There exists a 6-sided die that is weighted such that one of the 6 numbers has a 50% chance to come up and all the other numbers have a 1 in 10 chance. Nobody knows for certain which number the die is biased in favor of, but some people have had a chance to roll the die and see the result.
You get a chance to roll the die exactly once, with nobody else watching. It comes up 6. Running a quick Bayes's Theorem calculation, you now think there's a 50% chance that the die is biased in favor of 6 and a 10% chance for the numbers 1 through 5.
You then discover that there's a prediction market about the die. The prediction market says there's a 50% chance that "3" is the number the die is biased in favor of, and each other number is given 10% probability.
How do you update based on what you've learned? Do you make any bets?
I think I know the answer for this toy problem, but I'm not sure if I'm right or how it generalizes to real life...
Has anyone rolled the die more than once? If not, it's hard to see how it could converge on that outcome unless everybody that's betting saw a 3 (even a single person seeing differently should drive the price downward). Therefore, it depends on how many people saw rolls, and you should update as if you've seen as many 3s as other people have bet.
You should bet on six if your probability is still higher than 10%.
If the prediction market caused others to update previously then it's more complicated. Probably you should assume it reflects all available information, and therefore exactly one 3 was seen. Ultimately there's no good answer because there's Knightian uncertainty in markets.