58 min
Fairness In Machine Learning and AI, with Gal Yona and Yafit Lev-Aretz Unsupervised
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- Technology
AI and ML algorithms are becoming increasingly popular, being implemented in finance, health and law enforcement systems. Mistakes these algorithms can make can have tremendous impact on people’s lives, leading to many ethical and legal questions; how do we define fairness in this context? On what personal rights do these algorithms affect? How can people appeal decisions made by algorithms? These questions, in turn, pose computational challenges, like improving the explainability of algorithms and enforcing algorithmic fairness toward minority groups. In this episode we talk to Gal Yona, from Weitzmann institute, and Yafit Lev-Aretz, from City University of New York. Together they provide us with an introduction to the hot topic of fairness in AI, from computational and legal perspective.
AI and ML algorithms are becoming increasingly popular, being implemented in finance, health and law enforcement systems. Mistakes these algorithms can make can have tremendous impact on people’s lives, leading to many ethical and legal questions; how do we define fairness in this context? On what personal rights do these algorithms affect? How can people appeal decisions made by algorithms? These questions, in turn, pose computational challenges, like improving the explainability of algorithms and enforcing algorithmic fairness toward minority groups. In this episode we talk to Gal Yona, from Weitzmann institute, and Yafit Lev-Aretz, from City University of New York. Together they provide us with an introduction to the hot topic of fairness in AI, from computational and legal perspective.
58 min