Historical bias
A source of harm in which the training data accurately records a world that was already unjust, so a correctly built model faithfully reproduces the injustice. There is no data defect to repair; the fix is a governance decision about the objective or about whether to automate the decision at all.
Defined in 2 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in Certified AI Governance Professional (CAIGP).
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.
A source of harm in which the training data accurately records a world that was already unjust, so a correctly built model faithfully reproduces the injustice. There is no data defect to repair; the fix is a governance decision about the objective or about whether to automate the decision at all.
Bias entering because the training data accurately records a past that was unfair, even when the data is complete and correct (Suresh and Guttag, 2021).
A skew that arises when data accurately records an unfair real world, so the AI learns the unfairness as a pattern; not caught by accuracy checks.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- AI Ethics: Bias, Fairness, and Accountability · Ethical and Responsible AI and Operational Governance, Certified AI Practitioner: Workplace Foundations
- Data Literacy for AI: Datasets, Quality, and Pipeline Basics · Advanced AI Literacy, Certified AI Practitioner: Workplace Foundations
- Where the bias came from: tracing a bad prediction to its data · Build Before You Govern, Certified AI Governance Professional (CAIGP)
Where it shows up at work
A definition is where Historical bias 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.
Recognizes hallucination, drift, skew, brittleness and biased outcomes, and knows how each one enters a system.
One lesson on this page teach it as a primary outcome.
Profiles data, sets rules and thresholds, monitors, assigns issues to owners, and knows when data is not fit to train or run a model.
One lesson on this page teach it as a primary outcome.
Designs role-based AI training that measures skill, not attendance, with approved-use guidance, office hours and communities of practice.
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 Model Validatorneeds it at depth
- AI Literacy Leadneeds working knowledge
- Model Risk Managerneeds it at depth
- AI Evaluation Specialistneeds it at depth · 6 open postings this week
- Ethical AI Specialistneeds it at depth · 5 open postings this week
- Responsible AI Leadneeds working knowledge · 7 open postings this week
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: NIST AI RMF MEASURE 2; ISO/IEC 42001; EU AI Act Article 10; ISO 8000.
One interview question about it
Tell me about a time a model was confidently wrong. How did you notice, and what did you change afterwards?
Asked of candidates for model failure modes and bias recognition. 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.
- A data science, statistics or analytics degree carries it as work you can show: Bias and failure modes were in your projects, not only your reading.
- Data analysis, stewardship and business intelligence carries it as work you can show: Quality rules and profiling results are your artifacts.
- Human resources and people operations carries it as a claim to back up: Training design and delivery are part of the function.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.