Trump’s latest AI czar has already resigned
The director role for the Center for AI Standards and Innovation (CAISI) has become a revolving door since David Sacks left his position as czar.
Chris Fall, the director of the Center for AI Standards and Innovation (CAISI), has resigned, the agency confirmed to multiple news outlets.
He was appointed just three months ago after the last appointee, Collin Burns, left in less than a week, The Washington Post reported at the time. Burns was reportedly “pushed out” of the job in April because he previously worked for Anthropic and the Trump administration had been battling with the company, sources told the Post.
No reason was given for Fall’s departure. Prior to leading CAISI, Fall was the director of the Department of Energy’s Office of Science during the first Trump administration and had been the acting director of the DOE’s Advanced Research Projects Agency-Energy. He worked in the DOE’s Office of Naval Research (ONR) prior to that.
Before Burns and Fall, the agency was led by venture capitalist David Sacks, whose title at the time was White House AI and crypto czar. Sacks stepped down in March.
CAISI, which operates under the National Institute of Standards and Technology, is the primary organization for developing technical standards and testing methods for AI models as well as assessing cybersecurity risks. Yet it was not the agency at the center of the most recent model-risk brouhaha.
That occurred in June when the U.S. Commerce Department invoked an obscure export control directive that effectively forced Anthropic to pull its Mythos and Fable models from the market. The ban was lifted by the end of the month , when Secretary of Commerce Howard Lutnick said he was satisfied with Anthropic’s safety plans.
Earlier this month, the White House also signed an executive order for a new AI safety oversight program called “Gold Eagle” that creates a clearinghouse for cybersecurity vulnerability coordination. A host of federal organizations were named as part of the program, including the Commerce Department and Department of Homeland Security. But, as CNBC pointed out, CAISI was not among the federal organizations mentioned.
Meanwhile, after Anthropic’s models were freed from the ban, Google DeepMind CEO Demis Hassabis began calling for the creation of an independent, industry-run standards body to regulate frontier AI modeled after FINRA — the same sort of mission that CAISI was formed to tackle.
Fall’s resignation also follows this weekend’s handwringing over Chinese AI lab Moonshot’s new version of its open model Kimi, which performed competitively against flagship frontier models. The administration was weighing efforts to somehow ban Chinese open models, Axios reported . This sparked immediate debate and outrage over the weekend, including from Sacks , who argued that regulations shouldn’t be used as a protectionism strategy for U.S. proprietary AI labs.
While CAISI has released a few reports on the capabilities of Chinese open-weight models Z.ai’s GLM-5.2 and DeepSeek V4 Pro, it hasn’t talked much about its processes for testing. (Open weight means these models can be publicly downloaded and run locally, but its training code and datasets are not available). Since July 9, TechCrunch has sent multiple inquiries to both the DoC and NIST about how its LLM evaluations work and has not received a response.
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Key takeaways
- The instability in CAISI's leadership may undermine the establishment of essential technical standards for AI.
- CAISI's absence from the "Gold Eagle" program indicates a potential fragmentation in AI regulation in the U.S.
- The call for an independent standards body may inspire similar initiatives in Brazil.
- Competition among AI models highlights the need for constant innovation in the tech sector.
- Brazil should observe global dynamics to position itself as a leader in AI regulation in Latin America.
Editorial analysis
The rapid succession of directors at the Center for AI Standards and Innovation (CAISI) reflects an environment of uncertainty and instability in AI governance in the United States, which could have global repercussions, including in Brazil. The lack of continuity in leadership may hinder the establishment of robust technical standards and the assessment of cybersecurity risks, both critical areas for the responsible development of AI. For the Brazilian tech sector, which seeks to integrate into the global AI market, monitoring the policies and guidelines emerging from this scenario is essential.
Moreover, the recent establishment of an AI safety oversight program by the White House, dubbed "Gold Eagle," without CAISI's involvement raises questions about the effectiveness and coordination among different government agencies. This could impact how Brazilian companies working with AI prepare to meet international regulations, especially if the U.S. adopts a fragmented approach to AI regulation.
Demis Hassabis's call for an independent, industry-run standards body suggests growing pressure for the private sector to take a more active role in defining norms for AI. This could inspire similar initiatives in Brazil, where collaboration among businesses, government, and academia is crucial for advancing technology ethically and safely. Brazil should observe these dynamics and consider how it can position itself as a leader in AI regulation in Latin America.
Finally, the fierce competition among AI models, as evidenced by the performance of Moonshot's Kimi model, underscores the need for constant innovation and adaptation in the sector. For Brazil, this means that companies must not only keep up with global trends but also invest in research and development to ensure they can compete in an increasingly saturated and demanding market.
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