AI Trust Calibration

The process of aligning a user's level of trust in an AI system with the system's actual reliability and capabilities. In accessibility contexts, trust calibration is critical because blind and low vision users of AI-powered visual access tools tend to over-trust AI-generated image descriptions—perceiving them as more reliable than they actually are. Effective trust calibration helps users develop accurate mental models of when AI is likely to be correct versus when it may be wrong, enabling them to make informed decisions about when to rely on AI output and when to seek verification. Techniques for trust calibration include surfacing variations across multiple AI responses, showing confidence indicators, and providing provenance information about which models agree or disagree.