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Anthropic co-founder confirms the company briefed the Trump administration on Mythos

Published byAIDaily Editorial Team
4 min read
Original source author: Sarah Perez

In an interview at the Semafor World Economy summit this week, Anthropic co-founder Jack Clark explained why the company was still engaged with the U.S. government while simultaneously suing them.

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Jack Clark, one of Anthropic’s co-founders who also serves as Head of Public Benefit for Anthropic PBC, confirmed that the AI company had briefed the Trump administration about its new Mythos model.

The model, announced last week , is so dangerous that it’s not being released to the public, largely due to its alleged powerful cybersecurity capabilities.

In an interview at the Semafor World Economy summit this week, Clark explained why the company was still engaged with the U.S. government while simultaneously suing them.

This March, Anthropic filed a lawsuit against Trump’s Department of Defense (DOD) after the agency labeled the company a supply-chain risk. Anthropic had clashed with the Pentagon over whether the military should have unrestricted access to Anthropic’s AI systems for use cases that included mass surveillance of Americans and fully autonomous weapons. (OpenAI ended up winning the deal instead.)

At the conference, Clark downplayed the administration’s labeling of its business as a supply-chain risk, saying it was merely a “narrow contracting dispute” and that Anthropic didn’t want it to get in the way of the fact that the company cares about national security.

“Our position is the government has to know about this stuff, and we have to find new ways for the government to partner with a private sector that is making things that are truly revolutionizing the economy, but are going to have aspects to them which hit National Security, equities, and other ones,” said Clark. “So absolutely, we talked to them about Mythos, and we’ll talk to them about the next models as well.”

His confirmation comes after reports last week that Trump officials were encouraging banks to test Mythos , including JPMorgan Chase, Goldman Sachs, Citigroup, Bank of America, and Morgan Stanley.

Clark also addressed other aspects of AI’s impact on society during the interview, including things like unemployment and higher education.

Previously, Anthropic CEO Dario Amodei has warned that AI’s advances could bring unemployment to Depression-era numbers , but Clark slightly disagrees. He explained in the interview that Amodei believes that AI will get much more powerful than people expect very quickly, so he’s using that as the basis of his estimations.

Clark, who leads a team of economists at Anthropic, said that the company is so far only seeing “some potential weakness in early graduate employment” across select industries. He noted that Anthropic is ready in case there are major employment shifts, however.

Pushed to say what majors college students today should be pursuing or avoiding, as a result of AI’s impacts, Clark would only broadly suggest that the most important majors are those that “involve synthesis across a whole variety of subjects and analytical thinking about that.”

“That’s because what AI allows us to do is it allows you to have access to sort of an arbitrary amount of subject matter experts in different domains,” Clark said. “But the really important thing is knowing the right questions to ask and having intuitions about what would be interesting if you collided different insights from many different disciplines.”

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Key takeaways

  • Anthropic's engagement with the U.S. government highlights the importance of dialogue between AI companies and regulatory authorities.
  • The refusal to release the Mythos model raises questions about the ethical use of AI and its implications for privacy.
  • The divergence over AI's impact on employment reflects uncertainties that are also relevant to the Brazilian job market.

Editorial analysis

Jack Clark's confirmation of Anthropic's engagement with the Trump administration regarding the Mythos model raises crucial questions about the relationship between AI companies and governments, especially in a context where national security and privacy are in constant debate. For the Brazilian tech sector, this can serve as a wake-up call about the need for a more robust dialogue between AI startups and regulatory authorities. Brazil, which is in the process of developing its own AI regulations, can benefit from observing how companies like Anthropic handle governance and security issues.

Moreover, Anthropic's refusal to release Mythos to the public due to its cybersecurity capabilities highlights the growing concern over the ethical use of AI. This could influence the development of policies in Brazil, where technological innovation must be balanced with the protection of citizens' rights. The Brazilian government and local companies need to consider how to regulate emerging technologies without stifling innovation, a challenge that becomes increasingly relevant as AI advances rapidly.

Another important point is the discussion about AI's impact on employment. The divergence between Clark and Amodei regarding the extent of unemployment caused by automation reflects an uncertainty that can also be observed in Brazil. With an already vulnerable job market, it is essential for companies and the government to prepare for the changes that AI may bring by investing in education and workforce retraining. The future of work in Brazil may be shaped by how AI is adopted and regulated, requiring a proactive approach.

Finally, Anthropic's interaction with financial institutions to test Mythos suggests that the banking sector may be at the forefront of AI adoption. This is particularly relevant for Brazil, where the financial sector is one of the most innovative in terms of technology. What is observed in the U.S. could be a precursor to what may happen in Brazil, where collaboration between fintechs and traditional institutions could accelerate AI adoption and transform the local financial sector.

What this coverage includes

  • Clear source attribution and link to the original publication.
  • Editorial framing about relevance, impact, and likely next developments.
  • Review for readability, context, and duplication before publication.

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