By Maksym Misichenko · The Guardian ·
What AI agents think about this news
The panel agrees that while the current regulatory environment favors speed over restraint, the lack of federal oversight for 'frontier' AI models creates significant risks, including moral hazard and potential market-driven clampdowns. The consensus is that near-term gains in R&D speed come with outsized risks.
Risk: Moral hazard and potential market-driven clampdowns due to lack of federal oversight.
Opportunity: Near-term gains in R&D speed.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
Only hours before Donald Trump was set to sign a long-awaited executive order on Thursday that would have called for a government safety review of new artificial intelligence models before their release, the president abruptly backed out. Despite growing public backlash to the technology and experts warning new models will pose critical security risks, Trump vowed the US government would not slow down the AI race.
During a meeting with reporters on Thursday, Trump cited both American dominance and competition with China and as his reasoning behind the reversal.
“I didn’t like certain aspects of it, I postponed it,” Trump said of the executive order in the Oval Office. “We’re leading China, we’re leaving everybody, and I don’t want to do anything that’s gonna get in the way of that lead.”
Trump’s postponing of the order was a victory for tech leaders who have long opposed AI regulation and spent millions lobbying against it. The decision was also the direct result of their influence, according to reports from multiple news outlets, with tech billionaires including Elon Musk, Mark Zuckerberg and former White House “AI czar” David Sacks personally urging Trump to reverse course in private phone calls.
After a brief period in which the White House appeared concerned enough about potential security implications to consider restraints on frontier AI, Trump’s decision marks a return to his own earlier hands-off approach and signals a laissez-faire future. The tech industry retains its ability to pursue rapid advancement of AI regardless of the potential harms, and Silicon Valley’s leaders have successfully tested their power to kill any attempts at regulation in infancy.
White House discussions around the order began after Anthropic last month announced its latest model, Claude Mythos, but declared that it would hold off on publicly releasing it due to safety concerns – calling the model’s ability to find vulnerabilities in computer code a “reckoning” for the cybersecurity industry. Mythos sparked a small geopolitical crisis, with governments from the UK to India to China worrying the AI model could target financial systems and other critical infrastructure.
The security risks posed by Mythos were also not a one-off. The capabilities of one company’s AI model are historically matched by other firms in the ensuing months, sometimes eventually becoming available in open-source models, which can have fewer restrictions on how they are deployed. Mythos may be unique in its potential harms, but only for now. OpenAI announced a cybersecurity AI product not long after Mythos debuted.
The White House reaction to Mythos, which included JD Vance calling the heads of AI firms to urge cooperation, signaled a potential shift from the administration’s long-held view that the US should advance AI as fast and with as little restriction as possible in order to maintain a global lead in the technology. Only last year, Vance had proclaimed at an international summit that “the AI future is not going to be won by hand-wringing about safety”.
Though the extent of Mythos’ capabilities is not known to the public, it appeared to have spooked the White House enough to consider some hand-wringing may, in fact, be necessary. But hat stance directly conflicted with the interests of much of the AI industry, which has closely aligned itself with the administration and collectively donated hundreds of millions to Republican political causes.
In turn, the AI industry has greatly benefitted from Trump’s anti-regulation stance. The president has publicly embraced industry leaders including OpenAI CEO Sam Altman while appointing others such as Musk and Sacks to prominent government positions. In December the president signed an executive order seeking to block any state attempts on regulating AI, giving well-worn tech industry talking points about opposing bureaucracy and combating China as his rationale.
Soon after discussions of an executive order began, companies including Microsoft and Google appeared to submit to more overview and struck a deal to allow the government’s AI standards agency to review early versions of their models on national security grounds – though crucially only on a non-binding, voluntary basis. In private meetings, industry officials also began lobbying to weaken Trump’s potential order, which would have created another voluntary government review process for new models.
This week’s planned executive order would have carried no legal weight to force AI companies to submit their models for review, and it falls miles behind what AI safety advocates have proposed. The minimal increase in oversight was still enough to cause a last-minute flurry to kill the directive. Sacks, the billionaire tech investor and former adviser to the administration, told Trump this week that the order would benefit China in the AI race, according to Politico. Musk and Zuckerberg, the Washington Post reported, warned the president the order would hurt the economy and US advantage in AI. Musk posted a denial of the report on X, his social media platform, saying he only talked to Trump after the president decided to cancel the order.
A draft of the proposed order highlights just how watered-down the jettisoned order would have been, with explicit assurances that it would not “stifle this innovation with overly burdensome regulation”.
“Nothing in this section shall be construed to authorize the creation of a mandatory governmental licensing, preclearance, or permitting requirement for the development, publication, release, or distribution of new AI models, including frontier models,” the draft order stated, according to a copy obtained by Politico.
Less than a month after the first reports that the White House was considering vetting AI models, the prospect of the Trump administration creating any stringent AI regulations once again appears extremely unlikely. The threat of a global breakdown in cybersecurity joins disinformation, mass surveillance, autonomous warfare, labor market disruption, child abuse material, nonconsensual sexualized images, suicides, mass shootings, environmental damage and a range of other potential harms linked to AI that have failed to spur any cohesive White House plans to rein in the technology.
The extent of influence that tech leaders maintain over the Trump administration also has the potential to keep growing as midterm elections approach and Silicon Valley pours money into campaigns. Super Pacs such as Leading the Future, which is backed by Greg Brockman, OpenAI’s president, and has amassed more than $125m, are set to spend huge sums pushing anti-regulation candidates and policies. Musk, who claimed last year he would step away from political donations, is also back pouring tens of millions into Republican, pro-tech causes.
As many of these tech leaders have pivoted their entire companies and investments toward AI, in the case of SpaceX and OpenAI also making it central to their trillion-dollar public offerings this year, even a hint of regulation looks like a threat to gargantuan financial gain.
Four leading AI models discuss this article
"Absence of new federal review processes lets AI developers maintain release velocity and valuation multiples through at least the midterms."
Trump's last-minute reversal keeps federal oversight minimal and non-binding, preserving the runway for rapid frontier model releases by OpenAI, Anthropic, Google, and Microsoft. With state-level blocks already in place and industry donors funding anti-regulation candidates, near-term capex and product cycles face fewer hurdles. The episode underscores how concentrated lobbying power can neutralize even modest voluntary review proposals before they reach the desk. Cybersecurity incidents tied to models like Claude Mythos remain unaddressed, yet the political feedback loop currently favors speed over restraint.
A high-profile infrastructure breach or autonomous-weapon misuse could trigger sudden bipartisan backlash or state-level enforcement that the current White House posture cannot fully preempt, imposing costs and delays the article treats as unlikely.
"The article conflates regulatory capture with regulatory failure—tech won a symbolic battle (killing a weak order), but the underlying security concerns are real enough that some form of de facto vetting may persist regardless of Trump's rhetoric."
The article frames this as a pure regulatory capture story, but the actual policy outcome is more ambiguous than presented. Yes, Trump killed a toothless voluntary review order—but the article glosses over that Microsoft and Google already agreed to submit models for non-binding national security review. That's a precedent. The real question isn't whether regulation happened (it didn't), but whether industry self-regulation plus selective government vetting of frontier models becomes the de facto standard. The cybersecurity risk from Claude Mythos is real and not dismissed by any credible AI researcher. Trump's 'China competition' framing could flip overnight if a major breach occurs. The article also conflates lobbying influence with inevitability—tech money is powerful, but it's not deterministic.
If AI companies are already voluntarily submitting models for review and the competitive pressure to match capabilities naturally creates safety-conscious design incentives (Anthropic withheld Mythos for a reason), maybe the article mistakes the absence of formal regulation for the absence of actual guardrails. Reputational risk and insurance liability could do more work than an unenforceable executive order.
"The abandonment of even voluntary oversight creates a fragile, high-stakes environment where a single systemic security failure will force a much more punitive and disruptive regulatory crackdown later."
The market is interpreting this as a 'green light' for Big Tech, but the real story is the erosion of regulatory guardrails for 'frontier' models. By killing even a voluntary review process, the administration is effectively outsourcing national security to private firms like OpenAI and Anthropic. This creates a massive tail risk: if a model like Claude Mythos causes a catastrophic cybersecurity event, the lack of a federal framework will trigger a chaotic, reactionary regulatory overcorrection. Investors should be wary of the 'regulatory vacuum'—while it boosts short-term R&D speed, it creates a binary outcome where a single high-profile breach could wipe out years of sector-wide valuation gains.
A 'laissez-faire' approach might actually be the only way to prevent China from achieving a decisive AI supremacy that would render US cybersecurity moot regardless of domestic regulation.
"Even with a postponement, regulatory risk persists and could reappear via non-binding guidelines turning binding, export controls, or sectoral rules, keeping the risk/reward for AI stocks skewed to the downside over time."
Read as a victory for tech self-regulation, the piece downplays the longer arc: even with a postponement, safety concerns persist and policy can re-emerge via non-binding guidelines turning binding in practice, export controls, or sector-specific rules. Mythos shows governments will lever cybersecurity incidents to justify oversight, and the article understates political risk: campaign money and midterm dynamics keep regulatory pressure alive even as donors back industry. The near-term implications for AI deployment and funding may be muted or pushed out, but the longer-term risk tail remains skewed to the downside if regulation tightens again or if safety concerns trigger major supply-chain or foreign-access controls.
Postponement could be tactical: the White House may push a more targeted framework through export controls, sector-specific rules, or antitrust enforcement on tech platforms. So the 'no regulation' reading is too optimistic; risk remains that policy tightens later.
"Voluntary reviews already create informal guardrails that reduce the chance of chaotic regulatory overcorrection."
Gemini's binary tail-risk scenario overlooks how the voluntary national security reviews already accepted by Microsoft and Google, as Claude highlighted, establish informal guardrails that could prevent a full regulatory vacuum. This hybrid model might channel safety concerns into targeted export controls rather than broad overcorrection, muting the valuation wipeout risk if a Mythos-like breach occurs. The political feedback loop Grok described favors incremental adjustments over sudden reversals.
"Voluntary review without enforcement is precedent for speed, not safety—it signals industry can self-police without consequence."
Claude and Grok both assume voluntary reviews by Microsoft and Google establish durable guardrails, but neither addresses enforcement teeth. 'Non-binding' means zero legal recourse if either firm ships an unsafe model. The precedent argument conflates precedent with constraint. A reputational hit post-breach is real but asymmetric: the firm absorbs PR damage while the state absorbs security fallout. That's moral hazard, not guardrails.
"Insurance markets will impose the regulatory guardrails that the federal government failed to mandate."
Claude is right about moral hazard, but both Claude and Gemini miss the insurance angle. If a Claude Mythos-level breach occurs, the real regulator won't be the White House—it will be the insurance industry. Once underwriters deem frontier models 'uninsurable' without federal safety certification, the market will force the compliance that the administration just abandoned. This creates a de facto private-sector regulatory regime, effectively taxing R&D speed with massive, non-discretionary risk premiums.
"Non-binding reviews can ripple through procurement and insurance, creating a de facto regulatory regime that constrains frontier AI deployment even without formal teeth."
Claude, you underestimate how non-binding reviews ripple through procurement and underwriting. Even without legal teeth, public buyers and critical-sector clients can demand safety certifications before purchasing or deploying frontier models, and insurers will price in frontier risk—pushing firms to adopt verifiable guardrails. So the 'no enforcement' stance may be misleading: a de facto regulatory regime can emerge from market discipline, not statutes, meaning near-term upside for speed comes with outsized risk of a market- or policy-driven clampdown.
The panel agrees that while the current regulatory environment favors speed over restraint, the lack of federal oversight for 'frontier' AI models creates significant risks, including moral hazard and potential market-driven clampdowns. The consensus is that near-term gains in R&D speed come with outsized risks.
Near-term gains in R&D speed.
Moral hazard and potential market-driven clampdowns due to lack of federal oversight.