Connor Leahy argues that superintelligence cannot be made safe on any realistic timeline, and treats it as a political problem rather than a technical one. Without intervention he puts doom at 90–95%. The only remedy he sees is an internationally enforced ban backed by government power, and he has moved to Washington as US executive director of Control AI to campaign for it. He estimates such a campaign has about a 10% chance with $50 million and 40% with $500 million.
From open source to politics. Leahy first worked on AI around 2011 as a teenager, already worried about control. He expected AGI around 2040–2050, until GPT-2 in 2019 convinced him it was coming much sooner. He then built open-source replications on the hacker belief that openness makes software safe. He says he became "very burnt" when the community wanted only "faster, bigger, open source, uncensored", and now thinks some of that work was morally bad, though reasonable at the time. Asked why others resist the conclusion, he points to emotion, tribalism and Upton Sinclair's rule; Yampolskiy adds stock options.
Why technical safety fails. He says the field has made almost no progress on the hard problems. An aligned superintelligence would require solving governance, morality, cybersecurity, formal verification and the modeling of social systems at once. Humanity is too confused about morality even to consent to such a system. He gives it three generations of heavily funded science at best. On p(doom), he separates doing nothing (90–95%) from a global ban, which he says lowers it "a lot". In a pre-paradigmatic field, he argues, papers can justify anything, so the only shared ground is that not building superintelligence prevents the risk.
The governance case. Every risky industry has government-set risk limits: you can't build a bomb in your garage, while defense contractors like Lockheed Martin operate under tight security. AI, he says, faces "more regulation on selling a sandwich", defended by the largest lobbying force in history. As president, he would announce on national TV that preventing superintelligence is a national priority, and demand plans within a week from the military, intelligence and energy agencies. Nationalization is one possible tool among several. He wants verification methods that let the US and China each prove they are not building it.
Insiders, compute and red lines. He tells lab employees to quit, calling working from the inside a trap or vigilantism. A pact among Altman, Musk and Hassabis couldn't be enforced without law. If superintelligence becomes buildable on a laptop within a few years, "it's probably just game over", though he doesn't expect that soon. Each step forward makes turning back exponentially harder, and red lines from the Turing test to Mythos's hacking have passed without reaction, which is why he doubts a warning shot will come.
What went wrong in the movement. He blames AI safety's roots in libertarianism and utilitarianism. He cites an Eliezer Yudkowsky essay from around 1998–99, which Yudkowsky has since moved away from, that urged keeping the government and the public uninformed. Japanese attendees at a conference asked him why charities rather than militaries were handling a threat to nation-states. He calls this a textbook public-goods problem, like a river polluted under market pressure. He sets suffering risks aside as real but not actionable. He argues it doesn't matter which lab or country builds superintelligence first, because the result would be an evolving ecosystem of billions of grown, self-modifying copies, not a single system.
Resources and opponents. He sees funding as the binding constraint. He says roughly $500 million would deliver a message 7–10 times over a year to the US public. Control AI's donors, including Jaan Tallinn, have given far less than $50 million. With 10 years he is "quite confident"; with two it is "real tricky". He would rather talk with academics outside tech, unions and civil-rights groups than debate accelerationists, whom he sees as financially captured.