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A Deep Dive Into the Federal Agencies' Request for Information on Artificial Intelligence, With Special Guest Nicholas Schmidt, Chief Executive Officer, SolasAI
After discussing the current state of the regulators’ knowledge about artificial intelligence and machine learning (ML) in underwriting models, we examine the regulators’ key areas of focus for ML models (explainability/accuracy in adverse action notices, potential hidden bias, testing for disparate impact), discuss how to test for and counteract disparate impact and how to search for less discriminatory alternatives in ML model development, and consider regulators’ possible next steps.
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By Ballard Spahr LLP
4.9
4545 ratings
After discussing the current state of the regulators’ knowledge about artificial intelligence and machine learning (ML) in underwriting models, we examine the regulators’ key areas of focus for ML models (explainability/accuracy in adverse action notices, potential hidden bias, testing for disparate impact), discuss how to test for and counteract disparate impact and how to search for less discriminatory alternatives in ML model development, and consider regulators’ possible next steps.
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