Examining Data Compartmentalization for AI Governance
Nicole Mitchell ⋅ Peter Kairouz ⋅ Sébastien Krier ⋅ Eleni Triantafillou
Abstract
We present data compartmentalization as a unifying framework across a number of existing approaches that may allow for training and serving models with finer-grained control over data. We present hypotheses and open questions surrounding the suitability of technical approaches for addressing policy concerns related to AI governance.
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