US Treasury Secretary Janet Yellen raised significant concerns about the potential risks posed by artificial intelligence (AI) to the stability of the financial system.

Yellen expressed these concerns during a keynote address at an AI and financial stability conference on June 6. She emphasized the urgent need to address emerging risks and called for collaboration between the government and private sectors to develop solutions.

Yellen stated:

"The field of AI is evolving rapidly. There is much work ahead of us."

While acknowledging AI's benefits in the financial sector, such as improved fraud detection and enhanced customer service through chatbots, Yellen and other experts cautioned about the deeper integration of AI potentially leading to increased risks. These risks include AI being exploited in scams or manipulating markets through misinformation.

Yellen highlighted:

"Errors or inadequate data could also perpetuate or introduce new biases into financial decision-making."

She pointed out concerns about the complexity of AI models, deficiencies in current risk management frameworks, and the widespread reliance on a limited number of models by numerous market participants.

The Treasury Department has issued a request for information to gather insights from stakeholders on the uses, opportunities, and risks of AI in financial services. This initiative aims to inform future policymaking by incorporating expert opinions and industry practices.

Yellen emphasized:

"The significant opportunities and risks associated with AI use in financial firms have elevated this issue to the top of the Treasury's and the Financial Stability Oversight Council's agendas."

Yellen's remarks come amid broader governmental scrutiny of AI and the tech companies behind it. The Department of Justice is reportedly preparing to investigate several tech giants, including Nvidia and Microsoft, over concerns related to antitrust and competition in the AI sector.

US antitrust enforcer Jonathan Kanter announced plans to scrutinize the AI sector due to concerns about potential monopolies, particularly focusing on computing power, data for training large language models (LLMs), cloud services, engineering talent, and hardware.

Kanter stressed the need for timely regulatory action to prevent dominant tech firms from monopolizing the AI market, citing the current scarcity of graphics processing units (GPUs) crucial for training LLMs, which has led to increased competition for chip allocation.