Bias audit
An independent review of an automated decision tool's outcomes across different groups, required in New York City under Local Law 144 before an employer may use an automated employment decision tool; a company's own audit history can serve as a checkable fact in a translated talking point.
Defined in 2 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in The AI Lobbyist: Certified AI Policy Strategist.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
An independent review of an automated decision tool's outcomes across different groups, required in New York City under Local Law 144 before an employer may use an automated employment decision tool; a company's own audit history can serve as a checkable fact in a translated talking point.
A structured test of a hiring tool that reports, for each protected group, the selection rate and impact ratio, applies the four-fifths rule, names an independent auditor, and states the population and date. A fairness statement that lacks these elements is not a bias audit.
An independent evaluation of an AI system's outcomes across different demographic or protected-class groups, used to determine whether the system produces disparate impacts. Bias audits are the primary compliance mechanism behind deployer-side fairness laws such as NYC Local Law 144.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- The hiring-AI problem: bias audits, notices, and the law already watching hiring AI · The EU AI Act: The Executive Map, Certified AI Governance Professional (CAIGP)
- The Only Ten Things About AI That Matter in Policy · The Point Person Mandate, The AI Lobbyist: Certified AI Policy Strategist
- Translating Corporate AI Risk into Policy Talking Points · Business and Industry Representation, The AI Lobbyist: Certified AI Policy Strategist
Where it shows up at work
A definition is where Bias audit starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Knows the rules on automated employment decisions, bias audits and notices, and treats hiring AI as the highest-risk use case it is.
One lesson on this page teach it as a primary outcome.
Turns technical uncertainty into a one-page decision: material risks, trends, exceptions, remediation, and what the board is being asked to accept.
One lesson on this page teach it as a primary outcome.
Decides what a person affected by an AI decision must be told, how an output can be explained, and how they can challenge it.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- AI Regulatory Counselneeds working knowledge · 14 open postings this week
- Ethical AI Specialistneeds working knowledge · 5 open postings this week
- Chief AI Officerneeds it at depth
- Chief Audit Executive, AI audit editionneeds it at depth
- Chief Privacy Officer, AI privacy editionneeds it at depth
- Chief Risk Officer, AI risk editionneeds it at depth
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
Where the frameworks place it: NYC Local Law 144; EEOC guidance; EU AI Act Annex III employment; EU AI Act Articles 13 and 50.
One interview question about it
An AI tool screens job applicants. What must be true before you allow it, and what do you check every quarter?
Asked of candidates for ai in hiring and employment decisions. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- Human resources and people operations carries it as a claim to back up: Fair-hiring review and disparate-impact awareness are HR discipline.
- Internal audit and IT audit carries it as a claim to back up: Audit committee reporting is part of senior audit roles.
- Nonprofit program and grants oversight carries it as a claim to back up: Board and funder reporting is the cadence a governance committee needs.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.