The credibility crisis of AI stems from a fundamental problem: we cannot truly verify its outputs. Machine learning models produce conclusions, but the process is a black box—no one knows how it reasons or whether the data is accurate.

This is precisely the pain point that some Web3 projects aim to solve. Through on-chain verification and distributed consensus mechanisms, every step of AI's reasoning can be traced and validated. Turning model outputs into auditable facts rather than promises hanging in the air.

In other words, transparency and verifiability are the way to reshape human trust in AI.