AI Governance Engineer
GitHub

Four-fifths rule

By Updated

The US Uniform Guidelines rule of thumb that a group selection rate below 80% of the highest group's rate will generally be regarded as evidence of adverse impact, qualified by statistical and practical significance 1. It is not a safe harbour: smaller gaps can still count.

Developed in
ch. 16, The four-fifths rule and the adverse-impact ratio
ch. 20, Fairness measures the law recognises
Chapters
ch. 16, Fairness & XAI · ch. 20, Existing Law
Source
1 numbered reference, listed below

Where it is used

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

Patterns that use this term

One pattern page uses the term.

Sources

  1. [1] 29 CFR 1607.4(D), Uniform Guidelines on Employee Selection Procedures (1978) (adverse impact and the "four-fifths rule", with statistical-significance and small-numbers caveats; text as of 2026-09-01). eCFR. 2026-09-01. https://www.ecfr.gov/current/title-29/subtitle-B/chapter-XIV/part-1607/section-1607.4 (verified: primary)

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

Cite this term

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

BibTeX

@misc{aige2026fourfifthsrule,
  author  = {Jorge García Aibar},
  title   = {{Four-fifths rule}},
  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/four-fifths-rule}
}