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Employers increasingly rely on automated decision-making tools (ADMTs) for employee and recruiting decisions, a trend expected to continue amid federal AI regulatory rollbacks. Managing Directors Ling Ling Ang and Elizabeth Newlon explore the risk of litigation over alleged discriminatory bias in the decisions provided by ADMTs in their article "Automated Decision-Making Tools and the Potential for Discriminatory Bias: Labor and Employment, Fair Lending, and Beyond."
Dr. Ang and Dr. Newlon aim to clarify the uncertainties surrounding how discrimination claims based on ADMT bias will be demonstrated or refuted in court using statistical evidence. This article delves into the concept of algorithmic bias, limited US litigation and guidance related to bias in ADMTs, and approaches to auditing for algorithmic bias to mitigate the risk of litigation.
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