17 AI in policy practice
This chapter covers
- Why AI systems must not act as authorization decision-makers
- How AI assists policy authoring and design without becoming authoritative
- Using AI in runtime analysis to compare design-time intent with observed behavior
- Enforcing authorization before retrieval in RAG systems
- How architecture enables accountability and governance in AI-enabled systems
As AI systems become part of daily life, they play a bigger and bigger role in key decisions. These include what data is displayed, what actions are allowed, and who is accountable if something goes wrong. As a result, many teams are tempted to delegate authorization decisions to AI. That idea seems reasonable, but it’s usually a mistake.
Authorization exists to enforce the intent behind access decisions. It relies on determinism, explainability, auditability, and predictable failure modes. AI systems excel at many tasks, such as interpretation, synthesis, and exploration. When these strengths are applied appropriately, AI can significantly enhance the design, understanding, testing, and governance of policies without becoming the component responsible for access determination.