Measuring (some aspects of) the metacognition of AI
A robust decision-making process must take into account uncertainty, especially when the choice involves inherent risks. Because artificial intelligence (AI) systems are increasingly integrated into decision-making workflows, managing uncertainty relies more and more on the metacognitive capabilities of these systems; i.e, their ability to assess the reliability of and regulate their own decisions. Hence, it is crucial to employ robust methods to measure the metacognitive abilities of AI. This paper is primarily a methodological contribution that highlights a key limitation of commonly used measures of AI metacognitive sensitivity--the ability to generate confidence ratings that distingui...
| Authors | Richard Servajean, Philippe Servajean |
|---|---|
| Primary category | cs.AI |
| Published | 31 March 2026 |
| Last updated at source | 28 September 2026 |
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