insights that might otherwise be hidden. This panel discussion with two leading economic historians, Louis Hyman and Matthew Jones, will touch on the ways historians are employing AI methods, the advantages and also the costs as AI empowers scholars to push the boundaries of what we know about the economic past, transforming both research methodologies and historical storytelling. 

Louis Hyman is a historian of work and business at the Agora Institute at Johns Hopkins University. He has published two books on the history of personal debt (Debtor Nation and Borrow), a history of how American work became so insecure (Temp), as well as other edited collections and articles. He is currently working on a history of e-commerce.  ​Originally from Baltimore, Hyman received a B.A. in history and mathematics from Columbia University. A former Fulbright scholar and McKinsey associate, he received his Ph.D. in American history from Harvard University.  He is a founding editor of the Columbia Studies in the History of U.S. Capitalism book series from Columbia University Press and the director of the History of Capitalism Summer Camp.  Louis enjoys talking to book clubs and organizations over Zoom or Skype.

Matthew L. Jones focuses on the history of recent information technologies and intelligence as well as the history of science and technology in early modern Europe. He received his A.B. and Ph.D. from Harvard (1994, 2000) and an M.Phil. from Cambridge, after which he taught at Columbia for twenty-three years. Along with Chris Wiggins, he is the author of How Data Happened, a history of the science, politics, and power of data, statistics, and machine learning from the 1800s to the present (W. W. Norton, 2023). He has published two books previously, The Good Life in the Scientific Revolution: Descartes, Pascal, Leibniz and the Cultivation of Virtue and Reckoning with Matter: Calculating, Innovation, and Thinking about Thinking from Pascal to Babbage (both with Chicago). He has received fellowships from the Mellon Foundation, the Guggenheim Foundation, the Sloan Foundation, and the National Science Foundation, and is currently a CIFAR fellow in the Future Flourishing(Link is external) project.