Replication
An independent study, run by a different team, that produces a similar result to an earlier study, increasing confidence that the finding is real rather than a one-time artifact of a single study's design or sample. Replication carries the most weight when the original study was pre-registered, its design and analysis plan locked in before data collection, since that rules out the analysis being reshaped after the fact to fit the result.
Defined in 2 GAGE programs, which carry 2 distinct definitions of it. The wording above is taught in Certified AI Practitioner: Workplace Foundations.
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 study, run by a different team, that produces a similar result to an earlier study, increasing confidence that the finding is real rather than a one-time artifact of a single study's design or sample. Replication carries the most weight when the original study was pre-registered, its design and analysis plan locked in before data collection, since that rules out the analysis being reshaped after the fact to fit the result.
Independently reconstructing the conditions behind a headline claim, using a different sample, a different confirmed operating point, or a different data source than the original method, and stating explicitly what was changed, so as to reach a genuinely independent check rather than rerunning the original method unchanged.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- What the Evidence Really Says About AI and Learning · Bonus: AI for Educators, Certified AI Practitioner: Workplace Foundations
- Independent Challenge: The Second Line Reads the Model · Evaluation and Trust, Certified AI Governance Professional (CAIGP)
Where it shows up at work
A definition is where Replication 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.
Classifies models by tier, sets validation requirements, challenges data, methodology and performance evidence, and reports aggregate exposure.
One lesson on this page teach it as a primary outcome.
Designs tests for factuality, robustness, fairness, safety and abuse resistance with rubrics, baselines and thresholds, and says what a score misses.
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.
- Model Risk Managerneeds it at depth
- AI Model Validatorneeds it at depth
- Chief Audit Executive, AI audit editionneeds working knowledge
- Chief Risk Officer, AI risk editionneeds working knowledge
- Chief Technology Officer, AI engineering editionneeds it at depth
- AI Evaluation Specialistneeds it at depth · 6 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: SR 11-7; NIST AI RMF MEASURE; NIST AI RMF MEASURE 1 and 2; NIST AI 600-1.
One interview question about it
Explain independent challenge of a model to someone who built it. What do you challenge, and what do you leave to the developers?
Asked of candidates for model risk management and independent challenge. 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.
- Model risk, credit risk and quantitative analysis carries it as work you can show: Validation reports and model inventories are your record.
- A computer science or software engineering degree carries it as a claim to back up: Testing is second nature; AI evaluation design is a new shape of it.
- A data science, statistics or analytics degree carries it as a claim to back up: Evaluation design for a governance decision is a new frame for a known skill.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.