A stratified, versioned validation using representative: Before | AIGP
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A stratified, versioned validation using representative: Before approval, which evidence most directly

AIGP Understanding the Foundations of AI Governance Hard

Use representative, versioned, stratified validation to resolve both provenance and depot-specific performance uncertainty.

The question

A logistics company considers a vendor’s scheduling model. Its benchmark uses unknown data, while customization may alter performance across depot types. Before approval, which evidence most directly resolves both uncertainties?

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  1. A signed supplier warranty covering scheduling model performance
    A warranty allocates responsibility but does not demonstrate representative data, customized behavior, or performance across operational subgroups.
  2. A stratified, versioned validation using representative depot data ✓
    This tests performance across relevant depot types while documenting dataset provenance, transformations, versions, and limits for the intended scheduling use.
  3. The supplier’s overall accuracy benchmark and product specification
    A benchmark may not represent this company’s depots, and product specifications do not establish customized performance or data provenance.
  4. A pilot using historical schedules without depot-level subgroup analysis
    A pilot provides some evidence, but without subgroup analysis it cannot resolve whether performance varies across depot types.
The trap
Match validation evidence to the intended population, operational slices, and exact model version.

How to remember it

Use representative, versioned, stratified validation to resolve both provenance and depot-specific performance uncertainty.

How many of these would you get right?

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