I've been thinking about what Proof of Attribution actually changes and what it doesn't.
The idea is clean. Every time an AI model generates an output, OpenLedger traces which data trained it and who contributed. That trace becomes a payment. Every inference becomes a monetizable event for everyone in the contributor chain.
That's genuinely different from how AI economics work today. Most contributors sit outside the value loop entirely. OpenLedger is building the mechanism to change that.
What I keep coming back to is the adoption question underneath the infrastructure question.
OpenLedger is betting that data contributors and developers will choose a system that pays them over one that doesn't. That the data compensation gap is large enough that people will move toward transparent attribution once the option exists.
That bet might be correct. But crypto history also shows that financial incentives attract the behavior they reward, not always the behavior the system needs. A Datanet that pays for contributions will get contributions. Whether those contributions actually improve the models depends on quality controls that Proof of Attribution alone can't guarantee.
6 million registered nodes. 28 million transactions. 23,000 AI models.
The activity is real. The question is what quality looks like at that scale.