Vox50%

The AI industry just won a race  but lost the war 40%

By Eric Levitz27%

6/25/2026, 3:00:00 AM

BS Summary: This article contains 31 faulty reasoning types, including Confirmation Bias, Unattributed Quote, and Post Hoc (False Cause), with Biased Writer Voice as the most egregious example at 33.9% saturation with 410 hits. Analysis detected 2,845 faulty-reasoning hits from 1,208 analyzed words, generating a BS Score of 45% and a BS Rank of 40% (13,207 of 21,887 articles). This article is better (less manipulative) than 60.30% of the article peer group.

New York’s congressional primaries on Tuesday were supposed to be the moment AI’s top backers definitively proved they could bend US politics to their will. 
Instead, they left behind a muddy stalemate that only raises more questions about whether their spending can keep pace with an anti-AI backlash. 
The stage for the battle was set last year, when some of America’s leading tech investors launched a new, $100 million super PAC dedicated to electing candidates who were “aligned with the pro-AI agenda” and defeating those who weren’t. 
Months later, this group  dubbed Leading the Future (LTF)  named its first target: New York Assembly member Alex Bores. 
Bores had been the chief sponsor of the Empire State’s “RAISE Act,” which required developers of frontier AI models to follow various safety protocols or face steep fines. 
LTF fiercely opposed that bill. 
Thus, when Bores launched a congressional run, the super PAC sought to teach him  and his fellow Democrats  a lesson: Purse sweeping AI regulations and your next campaign will drown in a flood of opposition spending. 
At first glance, it may look like LTF just achieved that objective. 
Bores lost his bid on Tuesday night to represent New York’s 12th District. 
Headlines deemed the race a victory for “Big Tech.” 
But appearances can be deceiving. 
In truth, Silicon Valley’s libertarians are losing the fight over AI regulation  and the NY-12 race only underscores this reality. 
Bores lost. 
So did his enemies. 
Contrary to LTF’s hopes, Bores’s loss is unlikely to dissuade Democrats from backing far-reaching regulations on AI, for at least four reasons: 
First, the race’s winner, Assembly member Micah Lasher, is about as hostile to LTF’s vision as Bores was. 
Lasher co-sponsored the RAISE Act and campaigned on pausing data center construction nationwide, launching antitrust investigations into the major AI labs, protecting artists from “AI-driven copyright infringement,” prioritizing organized labor’s interests in debates over AI deployment, and myriad other regulatory constraints on the technology. 
In his victory speech, Lasher directly addressed the AI companies who took an “unusual interest” in the race, saying he “won’t be taking my cues from either of you when it comes to protecting our kids, our jobs and our families.” 
Simply put, if the tech industry wants to convince Democrats that backing strict AI regulations is politically self-defeating, they’ll need better evidence than a race won by…a Democrat who backs strict AI regulations. 
Second, it’s far from clear that Bores’s candidacy was actually hurt by industry opposition. 
As my former Vox colleague Kelsey Piper notes at The Argument, when LTF announced it was targeting Bores, betting markets gave him only a 10 percent chance of victory, placing him behind both Lasher and Kennedy scion Jack Schlossberg. 
Bores ultimately came in a close second, trailing Lasher by only 4 percentage points (or about 4,000 votes). 
It’s plausible that LTF unintentionally aided Bores’s rise to contention by validating his bonafides as the bane of Big Tech. 
Certainly, that identity earned the assembly member abundant media coverage. 
“For voters, tech billionaires spending millions to beat a state legislator wasn’t a flex; it was a tell,” Jesse Ferguson, a Democratic strategist who advised the Bores campaign, told me. 
Third  and related  the race ended up becoming a fight between AI companies, not just about them. 
Bores’s candidacy was not solely powered by a grassroots backlash to industry meddling. 
Rather, he was himself the recipient of massive Silicon Valley donations, albeit from the segment of the tech industry that worries about AI safety. 
Anthropic, the maker of the cha6bot Claude, was an enthusiastic supporter of the RAISE Act. 
And when LTF came for that law’s chief sponsor, the AI giant’s super PAC rallied to his support, supplying Bores with at least $11 million in outside funding. 
The crypto billionaire Chris Larsen, meanwhile, tossed another $19 million Bores’s way. 
Importantly, this flood of financing was a reaction to LTF’s intervention. 
In other words, by targeting Bores, the super PAC arguably made it easier for him to raise money  and highlighted the existence of a pro-regulation, tech industry donor network. 
It is hard to see how this will make Democrats more afraid to meddle with AI. 
Finally, Lasher’s victory probably didn’t have that much to do with artificial intelligence, one way or another. 
Lasher has been involved in New York politics for about a quarter century longer than Bores has, and boasts personal ties to Michael Bloomberg, Kathy Hochul, and other power players in the state’s Democratic Party. 
He was the race’s favorite for more or less the entirety of the race. 
Therefore, even if Lasher favored light-touch AI regulation, his narrow victory over Bores wouldn’t prove much. 
Given his actual positions on AI, his win does nothing to advance LTF’s argument. 
The push for AI regulation is coming from inside the (White) House 
Meanwhile, since Leading the Future launched last year, the national political climate has turned sharply against them. 
In a recent Fox News poll, 80 percent of respondents said they favored regulating AI to protect public interests, even if doing so slows innovation. 
Other surveys show a large majority of Americans opposing the construction of new data centers in their areas. 
By itself, public opinion might not be an insuperable obstacle to Big Tech libertarians’ agenda. 
Voters are increasingly skeptical of AI, but still don’t typically consider it a top priority. 
Yet the national security state is also turning against laissez-faire in the AI sector. 
And its will is harder to ignore. 
Amid growing concerns about AI’s capacity to aid cybercrime, the White House released an executive order earlier this month encouraging labs to seek the government’s approval before releasing new models. 
Weeks later, the Trump administration took the extraordinary step of essentially ordering Anthropic to remove its Fable model from the market, on national security grounds. 
This represented a more radical and capricious government intrusion into the AI industry than Bores’s signature law ever contemplated. 
Leading the Future knows that the ground has shifted beneath its feet. 
When it first announced its targeting of Bores, it lambasted the RAISE Act as a “clear example of the patchwork, uninformed, and bureaucratic state laws that would slow American progress and open the door for China to win the global race for AI leadership.” 
Last month, however, the super PAC announced that it actually supported the RAISE Act, as the law “gets the combination of innovation and safety right.” 
LTF reconciled these positions by insisting that, while Bores’s initial draft of the legislation was ruinous, the final version was excellent. 
This is unconvincing. 
It’s true that the RAISE Act got watered down before enactment. 
But the idea that these changes were large enough to transform the bill from an act of catastrophic national sabotage  into a model of pro-innovation lawmaking  is implausible. 
And LTF’s supposed support for the measure is belied by the months it spent vigorously lobbying the federal government to preempt New York’s law. 
In reality, the group has simply retreated in the face of shifting political winds. 
Silicon Valley’s proponents of light-touch AI regulation are losing. 
And Bores’s loss did nothing to change that. 
Article reasoning-pattern comparisonThis article: 18.9%Eric Levitz: 4.3%Vox: 4.5%Confirmation Bias18.9%This article: 0.0%Eric Levitz: 0.9%Vox: 0.5%Anchoring Bias0.0%This article: 9.7%Eric Levitz: 2.7%Vox: 3.0%Availability Heuristic9.7%This article: 5.2%Eric Levitz: 0.8%Vox: 1.2%Representativeness Heuristic5.2%This article: 3.1%Eric Levitz: 0.4%Vox: 1.4%Hindsight Bias3.1%This article: 0.0%Eric Levitz: 3.1%Vox: 2.2%Overconfidence Bias0.0%This article: 6.8%Eric Levitz: 7.1%Vox: 5.9%Framing Effect6.8%This article: 0.0%Eric Levitz: 0.3%Vox: 0.4%Loss Aversion0.0%This article: 0.0%Eric Levitz: 0.5%Vox: 0.4%Status Quo Bias0.0%This article: 4.5%Eric Levitz: 0.2%Vox: 0.2%Sunk Cost Effect4.5%This article: 4.4%Eric Levitz: 1.6%Vox: 2.0%Optimism Bias4.4%This article: 7.9%Eric Levitz: 2.4%Vox: 2.3%Pessimism Bias7.9%This article: 16.2%Eric Levitz: 2.4%Vox: 6.7%Negativity Bias16.2%This article: 6.0%Eric Levitz: 0.8%Vox: 0.8%Self-Serving Bias6.0%This article: 4.1%Eric Levitz: 0.7%Vox: 1.1%Fundamental Attribution Error4.1%This article: 0.0%Eric Levitz: 0.2%Vox: 0.2%Actor-Observer Bias0.0%This article: 0.4%Eric Levitz: 0.6%Vox: 1.3%In-Group Bias0.4%This article: 0.0%Eric Levitz: 0.7%Vox: 0.6%Out-Group Homogeneity Bias0.0%This article: 0.0%Eric Levitz: 0.6%Vox: 1.2%Halo Effect0.0%This article: 0.0%Eric Levitz: 0.1%Vox: 0.1%Horn Effect0.0%This article: 0.0%Eric Levitz: 0.0%Vox: 0.0%Dunning-Kruger Effect0.0%This article: 3.5%Eric Levitz: 1.7%Vox: 1.3%Recency Bias3.5%This article: 1.0%Eric Levitz: 0.2%Vox: 0.3%Primacy Effect1.0%This article: 1.2%Eric Levitz: 0.1%Vox: 0.1%Blind-Spot Bias1.2%This article: 0.0%Eric Levitz: 0.3%Vox: 1.1%Ad Hominem0.0%This article: 0.0%Eric Levitz: 0.9%Vox: 0.8%Straw Man0.0%This article: 9.1%Eric Levitz: 2.6%Vox: 3.2%Appeal to Authority9.1%This article: 6.3%Eric Levitz: 3.5%Vox: 2.0%False Dilemma6.3%This article: 0.0%Eric Levitz: 1.3%Vox: 1.6%Slippery Slope0.0%This article: 0.0%Eric Levitz: 0.2%Vox: 0.1%Circular Reasoning0.0%This article: 11.6%Eric Levitz: 4.8%Vox: 6.2%Hasty Generalization11.6%This article: 0.0%Eric Levitz: 0.1%Vox: 0.2%Red Herring0.0%This article: 0.0%Eric Levitz: 0.2%Vox: 0.5%Bandwagon0.0%This article: 2.1%Eric Levitz: 2.7%Vox: 3.9%Appeal to Emotion2.1%This article: 3.5%Eric Levitz: 1.0%Vox: 0.9%Begging the Question3.5%This article: 17.7%Eric Levitz: 3.5%Vox: 3.3%Post Hoc (False Cause)17.7%This article: 0.0%Eric Levitz: 0.4%Vox: 0.3%Tu Quoque0.0%This article: 5.9%Eric Levitz: 0.3%Vox: 0.5%Burden of Proof5.9%This article: 0.0%Eric Levitz: 0.1%Vox: 0.2%Appeal to Nature0.0%This article: 0.0%Eric Levitz: 0.3%Vox: 0.4%Composition/Division0.0%This article: 9.1%Eric Levitz: 1.9%Vox: 2.2%Anecdotal9.1%This article: 1.5%Eric Levitz: 0.1%Vox: 0.2%No True Scotsman1.5%This article: 6.2%Eric Levitz: 1.5%Vox: 1.6%Ambiguity (Equivocation)6.2%This article: 0.0%Eric Levitz: 0.0%Vox: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Eric Levitz: 0.0%Vox: 0.1%Middle Ground0.0%This article: 0.0%Eric Levitz: 0.0%Vox: 0.1%Personal Incredulity0.0%This article: 4.2%Eric Levitz: 0.3%Vox: 0.1%Special Pleading4.2%This article: 0.0%Eric Levitz: 0.0%Vox: 0.3%Genetic Fallacy0.0%This article: 18.0%Eric Levitz: 2.5%Vox: 1.8%Unattributed Quote18.0%This article: 4.6%Eric Levitz: 0.9%Vox: 0.9%Quote-first Misdirection4.6%This article: 33.9%Eric Levitz: 5.4%Vox: 8.8%Biased Writer Voice33.9%This article: 4.8%Eric Levitz: 1.0%Vox: 1.6%Indoctrination4.8%This article: 0.0%Eric Levitz: 0.6%Vox: 2.7%Politically Left Leaning Bias0.0%This article: 4.1%Eric Levitz: 1.3%Vox: 0.3%Politically Right Leaning Bias4.1%This article: 0.0%Eric Levitz: 0.3%Vox: 0.9%Attempt to Sell a Product or S…0.0%

1208 words analyzed.

Speakers

4speakers15%attributed speech1,024writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 12 words • 100.0% coverageWriter's voice • 25 words • 100.0% coverageWriter's voice • 23 words • 100.0% coverageWriter's voice • 39 words • 100.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageLeading the Future (LTF) • 5 words • 100.0% coverageWriter's voice • 38 words • 100.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 9 words • 100.0% coverageWriter's voice • 5 words • 100.0% coverageWriter's voice • 21 words • 100.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 4 words • 100.0% coverageWriter's voice • 22 words • 100.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 44 words • 0.0% coverageMicah Lasher • 41 words • 100.0% coverageWriter's voice • 33 words • 100.0% coverageWriter's voice • 14 words • 0.0% coverageKelsey Piper • 39 words • 100.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageJesse Ferguson • 30 words • 100.0% coverageWriter's voice • 19 words • 100.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 28 words • 0.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 16 words • 100.0% coverageWriter's voice • 17 words • 100.0% coverageWriter's voice • 35 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 14 words • 100.0% coverageWriter's voice • 12 words • 100.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 25 words • 100.0% coverageWriter's voice • 18 words • 100.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 7 words • 100.0% coverageWriter's voice • 30 words • 0.0% coverageWriter's voice • 25 words • 100.0% coverageWriter's voice • 19 words • 100.0% coverageWriter's voice • 12 words • 100.0% coverageLeading the Future (LTF) • 44 words • 100.0% coverageLeading the Future (LTF) • 25 words • 100.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 3 words • 100.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 30 words • 100.0% coverageWriter's voice • 24 words • 100.0% coverageWriter's voice • 14 words • 100.0% coverageWriter's voice • 9 words • 100.0% coverageWriter's voice • 8 words • 100.0% coverage
Selected voice

Micah Lasher

100%flagged-word coverage
41 attributed words22% of attributed speech82% writer coverage
0%50.0%100.0%Unattributed Quote+96.2 ptsWriter: 3.8%Micah Lasher: 100.0%100.0%Biased Writer Voice-39.6 ptsWriter: 39.6%Micah Lasher: 0.0%0.0%Indoctrination-5.7 ptsWriter: 5.7%Micah Lasher: 0.0%0.0%Politically Right Leaning -4.9 ptsWriter: 4.9%Micah Lasher: 0.0%0.0%Quote-first Misdirection-1.2 ptsWriter: 1.2%Micah Lasher: 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.