Evidence type
The specific field on a lineage map edge stating exactly how the claim behind that edge was verified, a config file, a query log entry, an interview, a hash check, or an honest "Suspected, unconfirmed"; the field this entire topic's method is built around interrogating.
Defined in 2 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in Certified AI Data Governance Professional (CADGP).
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.
The specific field on a lineage map edge stating exactly how the claim behind that edge was verified, a config file, a query log entry, an interview, a hash check, or an honest "Suspected, unconfirmed"; the field this entire topic's method is built around interrogating.
One of four categories of substantiation this topic requires behind any mitigation claim: a test log, a red-team note, a moderation sample, or a technical control description with a named responsible owner.
The specific proof behind a lineage claim, such as a pipeline configuration file read directly, a query log entry, an interview with a named role, or an inference from indirect signals. The evidence type field is what separates a defensible lineage claim from a guess.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- The lineage map: your estate's first honest picture of where its data actually comes from · The Estate Survey, Certified AI Data Governance Professional (CADGP)
- Your lineage map under attack: the red team finds the gap you papered over · Adversarial Data Governance, Certified AI Data Governance Professional (CADGP)
- Security Self-Assessment Methodology · Algorithm Filing and Registration, Certified China AI Regulatory Professional (CCARP)
Where it shows up at work
A definition is where Evidence type 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.
Reviews purpose, data, affected people, accuracy, bias, security, oversight, vendors and law for a use case, scores likelihood and impact, and documents residual risk.
One lesson on this page teach it as a primary outcome.
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.
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.
- Chief Risk Officer, AI risk editionneeds it at depth
- Chief Privacy Officer, AI privacy editionneeds it at depth
- Responsible AI Leadneeds it at depth · 7 open postings this week
- AI Governance Managerneeds it at depth
- AI Product Manager, responsible product editionneeds it at depth · 3 open postings this week
- AI Risk Managerneeds it at depth · 2 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 MAP and MEASURE; ISO/IEC 42005; EU AI Act Article 27; SR 11-7.
One interview question about it
Take me through an AI risk and impact assessment you would run for a hiring tool. What do you assess, and who signs?
Asked of candidates for ai risk and impact assessment. 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.
- Privacy and data protection carries it as work you can show: A DPIA is an impact assessment; the AI version adds accuracy, bias and oversight.
- Model risk, credit risk and quantitative analysis carries it as work you can show: Validation reports and model inventories are your record.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.