CITP Seminar – The Reach of Fairness: From Algorithmic Justice to Experimental Design
In translating these principles into practice, the challenge of evaluating automated decision systems in deployment is examined. The talk highlights how experimental designs often simplify human decision-making, potentially biasing the understanding of the impacts of algorithmic interventions. Together, these perspectives underscore the need for both conceptual expansion and rigorous evaluation to ensure that algorithmic deployments align with societal fairness.
Bio: Lydia Liu joined Princeton University as an assistant professor in 2024. Her current research examines the theoretical foundations of machine learning and algorithmic decision-making, with a focus on societal impact and welfare.
Prior to joining Princeton she was a postdoctoral associate at Cornell University Computer Science in the Artificial Intelligence, Policy, and Practice (AIPP) initiative. Her work has be recognized with a Microsoft Ada Lovelace Fellowship, an Open Philanthropy AI Fellowship, an NUS Development Grant, and an ICML Best Paper Award.
She obtained a Ph.D. in Electrical Engineering and Computer Sciences from University of California, Berkeley and a B.S.E. in Operations Research and Financial Engineering at Princeton University.
In-person attendance is open to Princeton University faculty, staff and students.
This talk will be open to the public, at this link, via Zoom. It will be recorded and posted here, on the CITP YouTube channel, and on the Princeton University Media Central channel.
If you need an accommodation for a disability please contact Jean Butcher at butcher@princeton.edu at least one week before the event.
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