About

Diag Davenport is a Presidential Postdoctoral Research Associate at the Princeton School of Public and International Affairs. His primary research identifies ways to shape the societal impact of artificial intelligence by examining the conditions governing people's interactions with these tools and the individual decision-making processes that follow. While algorithms and their deployment contexts can certainly amplify biased and badly-motivated decisions, he believes that leveraging insights about the psychology behind those processes will allow us to build better algorithms and policies that mitigate the role of biased motivations in socially and economically important settings.

Diag is a co-recipient of the 2023 Hillel Einhorn New Investigator Award from the Society of Judgment and Decision Making and his work received Honorable Mention for the 2023 Best Paper Award from the Behavioral Science and Policy Association. Diag’s work has been published in top journals such as Proceedings of the National Academy of Sciences and Nature Human Behavior. His work has also been featured in popular press venues such as Bloomberg, Boston Globe, Forbes, and The Telegraph.

Before joining Princeton, Diag earned his PhD in Behavioral Science (Economics track) from the University of Chicago Booth School of Business. Diag also has a master’s in Mathematics and Statistics from Georgetown and bachelor’s degrees in Economics and Management from Penn State. Prior to his PhD studies, Diag advised insurance and manufacturing executives on future litigation risks as a consultant at Bates White and built a variety of data products as a data scientist for the District of Columbia Superintendent of Education, the Federal Reserve Board, and a Covid-thwarted travel startup. During his PhD studies, he also operated an AI consulting firm that advised several startups on data strategy. Those clients have gone on to collectively raise over $20 million.