This is only a problem because we haven’t been comparing the relative “difficulty” of predictions. Admittedly this is hard to do; but I think it’s clear that:
“Intelligent roads are in use, primarily for long-distance travel.” is a much more ambitious prediction than “Local roads, though, are still predominantly conventional.”
Treating the two statements as a single prediction “A, though B” is more ambitious than either, and should be worth as many points as the two of them combined.
Moreover, any partial credit for “A, though B” would take into account that B happened though A didn’t. Or rather, a prediction that intelligent roads are only somewhat in use should receive more credit than a prediction that intelligent roads are ubiquitous.
In the future, we might distinguish “difficult” predictions from trivial ones by seeing if the predictions are unlike the predictions made by others at the same time. This is easy to do if we evaluate contemporary predictions.
But I have no idea how to accomplish this when looking back on past predictions. I can’t help but to feel that some of Kurzweil’s predictions are trivial, yet how can we tell for sure?
This is only a problem because we haven’t been comparing the relative “difficulty” of predictions. Admittedly this is hard to do; but I think it’s clear that:
“Intelligent roads are in use, primarily for long-distance travel.” is a much more ambitious prediction than “Local roads, though, are still predominantly conventional.”
Treating the two statements as a single prediction “A, though B” is more ambitious than either, and should be worth as many points as the two of them combined.
Moreover, any partial credit for “A, though B” would take into account that B happened though A didn’t. Or rather, a prediction that intelligent roads are only somewhat in use should receive more credit than a prediction that intelligent roads are ubiquitous.
Agreed that understanding the “difficulty” of a prediction is key if we’re going to evaluate the reliability of a predictor in a useful way.
In the future, we might distinguish “difficult” predictions from trivial ones by seeing if the predictions are unlike the predictions made by others at the same time. This is easy to do if we evaluate contemporary predictions.
But I have no idea how to accomplish this when looking back on past predictions. I can’t help but to feel that some of Kurzweil’s predictions are trivial, yet how can we tell for sure?