MIT FutureTech and the University of Queensland surveyed 272 AI experts from 37 countries on 24 categories of catastrophic AI risk, defined as over 1 million deaths, over $100 billion in losses, or civilizational-scale damage. Under current development trajectories, 18 of 24 risk categories cleared a 10% five-year probability threshold. Even with pragmatic mitigations applied, 5 categories remained above that bar. Weapons, cyberattacks, and power concentration topped the list.

Catastrophic AI risk has mostly lived in op-eds and open letters. This study puts numbers on it instead. MIT FutureTech and the University of Queensland’s School of Psychology surveyed 272 international AI experts, drawn from industry, academia, government, and civil society across 37 countries, asking them to evaluate 24 distinct AI risk categories, according to MIT Sloan’s release of the working paper. A catastrophic outcome was defined precisely: more than 1 million deaths, more than $100 billion in financial loss, or civilizational-scale intangible impacts.

Under a business-as-usual trajectory, experts judged 18 of the 24 risk categories to carry at least a 10% probability of a catastrophic outcome within five years, according to the University of Queensland’s summary of the findings. Even after applying pragmatic mitigations, the kind of cost-effective interventions governments and companies could plausibly adopt, 5 categories still cleared that bar. Catastrophic AI risk at that level would be treated as intolerable in almost any other mature industry, which is exactly the comparison MIT FutureTech’s own director drew.