Generalization
The intended outcome of most model training, where the model learns a statistical pattern that applies across the training population without retaining any specific individual example in reproducible form. Distinguished from memorization, which is an unintended but real and testable retention risk.
Defined in 2 GAGE programs, which carry 3 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 intended outcome of most model training, where the model learns a statistical pattern that applies across the training population without retaining any specific individual example in reproducible form. Distinguished from memorization, which is an unintended but real and testable retention risk.
Whether a model performs well on new examples it did not train on. A model that scores well on its training data but fails on new data has learned the wrong thing (often a shortcut) and will fail in deployment.
The intended outcome of machine learning training, in which a model learns patterns that transfer to new, unseen inputs rather than retaining specific training examples. Generalized model behavior is not, by itself, a personal data concern, because no specific record survives inside 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 that was not: personal data found in a model trained last year · Data Incidents, AI Data Governance: The Data Chair
- Train a model with your own hands and watch what it actually learns · Build Before You Govern, 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.