AI Governance Engineer
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Hallucination

By Updated

Generative output that is stated confidently but is false or unsupported by its sources; NIST's generative AI profile calls it confabulation and lists it among the risks generative AI creates or worsens 1. Groundedness and citation checks are the usual evidence against it.

Developed in
ch. 17, AI-specific failure modes
ch. 11, Predictive versus generative
Chapters
ch. 11, AI Defined · ch. 17, Incidents
Contrast with
Regurgitation
Source
1 numbered reference, listed below

Where it is used

6 chapters of the Body of Knowledge use the term. Each link opens the first section that does.

  • Drift

    The gradual divergence of a model's inputs, outputs or performance from its validated baseline over time; a runtime signal that a control or eval must catch.

  • Generative AI

    AI that outputs new content (text, images, audio, video, code) rather than an estimate about something that exists.

  • Predictive AI

    AI that outputs an estimate about something that exists: a score, class or forecast.

Sources

  1. [1] Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile, NIST AI 600-1 (twelve risks unique to or exacerbated by generative AI; confabulation defined). NIST. 2024-07. https://doi.org/10.6028/NIST.AI.600-1 (verified: primary)

Definitions of legal terms paraphrase the cited text, which governs. Dated statements are as of .

Cite this term

García Aibar, J. (2026). Hallucination. In AI Governance Engineering: The Thesis & Body of Knowledge (v0.5.0), Glossary. https://doi.org/10.5281/zenodo.22956197. https://aigovernanceengineer.com/glossary/hallucination. CC BY 4.0

BibTeX

@misc{aige2026hallucination,
  author  = {Jorge García Aibar},
  title   = {{Hallucination}},
  note    = {Glossary, AI Governance Engineering: The Thesis \& Body of Knowledge, version 0.5.0},
  year    = {2026},
  doi     = {10.5281/zenodo.22956197},
  url     = {https://aigovernanceengineer.com/glossary/hallucination}
}