Lesson 1917 of 2116
AI and Data Minimization Audit: Trimming the Training Set
AI can audit a training dataset against a minimization principle, but the data steward decides what to remove.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2data minimization
- 3training data
- 4privacy
Concept cluster
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Section 1
The premise
AI can audit a training dataset schema against the model's stated purpose and surface fields that may not be necessary.
What AI does well here
- Map each field to a stated model purpose with a necessity rating
- Flag identifiers and quasi-identifiers for additional review
What AI cannot do
- Decide that an 'unnecessary' field can actually be deleted (downstream contracts)
- Sign off on a dataset modification
Key terms in this lesson
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