AI hallucinations are just errors. Bias shapes what we see, how it's framed, and what gets emphasized. It’s subtle, systemic, and impossible to eliminate in centralized systems. That’s the problem @Mira_Network is solving. Most AI today is controlled by a small group of centralized organizations, mostly in the US and China. Even with good intentions, their cultural and political perspectives define how AI behaves. That’s baked into training data, alignment, and output moderation. Mira’s solution: Use crypto-economic incentives to distribute verification and make AI accountability trustless. Instead of trusting a team to moderate outputs, you rely on diverse participants who stake real value to verify them. If they manipulate, they lose. If they align honestly, they get rewarded. This creates neutral outcomes from market forces, not from authority. Mira’s framework uses multiple AI models with different perspectives. When they agree, the output reflects broad consensus. When they disagree, it exposes cultural or ideological divergence, making the bias visible instead of hidden. This approach will: - Reduce polarization - Surface nuance - Promote global representation - Enable autonomous systems that self-verify - Remove the need for centralized moderation The goal isn’t to make AI free of values (that’s not realistic). It’s to prevent any single set of values from dominating global information. Mira’s crypto-economic design isn’t the final solution today, but it’s one of the most credible attempts we’ve seen to build scalable, unbiased AI infrastructure.