Reducing algorithmic bias in AI | Kumba Sennaar | TEDxBrandeisU
Автор: TEDx Talks
Загружено: 2024-05-08
Просмотров: 3058
The rapid proliferation of artificial intelligence (AI) applications can help us perform tasks faster, with greater accuracy and at reduced costs. However, these innovations can also present risks related to data privacy, data security and algorithmic bias. In this TEDx talk the speaker will discuss how each of us can contribute to a world where AI accelerates positive change in virtually every industry while bias, risk and harm are minimized. Kumba Sennaar is a PhD candidate in Social Policy at Brandeis University and founder of William Kelly Consulting. Her research interests include maternal health disparities and ethical use of Artificial Intelligence (AI) in healthcare. Sennaar earned an M.A. in Social Policy from Brandeis, M.S. in Biotechnology from Johns Hopkins University and a B.S. with honors from Rensselaer Polytechnic Institute, in Science, Technology & Society (STS). Her articles on applications of AI have been cited by consulting firms and by journals including the Boston University Law Review, Fordham Urban Law Journal and the Harvard Data Science Review. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx
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