AI Governance Engineer
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Abstention band

By Updated

A range of scores in which a system does not act on its own but routes the case to a human reviewer. Its width is set by risk tier; the band size and the reviewers' override rate are monitored as signals. Conformal prediction gives one way to size it 1.

Developed in
ch. 11, Certainty required by risk tier
Chapters
ch. 11, AI Defined
Source
1 numbered reference, listed below

Where it is used

One chapter of the Body of Knowledge uses the term. Each link opens the first section that does.

  • Automation bias

    The tendency of a person to over-rely on an automated system's output.

  • Conformal prediction

    A distribution-free method that turns a trained model's output into a set of candidate answers that contains the right one with a chosen probability.

  • Risk tier

    An organisation's own rating of an AI use case, computed at intake by a versioned policy from declared profile fields such as autonomy, decision impact…

Sources

  1. [1] A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification (prediction sets with user-specified coverage; arXiv 2107.07511). Angelopoulos and Bates. 2021-07-15. https://arxiv.org/abs/2107.07511 (verified: primary)

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

Cite this term

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

BibTeX

@misc{aige2026abstentionband,
  author  = {Jorge García Aibar},
  title   = {{Abstention band}},
  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/abstention-band}
}