In fairness, it would seem that simply coming up with the prediction is probably a lot of the work.
As a metaphor: it’s relatively easy to walk non-experts through a proof of Godel’s Incompleteness Theorem. The hard part is often coming up with the idea in the first place, or proving it’s correctness; simply agreeing on a proof or theory is vastly easier :)
Some of the predictions are affected by this more than others, but it’s hard to judge in any case. For example, the “nanotechnology is prevalent” hypothesis wouldn’t be that hard to locate, given that a lot of people were talking about nanotechnology at the time. Then it’s just a matter of deciding yes or no based on evidence and your model(s). On the other hand, something like his prediction that “Personal computers with high resolution interface embedded in clothing and jewelry, networked in Body LAN’s,” while wrong, is much harder to locate in the hypothesis space.
In fairness, it would seem that simply coming up with the prediction is probably a lot of the work.
As a metaphor: it’s relatively easy to walk non-experts through a proof of Godel’s Incompleteness Theorem. The hard part is often coming up with the idea in the first place, or proving it’s correctness; simply agreeing on a proof or theory is vastly easier :)
For anyone who hasn’t read it, see locating the hypothesis
Some of the predictions are affected by this more than others, but it’s hard to judge in any case. For example, the “nanotechnology is prevalent” hypothesis wouldn’t be that hard to locate, given that a lot of people were talking about nanotechnology at the time. Then it’s just a matter of deciding yes or no based on evidence and your model(s). On the other hand, something like his prediction that “Personal computers with high resolution interface embedded in clothing and jewelry, networked in Body LAN’s,” while wrong, is much harder to locate in the hypothesis space.