Bias in the Bot: Promoting Fairness in Large Language Models

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Artificial intelligence is rapidly reshaping the economy with the promise of advancing human progress. Yet Mahzarin Banaji—Harvard psychologist and co-coiner of the term “implicit bias”—has found that large language models (LLMs) exhibit higher levels of bias than most human studies reveal. In turn, these deeply embedded LLM biases risk distorting human decision-making in domains as consequential as employment, healthcare, and lending.

Join Professor Banaji and Professor Kenji Yoshino, Chief Justice Earl Warren Professor of Constitutional Law and Director of the Meltzer Center for Diversity, Inclusion, and Belonging, for a timely conversation about the latest research into implicit bias in LLMs, and how individual users, organizational leaders, and policy-makers can shape artificial intelligence to promote fairness and flourishing. 

This event is part of the Meltzer Center for Diversity, Inclusion, and Belonging speaker series and is cosponsored by the Birnbaum Women’s Leadership Center. Visit our website for a list of our sponsors.

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Note on Accessibility: This virtual event requires an Internet connection and computer or smartphone. Live captioning is availabile for this event. For any questions and/or requests for accommodations, please email bao.dinh@nyu.edu 5-7 business days in advance of the event date. However, we will always do our best to meet an accommodation need when communicated.