Trump's latest AI czar has already resigned ⁠54%

By Julie Bort⁠55%

7/20/2026, 10:21:04 PM

BS Summary: This article contains 22 faulty reasoning types, including Post Hoc (False Cause), Availability Heuristic, and Unattributed Quote, with Negativity Bias as the most egregious example at 26.4% saturation with 137 hits. Analysis detected 1,220 faulty-reasoning hits from 518 analyzed words, generating a BS Score of 52.7% and a BS Rank of ⁠54% (9,498 of 20,515 articles). This article is worse (more manipulative) than 53.70% of the article peer group.

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. 
Article reasoning-pattern comparisonThis article: 5.6%Julie Bort: 4.1%TechCrunch: 3.0%Confirmation Bias5.6%This article: 0.0%Julie Bort: 2.7%TechCrunch: 1.4%Anchoring Bias0.0%This article: 19.7%Julie Bort: 7.5%TechCrunch: 3.4%Availability Heuristic19.7%This article: 13.3%Julie Bort: 2.4%TechCrunch: 1.1%Representativeness Heuristic13.3%This article: 0.0%Julie Bort: 1.2%TechCrunch: 0.6%Hindsight Bias0.0%This article: 0.0%Julie Bort: 3.9%TechCrunch: 2.5%Overconfidence Bias0.0%This article: 0.0%Julie Bort: 4.4%TechCrunch: 4.6%Framing Effect0.0%This article: 0.0%Julie Bort: 0.2%TechCrunch: 0.6%Loss Aversion0.0%This article: 5.6%Julie Bort: 1.2%TechCrunch: 0.6%Status Quo Bias5.6%This article: 0.0%Julie Bort: 0.1%TechCrunch: 0.2%Sunk Cost Effect0.0%This article: 0.0%Julie Bort: 4.2%TechCrunch: 5.0%Optimism Bias0.0%This article: 5.0%Julie Bort: 1.0%TechCrunch: 1.2%Pessimism Bias5.0%This article: 26.4%Julie Bort: 5.4%TechCrunch: 5.0%Negativity Bias26.4%This article: 0.0%Julie Bort: 3.0%TechCrunch: 2.1%Self-Serving Bias0.0%This article: 5.8%Julie Bort: 0.9%TechCrunch: 0.5%Fundamental Attribution Error5.8%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.1%Actor-Observer Bias0.0%This article: 0.0%Julie Bort: 0.1%TechCrunch: 0.5%In-Group Bias0.0%This article: 0.0%Julie Bort: 0.4%TechCrunch: 0.2%Out-Group Homogeneity Bias0.0%This article: 13.3%Julie Bort: 8.6%TechCrunch: 3.3%Halo Effect13.3%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.1%Horn Effect0.0%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.0%Dunning-Kruger Effect0.0%This article: 11.4%Julie Bort: 4.1%TechCrunch: 2.3%Recency Bias11.4%This article: 6.6%Julie Bort: 0.3%TechCrunch: 0.3%Primacy Effect6.6%This article: 0.0%Julie Bort: 0.1%TechCrunch: 0.1%Blind-Spot Bias0.0%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.2%Ad Hominem0.0%This article: 0.0%Julie Bort: 0.3%TechCrunch: 0.6%Straw Man0.0%This article: 8.5%Julie Bort: 7.9%TechCrunch: 4.3%Appeal to Authority8.5%This article: 13.9%Julie Bort: 1.5%TechCrunch: 1.7%False Dilemma13.9%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.6%Slippery Slope0.0%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.2%Circular Reasoning0.0%This article: 5.6%Julie Bort: 6.9%TechCrunch: 6.0%Hasty Generalization5.6%This article: 5.4%Julie Bort: 0.4%TechCrunch: 0.2%Red Herring5.4%This article: 0.0%Julie Bort: 3.8%TechCrunch: 1.2%Bandwagon0.0%This article: 5.4%Julie Bort: 2.0%TechCrunch: 2.2%Appeal to Emotion5.4%This article: 0.0%Julie Bort: 0.9%TechCrunch: 0.6%Begging the Question0.0%This article: 24.7%Julie Bort: 4.0%TechCrunch: 2.9%Post Hoc (False Cause)24.7%This article: 0.0%Julie Bort: 0.2%TechCrunch: 0.1%Tu Quoque0.0%This article: 1.4%Julie Bort: 0.8%TechCrunch: 0.5%Burden of Proof1.4%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.2%Appeal to Nature0.0%This article: 0.0%Julie Bort: 0.7%TechCrunch: 0.3%Composition/Division0.0%This article: 0.0%Julie Bort: 3.6%TechCrunch: 2.3%Anecdotal0.0%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.0%No True Scotsman0.0%This article: 12.4%Julie Bort: 3.4%TechCrunch: 2.0%Ambiguity (Equivocation)12.4%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Julie Bort: 0.3%TechCrunch: 0.2%Middle Ground0.0%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.0%Personal Incredulity0.0%This article: 0.0%Julie Bort: 0.1%TechCrunch: 0.1%Special Pleading0.0%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.1%Genetic Fallacy0.0%This article: 18.0%Julie Bort: 4.5%TechCrunch: 1.9%Unattributed Quote18.0%This article: 0.0%Julie Bort: 0.5%TechCrunch: 0.7%Quote-first Misdirection0.0%This article: 16.0%Julie Bort: 7.3%TechCrunch: 4.6%Biased Writer Voice16.0%This article: 6.6%Julie Bort: 0.8%TechCrunch: 0.8%Indoctrination6.6%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Julie Bort: 0.0%TechCrunch: 0.1%Politically Right Leaning Bias0.0%This article: 5.0%Julie Bort: 3.6%TechCrunch: 4.5%Attempt to Sell a Product or S…5.0%

518 words analyzed.

Speakers

10speakers64%attributed speech189writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 7 words • 100.0% coverageCenter for AI Standards and Innovation (CAISI) • 22 words • 0.0% coverageThe Washington Post • 26 words • 100.0% coverageWriter's voice • 30 words • 100.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 34 words • 100.0% coverageWriter's voice • 13 words • 0.0% coverageDavid Sacks • 25 words • 0.0% coverageDavid Sacks • 5 words • 0.0% coverageCenter for AI Standards and Innovation (CAISI) • 31 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageCommerce Department • 22 words • 100.0% coverageHoward Lutnick • 24 words • 100.0% coverageWhite House • 29 words • 0.0% coverageWhite House • 21 words • 0.0% coverageCNBC • 13 words • 0.0% coverageDemis Hassabis • 44 words • 0.0% coverageWriter's voice • 26 words • 100.0% coverageAxios • 13 words • 100.0% coverageDavid Sacks • 28 words • 100.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageTechCrunch • 26 words • 100.0% coverage
Selected voice

Demis Hassabis

100%flagged-word coverage
44 attributed words13% of attributed speech89% writer coverage
0%10.0%20.0%Indoctrination-18.0 ptsWriter: 18.0%Demis Hassabis: 0.0%0.0%Biased Writer Voice-17.5 ptsWriter: 17.5%Demis Hassabis: 0.0%0.0%Unattributed Quote-15.9 ptsWriter: 15.9%Demis Hassabis: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.