This research challenges the conventional wisdom that AI systems must explain themselves to be trusted, arguing instead that trust may sometimes precede explanation.

• Trust as prerequisite: In some cases, humans must trust AI before explanations are possible
• Explanation limitations: Formal modeling shows explanations can fail even under ideal conditions
• Security implications: Default trust in AI without verification creates significant security vulnerabilities
• Knowledge networks: Explanation success depends on finding paths through shared conceptual understanding

For security professionals, this research highlights critical blind spots in AI deployment strategies where users may inevitably trust systems before understanding them, requiring new approaches to responsible AI implementation.

Why Trust in AI May Be Inevitable