I’ve noticed something strange: the more confident a system sounds, the less people question it. Certainty has become a design feature. Doubt, meanwhile, sits off to the side — unpaid and ignored.

What if $MIRA flipped that dynamic?

Instead of rewarding agreement with a verified output, imagine staking on the probability that it gets overturned within 30 days. Not chaos. Not trolling. Structured skepticism. You’d be pricing the fragility of conclusions, not just their acceptance.

That changes behavior. Analysts would think twice before pushing borderline outputs. Reviewers would track weak assumptions because doubt now has a market. And if the majority consensus turns out wrong, those who identified structural cracks early capture value. In that framework, epistemic risk becomes measurable.

The uncomfortable part? It exposes how often confidence is manufactured. If a large share of verified outputs keep getting overturned, the issue isn’t volatility — it’s overconfidence baked into the pipeline. A live overturn market would surface that in real time.

Of course, speculation on reversal probability could also incentivize people to hunt for failure rather than improve quality. Designing guardrails would matter more than the headline.

Still, turning doubt into something stakeable under #MIRA forces a simple question: how stable are our conclusions, really?@Mira - Trust Layer of AI #Mira