AI

Social Justice Best Paper Award

A paper co-authored by Heng Xu and Nan Zhang, “Fairness of Ratemaking for Catastrophe Insurance: Lessons from Machine Learning,” published at Information Systems Research, has been honored with the INFORMS...

Is AI Useful for Scientific Assessments?

On September 25, 2024, Dr. Heng Xu was invited to speak on “AI Landscape and Tools for Scientific Assessments” to the Committee to Advise the U.S. Global Change Research Program...

AI and State/Local Government Services and Equity

On August 22, 2024,Dr. Heng Xu moderated a discussion session titled “AI Peer-to-Peer Series: AI and State and Local Government Services and Equity,” organized by the National Academy of Sciences’...

Navigating the AI Landscape

On April 9, 2024, Dr. Heng Xu was invited, along with Rayid Ghani (Carnegie Mellon University) and Santiago Garces (Boston’s Chief Innovation Officer), to speak at an event titled “Navigating...

National Academies Board on Human-System Integration

Dr. Heng Xu will join leaders in science, engineering, and industry to serve on the Board on Human-Systems Integration, National Academies of Science, Engineering, and Medicine. The board was established...

Goal Orientation for Fair Machine Learning Algorithms

A key challenge facing the use of Machine Learning (ML) in organizational selection settings (e.g., the processing of loan or job applications) is the potential bias against (racial and gender)...

Nature Forum on Empowering Data as a New Asset

In an upcoming Nature Conference, Forum on Empowering Data as A New Asset, Heng Xu will join a panel of industry leaders, data economists and policy makers to discuss about...

Provost’s Distinguished Lecture

Professor Heng Xu will be featured in one of the two events in the Fall 2022 Provost’s Distinguished Lecture Series in American University. She will deliver a talk titled “What...

Change Can't Wait San Francisco Panel on AI Governance

Professor Heng Xu joined a panel of experts to discuss AI Governance in the Change Can’t Wait San Francisco event on March 11, 2022.

Working Paper - Fairness of Ratemaking for Catastrophe Insurance

We posted on SSRN a working paper by Nan Zhang and Heng Xu, addressing the problem of fair ratemaking in catastrophe insurance.

Fairness in AI Project

We gratefully acknowledge the National Science Foundation and Amazon for their generous support of our project “Using Machine Learning to Address Structural Bias in Personnel Selection”, which was selected as part of the NSF Program on Fairness in Artificial Intelligence...