FPF Submits Written Statement to the U.S. House Committee on Financial Services Task Force on AI
This week, Future of Privacy Forum (FPF) Senior Counsel and Director of AI & Ethics Brenda Leong submitted a written statement on the use of artificial intelligence and machine learning-based applications in financial products and services. Addressed to the House Committee on Financial Services Task Force on Artificial Intelligence, the statement explores how to protect AI and ML-based financial systems from the impact of undesired or unintended bias.
“Financial services organizations have the responsibility, both legally and ethically, to treat their customers, whether other businesses or individuals, fairly and equally,” wrote Leong. “As more players in this industry employ AI systems in more use cases, it is incumbent on them to ensure that their algorithms are fair and explainable.”
In the statement, Leong describes beneficial ways that financial institutions are currently using AI, such as combating fraud or extending credit to traditionally underserved individuals. She also identifies a few factors that can present fairness and equity concerns that are unique to or heightened by processing within an AI or ML-based system; and identifies the technical, policy, regulatory and legislative actions that can help mitigate risk and bias from the use of these systems.
“While ML and AI are technologies thought of as completely ‘other’ from human thinking, they are so far still always based on algorithms and models created by people,” wrote Leong. “Thus, these algorithms are prone to incorporating the biases of their designers, as well as the biases of the systems they’re designed to serve, because the only data available to train them already reflects decades or even centuries of inequality.”
She prompts legislators to take caution when taking new action to legislate AI, since existing laws and regulations already apply, including legislation protecting consumers from unfair or misleading trade practices, labor and employment laws, applicable privacy laws, and the entire regulatory structure around financial services.
The statement was submitted for the record of the Equitable Algorithms: Examining Ways to Reduce AI Bias in Financial Services hearing held by the Task Force on Artificial Intelligence on February 12.
