Fed’s Barr highlights digital redlining risk resulting from AI tools

While artificial intelligence and machine learning have enormous potential, Federal Reserve Vice Chairman for Supervision Michael Barr today cautioned that “they also carry risks of violating fair lending laws and perpetuating the very disparities they have the potential to address.”

Among those risks is digital redlining in marketing that excludes majority-minority communities or minority applications, Barr noted. “Digital redlining may result if advertisers select their audiences based on a characteristic that is correlated with protected characteristics,” he said. “New technologies can also result in ‘reverse redlining,’ or steering in the advertisement of more expensive or otherwise inferior products to minority communities. These risks are amplified when a model is opaque and lacks a sufficient degree of explainability—the degree to which the bank can understand how data, variables, and other features inform the credit decisions.”

Barr added that regulators will evaluate through the supervisory process “whether firms have proper risk management and controls, including with respect to those new technologies.”