I was thinking about your Thirdness solution of "betting" on the outcome of any given event. Could the data an AI or algorithm be trained, from establishing these betting servicing, through the "winners" always having to provide their reasons for thinking they'd win. Over time this should provide a robust dataset that AI could pinpoint the common themes at an increasingly granular level (e.g. when in this situation, people from this or that background have a lower or higher likelihood of this and that outcome).
Yes, but the betting will be on the judgments made by the Thirdness team, which will always be parallel or "adjacent" to actual events. I don't see a way of making it work with betting on events, beyond ones with formalized closure, like elections, games, verdicts, exchange rates, etc., which is both very limiting and not very illuminating. Think of it in terms of betting on people playing video games or, maybe on the decision to made by a jury, but in this case a "virtual" jury constructing its own "cases" so as to make things difficult for itself. This would, I think, indeed produce robust databases and everything else you're pointing to. The Thirdness team would write up the reasons for its decisions but bettors could be incentivized to do so as well.