AI performing worse for some groups: what it is, and how experts rate it
Accuracy and effectiveness of AI decisions and actions is dependent on group membership, where decisions in AI system design and biased training data lead to unequal outcomes, reduced benefits, increased effort, and alienation of users.
Definition and category 1.3 from the MIT AI Risk Repository, used under CC BY 4.0.
How experts rate it
With mitigations — 5.4%The difference between the two estimates — 3.8 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 21 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 3.8 percentage points.
Rank 21 of 23 by expert-rated severity, at 9.2%. See all 23 ranked
Evidence
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What Australians say
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