On November 29, The United States House of Representatives Committee on Financial Services published their response to the request for information on financial institutions’ use of artificial intelligence (AI), including machine learning (ML).
As the Committee previously outlined, “any use of AI in the financial services industry must emphasize principles of transparency, enforceability, privacy and security, and fairness and equity, with strict scrutiny on financial institutions that exhibit algorithmic bias or engage in technological redlining.”
To understand and analyze the issues, the Committee launched a task force last Congress on AI which examined various topics, including:
How to reduce AI bias
The impact of AI on capital markets
AI usage by cloud computing providers
This Congress, the task force continued investigations on whether emerging technologies such as AI are serving the needs of consumers, investors, small businesses, and the American public, in particular:
how the use of human centred AI/ML can build equitable algorithms and address systemic racism and in housing and financial services
how financial institutions increasingly relied on AI to create and authenticate digital identities of clients
how governments, industry and civil society must build better AI ethical frameworks
The Committee highlighted racial bias concerns in AI/ML technology, citing that models have been found to be discriminatory with some algorithm exacerbating bias on protected groups.
As such, the Committee outlined the following guiding principles to AI regulation that must focus on :
Transparency and explainability
Oversight and enforceability
Safeguarding consumer privacy, including preventing cyberattacks from hackers, including foreign adversaries
Promoting fairness and equity in AI usage, proactively addressing algorithmic bias