Pseudonymisation
Processing personal data so it can no longer be attributed to a specific person without additional information kept separately (for example replacing names with codes). Pseudonymised data is still personal data and still fully regulated; it is not the same as anonymisation.
Defined in 2 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in AI Governance: Applied Mastery.
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.
Processing personal data so it can no longer be attributed to a specific person without additional information kept separately (for example replacing names with codes). Pseudonymised data is still personal data and still fully regulated; it is not the same as anonymisation.
Replacing identifying details with a consistent stand-in code so a record can still be linked back to the original if genuinely needed, unlike anonymisation, which removes that link entirely; a practical middle option when drafting a prompt.
Replacing direct identifiers with a key or token that can re-identify the data. It reduces risk but does not remove data from scope; pseudonymised data is still personal data and still needs a retention clock.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- Your Regulator Probably Isn't Brussels · Ethical and Responsible AI and Operational Governance, AI Literacy & Professional Conduct
- Consent archaeology: what this data was collected for versus what you want to do · Data Reality, AI Governance: Applied Mastery
- The retention decision: what you must keep, what you must destroy, and proving both · Data Reality, AI Governance: Applied Mastery
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.