Applying the minimization principle to AI governance
The IAPP has published analysis examining how the data minimization principle — traditionally used in privacy law to limit unnecessary data collection — can be applied to AI governance frameworks.
Why this matters: Data minimization is one of the oldest and most practical ideas in privacy: collect only what you actually need. AI systems tend to work in the opposite direction, consuming as much data as possible on the assumption that more is better. If minimization gets built into how AI is designed and governed, that changes what companies can justify collecting in the first place. That is a meaningful shift, not a procedural one. It moves the pressure point earlier, before data is gathered, rather than after something goes wrong.
Who should care: AI governance · Lawyers · Administrators · General readers · Policy
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