Profiling
As defined in GDPR Article 4(4), any form of automated processing of personal data consisting of using such data to evaluate certain personal aspects relating to a natural person, in particular to analyse or predict aspects concerning that natural person's performance at work, economic situation, health, personal preferences, interests, reliability, behaviour, location or movements.
Defined in 2 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in EU AI Act Implementation Expert.
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.
As defined in GDPR Article 4(4), any form of automated processing of personal data consisting of using such data to evaluate certain personal aspects relating to a natural person, in particular to analyse or predict aspects concerning that natural person's performance at work, economic situation, health, personal preferences, interests, reliability, behaviour, location or movements.
Under GDPR Article 4(4), any form of automated processing of personal data used to evaluate certain personal aspects relating to a natural person, including performance at work, economic situation, health, reliability, and behavior. Fraud scoring and hiring ranking are both profiling, which is why Recital 71 names them as the paradigm cases GDPR Article 22 was built to reach.
Automated processing of personal data to evaluate certain personal aspects of a natural person, in particular to analyse or predict aspects concerning personality, interests, behaviour, or location. In the Article 5(1)(d) context, profiling of a natural person as the sole basis for a criminal-offence risk assessment is prohibited.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- The right to an account: keeping the decision trail a person affected by your AI can find, follow, and contest · Lineage Under Audit, Certified AI Data Governance Professional (CADGP)
- Prohibited AI Practices: The Hard Lines (Article 5) · Act Foundations and Current Timeline, EU AI Act Implementation Expert
- Annex III Deep Dive: The High-Risk Domains · AI System Inventory and Classification, EU AI Act Implementation Expert
Where it shows up at work
A definition is where Profiling 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.
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.
Classifies a system by role and risk tier, knows which obligations bind on which date after the Digital Omnibus, and what evidence conformity needs.
One lesson on this page teach it as a primary outcome.
Defines who reviews AI outputs, what they check, when they can override, and how to keep review from becoming a rubber stamp.
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 it at depth · 14 open postings this week
- AI Compliance Managerneeds it at depth · 2 open postings this week
- Responsible AI Leadneeds it at depth · 7 open postings this week
- AI Product Manager, responsible product editionneeds it at depth · 3 open postings this week
- Ethical AI Specialistneeds working knowledge · 5 open postings this week
- Chief Privacy Officer, AI privacy editionneeds working knowledge
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: EU AI Act Articles 13 and 50; NIST AI RMF trustworthiness characteristics; Regulation (EU) 2024/1689; Regulation (EU) 2026/1744.
One interview question about it
A customer asks why the model decided against them. What can you explain, what can you not, and how can they contest it?
Asked of candidates for explainability, transparency and contestability. 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 law degree (JD, LLB or LLM), no AI work yet carries it as a claim to back up: The EU AI Act reads like the statutes you were trained on; the content is new, the method is not.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.