Yoshua Bengio and Geoffrey Hinton — both Turing-award laureates and architects of modern deep learning — addressed UN delegates in Geneva this week ahead of the Global Dialogue on AI Governance scheduled for July. Bengio, who co-chairs the dialogue's Scientific Panel with journalist Maria Ressa, told delegates that the world is 'in trouble if you go down a hill with no brake — but you're in even more trouble if there's no steering wheel.' Hinton, speaking at the parallel Digital World Conference co-organized by the UN Research Institute for Social Development, described unregulated AI as a 'very fast car with no steering wheel' and called for binding international frameworks on frontier development.
Both men pointed to the same gap. Capability research is funded at roughly two orders of magnitude more than safety research, and the institutions that exist to govern AI — national regulators, the EU AI Act, the US executive frameworks — are reactive and fragmented. The recent International AI Safety Report, which Bengio led with input from more than 100 researchers across the US, EU, China, and Singapore, found that current safeguards are inadequate to the pace of capability gains. The headline ask in Geneva was concrete: more public funding for alignment and evaluation work, and a coordinated mechanism for setting and enforcing rules on the most capable systems.
The political backdrop is that the three biggest jurisdictions are moving in different directions. The US National Policy Framework released in March preempts state regulation of model development and discourages new federal AI agencies. The EU is pushing to extend its AI Act timeline while adding export controls on dual-use chips and high-risk algorithms. China requires ethics review for high-risk AI activities through a new April trial guideline. The UN Global Dialogue is the only forum that brings all 193 member states together on this question, which is why Bengio's and Hinton's interventions this week are aimed less at any single government and more at the dialogue's July summit.
For learners: 'AI safety' covers very different things depending on who is talking. It can mean preventing chatbots from giving harmful advice, or stopping AI-generated CSAM, or evaluating whether a frontier model can autonomously help with bioweapons or cyber attacks, or — at the longest horizon — ensuring future systems remain under meaningful human control. When you see calls for 'AI regulation,' look for which of those problems the proposal is actually trying to address. The policies that work for one are often badly suited to the others.