Inside the alternative playbook to AI regulation (axios.com)

AI regulation in the U.S. over the last few months has been a frenzy. Some experts say it didn't have to be this way. Why it matters: AI companies and the government are praising each other for successful collaboration on rules for cutting-edge AI, but that view hides a scramble behind the scenes that could have been avoided. Driving the news : OpenAI and Anthropic's latest, most powerful models both ended up getting nods from the government before wide release. That would have been unthinkable just months ago. The big picture: The two companies now know first-hand what it's like to release powerful models under the Trump administration's approach to regulation. That's featured export control threats, licensing requirements and negotiations with a host of government agencies that are sometimes at odds. Other AI labs are poised to face the same process, as a cybersecurity executive order detailing standards and procedures gets implemented. Flashback: A Biden-era AI executive order required companies to share safety testing results with the government, including whether their models could be tricked into bypassing built-in safety guardrails. The "jailbreaking" issue was the type of vulnerability Amazon flagged last month that eventually led to export controls on Anthropic. President Trump, vowing to pursue a deregulatory agenda on AI, scrapped that order's reporting requirements. When the Trump administration's safety concerns with Anthropic came to a head, there was no alignment with industry and government on how severe jailbreaks need to be to raise a red flag. Had there been a framework to assess and standardize the severity of jailbreaking or safety bypassing, export controls may have been avoided, one source familiar with the situation told Axios. What they're saying: The rest of the world has implemented tech privacy regulations, updated antitrust laws and passed transparency and research access measures, former Biden tech official Asad Ramzanali said. "We didn't do any of it," he said of the U.S., depriving the country of a strong foundation to create rules around AI today. "Given where things are, this is the right thing for the companies and for the government," he added, referring to the Trump administration's efforts to set rules around powerful AI models. "But we should never have been here." The government failed to recruit and retain technical expertise from the outset, according to the Cato Institute's Kevin Frazier, noting less than 1 percent of AI Ph.D.s go into government. Agencies like the Cybersecurity and Infrastructure Security Agency and the Center for AI Standards and Innovation have also been "sidelined" and underfunded, said Frazier, who is also the director of the University of Texas' AI and law program. CAISI's operational budget is $15 million but it needs $84 million annually to fulfill Trump's AI action plan, according to the Institute for Progress . "The truth is that there's never been a 'right' answer for how to g