It’s not about Anthropic vs. OpenAI anymore
AI models have progressed to the point where their capabilities have real political consequences. Dealing with those consequences will require collective action.
The U.S. government is set to take an awful lot of control over which AI models get released.
Two weeks after the U.S. government pulled Anthropic’s Fable and Mythos models , OpenAI’s new model seems to be headed for the same limbo. The Information broke the news Thursday that GPT 5.6 would be released only into limited preview, with the government approving the release “customer by customer” until a general release can be approved.
If that preview only lasts a “couple of weeks,” as Altman reportedly projected, that might not be a particularly big problem. But Mythos has already been in preview for months, and there’s no indication it will make it to general release any time soon. Even a few weeks spent in review could significantly limit the economic upside of a costly new system, at a time when AI labs are trying desperately to improve their bottom lines. If the pace of model development slows as a result, it’s likely to put a similar chill on the ongoing data center buildout.
If this goes bad, the entire industry could be at risk.
Critically, OpenAI and Anthropic are now in the same exact position with the same problems facing them and the same disaster waiting if they fail. Conversations within the tech industry tend to focus on the role of one side or another in bringing this on, either accusing Anthropic of running a regulatory capture scheme or accusing OpenAI of cozying up to Trump to ice out a rival. It’s understandable; many of the most prominent people in the industry have billions of dollars riding on one company or the other.
But what’s happening now is bigger than that. The cost of implementing a haphazard government approval process for every frontier model is obvious, and there’s no fix that helps one lab without helping the others.
The most immediate problem is simply establishing a release process that makes sense. It’s fine for the government to test models before release (this is how it works for lots of consumer products) — but as GMU fellow (and soon-to-be OpenAI employee) Dean Ball detailed in an eloquent post this morning , it’s not clear what kind of safety assurances could be put in place to satisfy regulators. The U.S. government doesn’t have the expertise or capacity for the kind of testing that would be needed here. It’s not even clear what regulators would be trying to protect against, since there’s been no effort to articulate what risks the government is actually concerned about.
It’s tempting to see the government process as the whole of the problem itself, but there are real concerns underneath. Even if you don’t believe the Mythos hype, there’s clear evidence of how AI tools are revolutionizing cybersecurity. There are similar processes at work in biorisk and alignment. Restricting model releases can’t be the whole answer in itself — that will only limit what’s available to the public — but there are real concerns to be addressed.
The best ideas for addressing them, as laid out by Ball, will mean working together. It will mean trusting independent groups to guide the process, even if they don’t completely align with your goals. It will mean lining up behind the least-bad regulatory options available, instead of fighting every regulation tooth and nail. And most of all, it will mean fighting for AI as an industry, instead of seeing safety and regulation as opportunities to gain an advantage.
For a lot of people working in AI, that will be a tough sell. Unfortunately, AI models have progressed to the point where their capabilities have real political consequences. Dealing with those consequences will require collective action. In the weeks to come, we’ll find out if that’s something the industry is capable of.
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Key takeaways
- AI regulation in the U.S. may influence Brazil's approach to innovation and safety.
- Increased bureaucracy could discourage investments in AI startups in Brazil.
- Collaboration between the private sector and regulators will be crucial for an effective regulatory model.
Editorial analysis
The current situation involving the regulation of AI models in the U.S. has significant implications for the tech sector in Brazil. As the U.S. government intensifies control over the release of new models, this could serve as a warning for Brazilian regulators. Brazil, already facing challenges in terms of infrastructure and technical expertise, may be pressured to establish a regulatory framework that not only protects consumers but also does not stifle innovation. The U.S. experience can provide valuable lessons on how to balance safety and technological progress.
Furthermore, the increasing reliance on a government approval process could impact the ecosystem of startups and emerging companies in Brazil. If bureaucracy becomes a hindrance, it may discourage investments in AI and related technologies, especially at a time when the country seeks to position itself as an innovation hub in Latin America. Brazil needs to consider how it can foster an environment that allows for experimentation and development while ensuring safety and ethics in AI usage.
What to watch for next is how tech companies, both in the U.S. and Brazil, will adapt to these new regulatory requirements. Collaboration between the private sector and regulatory bodies will be crucial in developing a model that works for all. Additionally, how companies position themselves regarding these changes may influence public perception of AI and its potential, both positively and negatively. Brazil must pay attention to these dynamics to avoid missing opportunities for leadership in the field of AI.
Finally, it is important to emphasize that the current situation is not just about a rivalry between tech giants, but reflects a broader need for dialogue about responsibility and ethics in AI. Brazil, with its diversity and social complexity, can benefit from a deeper discussion on how AI can be used for the common good, avoiding pitfalls that may arise from overly restrictive or poorly directed regulation.
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