On December 16, the same day Tabassi spoke at NeurIPS, six members of Congress signed a bipartisan open letter raising concern about the prospect of NIST enlisting private companies with little transparency. “We have learned that NIST intends to make grants or awards to outside organizations for extramural research,” they wrote. The letter warns that there does not appear to be any publicly available information about how those awards will be decided.
The lawmakers’ letter also claims that NIST is being rushed to define standards even though research into testing AI systems is at an early stage. As a result there is “significant disagreement” among AI experts over how to work on or even measure and define safety issues with the technology, it states. “The current state of the AI safety research field creates challenges for NIST as it navigates its leadership role on the issue,” the letter claims.
NIST spokesperson Jennifer Huergo confirmed that the agency had received the letter and said that it “will respond through the appropriate channels.”
NIST is making some moves that would increase transparency, including issuing a request for information on December 19, soliciting input from outside experts and companies on standards for evaluating and red-teaming AI models. It is unclear if this was a response to the letter sent by the members of Congress.
The concerns raised by lawmakers are shared by some AI experts who have spent years developing ways to probe AI systems. “As a nonpartisan scientific body, NIST is the best hope to cut through the hype and speculation around AI risk,” says Rumman Chowdhury, a data scientist and CEO of Parity Consulting who specializes in testing AI models for bias and other problems. “But in order to do their job well, they need more than mandates and well wishes.”
Yacine Jernite, machine learning and society lead at Hugging Face, a company that supports open source AI projects, says big tech has far more resources than the agency given a key role in implementing the White House’s ambitious AI plan. “NIST has done amazing work on helping manage the risks of AI, but the pressure to come up with immediate solutions for long-term problems makes their mission extremely difficult,” Jernite says. “They have significantly fewer resources than the companies developing the most visible AI systems.”
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