This was basically taking the 2009 graph and skewing it to the right, pivoting on Undecided. It was still too optimistic.
True: 15-20% vs 12% Weakly True: 8-12% vs 12% Undecided: 8-12% vs 10% Weakly False: 20-25% vs 15% False: 35-45% vs 50%
Looking at the discrepancy, it doesn’t seem like any systematic skewing adjustment, i.e. adjusting for overconfidence, would have gotten good results. (The closest would be one that pivoted on ‘Weakly False’.) A better model would be assuming that all predictions had a modest chance of being other-than-totally-false which was uniformly distributed over degree of truth, and most were totally false.
Therefore, I predict that if these predictions are examined again in 10 or 20 year’s time, they will still have this uniform distribution over degree of truth property, though presumably a higher chance of not being totally false.
prediction after seeing the 2009 graph:
15-20% True
8-12% Weakly True
8-12% Undecided
20-25% Weakly False
35-45% False
This was basically taking the 2009 graph and skewing it to the right, pivoting on Undecided. It was still too optimistic.
True: 15-20% vs 12%
Weakly True: 8-12% vs 12%
Undecided: 8-12% vs 10%
Weakly False: 20-25% vs 15%
False: 35-45% vs 50%
Looking at the discrepancy, it doesn’t seem like any systematic skewing adjustment, i.e. adjusting for overconfidence, would have gotten good results. (The closest would be one that pivoted on ‘Weakly False’.) A better model would be assuming that all predictions had a modest chance of being other-than-totally-false which was uniformly distributed over degree of truth, and most were totally false.
Therefore, I predict that if these predictions are examined again in 10 or 20 year’s time, they will still have this uniform distribution over degree of truth property, though presumably a higher chance of not being totally false.
Strong upvote for writing your own predictions before seeing the 2019 graph.