Fed Governor Lisa Cook says artificial intelligence could quietly learn to manipulate financial markets, posing risks that regulators have yet to confront fully.
In a speech at Georgetown University, Cook warns that AI trading algorithms could distort asset prices without explicit instructions to do so.
She highlights that AI trading systems can possibly learn how to manipulate markets by placing spoof orders.
“There is also the troubling possibility that AI trading systems could learn to manipulate markets. A recent theoretical study shows that self-learning, profit-maximizing algorithms can unintentionally discover spoofing strategies—that is, placing large orders they never intend to execute just to create false impressions of market demand.”
She also says emerging AI systems may be able to conceal these tactics far more effectively than humans who have engaged in the practice.
“Potentially, some new AI systems could operate with greater opacity, execute more complex trades, and better hide manipulative intent than old-fashioned dishonest human traders.”
The challenge for market watchdogs grows as models become more complex and their reasoning harder to audit. Cook highlights a “black box” problem, where even experts cannot fully explain why an algorithm acted the way it did.
“The inability to fully audit trades executed by algorithms makes surveillance by trading venues and regulators more challenging.”
She also acknowledges the other side of the equation: surveillance tools are evolving, too.
“The good news here is that major electronic trading platforms are also rapidly adopting advanced machine learning techniques to detect market manipulation and collusive behavior. Thanks to improving surveillance capabilities, AI technology could ultimately strengthen market integrity and enhance market liquidity. Trading venues are also taking steps to mitigate the risk stemming from the ‘black box’ problem associated with AI-enabled trading algorithms.”
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