Federal Reserve Watchdog Warns AI and Machine Learning Could Perpetuate Lending Bias
The Federal Reserve’s top watchdog, Michael Barr, issued a warning about the potential for artificial intelligence (AI) and machine learning to perpetuate bias in lending practices. Speaking at the National Fair Housing Alliance’s national conference, Barr acknowledged the enormous potential of these technologies but also highlighted the risks involved. He emphasized that while AI tools could expand credit to more people at a relatively low cost, they could also exacerbate bias and inaccuracies in the data used to train the systems or make predictions.
To address concerns about appraisal discrimination in mortgage transactions, the Federal Reserve recently announced two policy initiatives. The first initiative involves implementing quality control standards in automated valuation models, where institutions engaging in certain credit decisions would need to adopt policies and practices to ensure the accuracy and integrity of automated estimates. The second initiative focuses on incorporating reconsiderations of value into the home appraisal process to mitigate the risk of improperly valuing real estate.
Barr highlighted the importance of homeownership as a means for families to build wealth and expressed full support for both policy initiatives. He emphasized that fair lending is synonymous with safe and sound lending, receiving applause from the audience.
The commitment to addressing automated systems that can cause harmful business practices was also reiterated by a quartet of federal agencies, including the Federal Trade Commission and the civil rights division at the Department of Justice. This commitment aims to crack down on algorithmic bias and ensure fair lending practices.
The National Fair Housing Alliance President and CEO, Lisa Rice, expressed excitement about Barr’s acknowledgement of algorithmic bias, stating, When have you ever heard a vice chair of the board of governors speak against algorithmic bias? I’m telling you, I’m excited.
The warning from the Federal Reserve Watchdog serves as a reminder of the potential downside of AI and machine learning in lending practices. While these technologies offer significant opportunities, they must be implemented with caution to avoid perpetuating bias and disparities. The proposed policy initiatives aim to address these concerns and promote fair lending practices, ultimately benefiting more individuals and families in their pursuit of homeownership.
As the debate surrounding the use of AI and machine learning continues, it remains crucial for regulators, financial institutions, and industry stakeholders to collaborate and find solutions that mitigate bias and ensure equitable access to credit. By doing so, they can harness the potential of these technologies to not only expand credit but also promote fair lending and eliminate disparities in the housing market.
