Mortgage lenders, landlords, and others increasingly use AI models to decide who gets access to housing. These AI models can embed past discrimination and so perpetuate harmful bias in housing markets. In this lecture, Michael Akinwumi will describe algorithmic fairness techniques that can reduce bias in algorithmic housing-related decisions. He will further explain how existing fair housing laws can, in some instances, impede the use of such fairness techniques. Finally, he will propose legal and policy changes to make algorithmic fairness techniques permissible and so to better achieve the purposes of fair housing laws themselves.
Featuring Michael Akinwumi, Chief Responsible AI Officer at the National Fair Housing Alliance.
Негізгі бет Data Points Lecture - Reprogramming Equality: Paving the Way for Fair Housing with AI
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