Michael Ekstrand, PhD

Ekstrand is an internationally recognized leader in transparency and fairness of the algorithms that drive artificial intelligence, search engines and recommender systems, such as those used by Netflix, YouTube, Amazon and Spotify. He was a co-author of one of the first position statements — from a professional organization of AI researchers — calling attention to the potential risks of artificial intelligence and the need for policy to ensure fairness, accountability and transparency.

His research strives to answer questions about what fairness and transparency look like when it comes to the algorithms that find and curate information online. Ekstrand has discussed his work and shared his expertise in news stories about the algorithms behind search engines, Twitter/X and ChatGPT.

Ekstrand has published and presented extensively on how people interact with recommendations, depending on how they are presented; how search engines could better tailor their results to meet the needs of users; and how to ensure recommendation and search results are fair to different users and creators. His research groups have worked to develop tools for understanding how people consume news and to provide teachers with access to a wider variety of information sources via a recommender program.

Ekstrand earned degrees from Iowa State University and the University of Minnesota and has previously served as an assistant professor of computer science at Texas State University and Boise State University, and from 2020-2023 served on the Executive Committee for the Association for Computing Machinery’s Conference on Fairness, Accountability, and Transparency.