Transparency & interpretability: what it is, and how experts rate it
Challenges in understanding or explaining the decision-making processes of AI systems, which can lead to mistrust, difficulty in enforcing compliance standards or holding relevant actors accountable for harms, and the inability to identify and correct errors.
Definition and category 7.4 from the MIT AI Risk Repository, used under CC BY 4.0.
How experts rate it
With mitigations — 4.8%The difference between the two estimates — 2.7 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 23 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 2.7 percentage points.
Rank 23 of 23 by expert-rated severity, at 7.5%. See all 23 ranked
Evidence
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What's been called for
Called for by 5 organisations
Companies building the most capable AI models should have to tell government and the public what their models can do and the risks they pose.
What politicians have said
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What Australians say
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What people ask
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Think Australia should act?
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