Transparency in AI

The principle that AI systems should clearly communicate how they work, what data they use, where processing occurs, and what their limitations are. In accessibility contexts, blind users have expressed strong desires to understand how AI-enabled privacy techniques are designed, how AI systems are trained, and where obfuscation might fail. Research highlights that current transparency practices — such as vague disclaimers, beta labels, and terms of service — are insufficient, and that meaningful transparency requires concrete explanations of failure modes and limitations.