Data subject
The individual to whom personal data relates, the terminology used across GDPR and most global privacy frameworks. A deletion decision ultimately exists to serve, and be defensible to, the interests of the data subjects whose information is in scope, even though the decision itself is made by the organization.
Defined in 2 GAGE programs, which carry 5 distinct definitions of it. The wording above is taught in AI Data Governance: The Data Chair.
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 individual whose personal data is being processed, the party who holds rights (including the right to erasure under GDPR Article 17 and comparable rights under other frameworks) with respect to that data. In this topic's Section 5 scenario, Diane is the data subject exercising her erasure right against Glenrock Credit Union.
The identified or identifiable living person that a piece of personal data describes. Consent archaeology is ultimately about what was promised to the data subjects, whose reasonable expectations the analysis must protect.
The individual to whom personal data relates, the terminology used across GDPR and most global privacy frameworks. A deletion decision ultimately exists to serve, and be defensible to, the interests of the data subjects whose information is in scope, even though the decision itself is made by the organization.
The GDPR term for the identified or identifiable natural person whose personal data is being processed. In this topic's context, the person whose photo, text, or other personal data a model may have memorized, whether or not that person is aware their data fed the training set.
The identified or identifiable individual to whom personal data relates, and the person who can exercise rights such as erasure and restriction over it.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- Retention versus the model that memorized: deleting data a model already learned from · Consent, Purpose, and the Law of Data, AI Data Governance: The Data Chair
- The deletion decision: the terabytes your organization should destroy this quarter, defended · The Money of Data, AI Data Governance: The Data Chair
- The deletion that was not: personal data found in a model trained last year · Data Incidents, AI Data Governance: The Data Chair
- 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.