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[ARTICLE · art-56799] src=arxiv.org ↗ pub= topic=artificial-intelligence verified=true sentiment=· neutral

Ceci n'est pas une pipe: AI systems as semantic abstractions

A new semantic framework proposed in arXiv:2607.09489v1 distinguishes between justified domain knowledge, reference sources, and system capabilities to define AI failures such as extrapolation, refuted assertions, and source mismatches. The framework aims to provide a vocabulary for specifying and checking AI systems whose outputs must be justified by reliable claims and explicit authority.

read1 min views17 publishedJul 13, 2026

arXiv:2607.09489v1 Announce Type: new Abstract: An AI system's output is not the fact or world state it appears to describe, but rather an engineered representation. We propose a semantic framework to describe AI systems, to be able to examine the correctness of such representations. To do so, we distinguish what is justified by accepted domain knowledge, what reference sources say, and what the system can currently use. This allows us to give precise definitions to common failures: extrapolation, refuted or unsupported assertion, sources versus knowledge mismatch, stale or refuted source, added hypotheses, unsupported use... We hope our framework gives a useful vocabulary for specifying and checking AI systems whose outputs, citations, tool calls, and world-changing actions must be justified by reliable claims and explicit authority rather than apparent fluency.

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