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The Implications of AI Bias & Approaches to Operationalize Fairness

Conference:  Transform X 2021

2021-10-07

Authors:   Nicol Turner Lee


Abstract

Join Nicol Turner-Lee, Senior Fellow at The Brookings Institution, as she explores the societal need for fair AI that is equitable to all. She describes the individual and enterprise consequences of bias in AI and the need for multi-disciplinary and multi-methodological approaches to preventing it. How does unintentional bias in AI occur? How do you self-regulate your AI algorithms, so they benefit everyone in the demographics you are trying to serve? How can the fields of data science, law, and sociology join forces to ensure that AI is unbiased? Join this session to hear a thoughtful and research-driven exploration about the risks, impacts, and approaches to mitigating unintended bias in AI.

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