Capability & robustness: what it is, and how experts rate it
AI systems that fail to perform reliably or effectively under varying conditions, exposing them to errors and failures that can have significant consequences, especially in critical applications or areas that require moral reasoning.
Definition and category 7.3 from the MIT AI Risk Repository, used under CC BY 4.0.
How experts rate it
With mitigations — 7.0%The difference between the two estimates — 3.7 points
Mean probability of a catastrophic outcome by 2030 — more than 1 million deaths, or more than USD 100 billion in financial loss, or comparable civilisation-scale intangible damage. Across 272 experts who took part. How this was measured
The study tabulates 5 of its 23 figures; this one was read from MIT's published chart on 18 August 2026.
Ranks 18 of 23 rated risks. This study published no interval for it, so the position of neighbouring risks is not meaningful. Experts put the difference at 3.7 percentage points.
Rank 18 of 23 by expert-rated severity, at 10.7%. See all 23 ranked
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