Which AI founders are against AI regulation and why?

Who is pushing back

On the other side from Amodei and Hassabis stand Meta's Mark Zuckerberg and Nvidia's Jensen Huang, who have rejected the premise that new AI regulation is needed. Elon Musk has joined them in practice. Zuckerberg, Musk, and Huang spoke with President Donald Trump and convinced him to block efforts to establish an industry-funded AI oversight body, a proposal that had come from Google's Demis Hassabis, modeled on the financial regulator FINRA.

What they actually argue

Their case has three threads, and they are worth taking seriously on their own terms.

Safety is an engineering problem, not a legislative one. Huang's reasoning is that models are software running on computers, complicated but ordinary, and therefore controllable with tools that already exist. Safety, in his framing, is a job for engineers rather than legislators. At Salesforce's Dreamforce conference he put it plainly: "We don't need new laws or regulations," casting safety as "an engineering problem" and denying any trade-off between velocity and care.

Market pressure already disciplines companies. Zuckerberg argued that AI companies already have powerful commercial reasons to build aligned systems, avoid harms that could bring legal liability, and work with outside evaluators. In a long post on X, he said the market could discipline AI companies: people will not use agents that behave in ways they do not want, so trust and alignment become a competitive advantage.

Regulation protects incumbents, not the public. This is the argument that carries the most weight if you think about it structurally. The three CEOs argued the proposed framework would cement dominance for OpenAI, Anthropic, and Google, creating a regulatory moat. Stringent compliance requirements that a trillion-dollar company absorbs easily can quietly kill every startup trying to compete with them.

The tension that does not go away

Both sides have a real point, which is why this argument is not resolving quickly. The pro-regulation camp is right that capability is moving faster than any company's internal safety work. The anti-regulation camp is right that badly designed rules tend to freeze the current power structure in place.

Musk's own record illustrates the tension: he signed the Future of Life Institute open letter calling for a pause on giant AI experiments, then announced his own new AI company two weeks later, and later used DOGE to dismantle chunks of the federal workforce rather than build regulatory capacity. Positions in this debate track commercial interest at least as much as philosophy, and that is worth holding in mind when you hear either side make a principled case.

The honest read is that the people building the most profitable AI infrastructure have the clearest incentive to argue against rules that would slow it down, and the people at labs most vulnerable to a catastrophic failure have the clearest incentive to argue for rules that might distribute responsibility. Neither position is automatically wrong. But knowing which is which helps you weight what you hear.