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Pink dotted and green striped territories sit on opposite sides of a wall, each with its own rulebook and rule symbols. A robot carries a mixed suitcase between them, and mismatched symbols appear inside both territories.
Reviewed visual · version 1

RS Glossary

Policy Leakage

Policy leakage is what happens when rules, defaults, or sensitivities built for one legal or cultural setting show up in how an AI system behaves somewhere else — so people in the second place are governed by the first place's assumptions without having chosen them or being told.

Review state
Reviewed in POC
Freshness
Current
Version
3
  • Policy Leakage

Remember it this wayThe model crossed borders; its policy came too.

In plain language

An AI system may carry behavioral limits or defaults from the place where it was built, trained, reviewed, or governed into a different setting. Users then encounter policy they did not knowingly choose.

Why it matters

Hidden policy transfer can affect access, expression, compliance, and trust. Teams need to distinguish model behavior from requirements that actually apply in the deployment environment.

Example

A service used in one country refuses an ordinary local request because its behavior reflects restrictions designed for another jurisdiction.

Common misconception

Policy leakage is not the same as leaking private policy documents. It is the appearance of embedded rules or assumptions outside their original context.

Related terms

Sources

  • Anu Bradford, “The Brussels Effect”explains how one jurisdiction’s standards can spread through global markets and become embedded elsewhere without international agreement or direct coercion. This supports the mechanism behind the Renaissance Solutions term; Bradford uses “Brussels Effect,” not the label “Policy Leakage.”

Learn more

  • Compare deployment context with [[context-to-reality-drift|Context-to-Reality Drift]].

Public history

25 recorded events · 25 public summaries

  1. A potential shared concept was discussed and selected for initial glossary drafting.

  2. The captured candidate received a complete initial draft and entered section-level human review.

  3. Radar reviewed the initial definition draft for human consideration.

  4. Radar reviewed the initial plain-language-explanation draft for human consideration.

  5. Radar reviewed the initial why-it-matters draft for human consideration.

  6. Radar reviewed the initial example draft for human consideration.

  7. Radar reviewed the initial common-misconception draft for human consideration.

  8. Radar reviewed the initial remember-it-this-way draft for human consideration.

  9. Radar reviewed the initial related-terms draft for human consideration.

  10. Radar reviewed the initial sources draft for human consideration.

  11. Radar reviewed the initial learn-more draft for human consideration.

  12. A proposal was opened for section-level human review while preserving the current version.

  13. A human reviewer opened a proposed revision while preserving the current approved or captured version.

  14. definition approved by a human reviewer.

  15. plain-language-explanation approved by a human reviewer.

  16. why-it-matters approved by a human reviewer.

  17. example approved by a human reviewer.

  18. common-misconception approved by a human reviewer.

  19. remember-it-this-way approved by a human reviewer.

  20. related-terms approved by a human reviewer.

  21. sources approved by a human reviewer.

  22. learn-more approved by a human reviewer.

  23. All section gates are approved; content version 1 is now a fully approved term.

  24. Definition review recorded as replace.

  25. Sources review recorded as approve-proposed.

Source: vault/Glossary/terms/policy-leakage/term.md · sha256:86dafd9abd4e74886d8f9e8b02fc77c83cf55f7360e3604290fed337292d9d01 · Release: rs-glossary-glossary-team-poc-0.5.5-2026-09-02