And many readers can no doubt point out many non-trivial predictions that Drexler got right, such as the idea that we will have millions of AIs, rather than just one huge system that acts as a unified entity. And we’re still using deep learning as Drexler foresaw, rather than building general intelligence like a programmer would.
One of the simpler and more important lessons one learns from research on forecasting: be wary of evaluating someone’s forecasting skill by drawing up a list of predictions they got right and wrong—their “track record.” One should compare Drexler’s performance against alternative methods/forecasters (especially for a forecast like “we’re still using deep learning”). I’m not saying this is nothing, but I felt compelled to highlight this given how often I’ve seen this potential failure mode.
I agree. Possibly an even bigger problem is that people rarely make unambiguous predictions that can be scored in the first place. If Drexler had done that, it would be much easier to compare his forecasts to others.
One of the simpler and more important lessons one learns from research on forecasting: be wary of evaluating someone’s forecasting skill by drawing up a list of predictions they got right and wrong—their “track record.” One should compare Drexler’s performance against alternative methods/forecasters (especially for a forecast like “we’re still using deep learning”). I’m not saying this is nothing, but I felt compelled to highlight this given how often I’ve seen this potential failure mode.
I agree. Possibly an even bigger problem is that people rarely make unambiguous predictions that can be scored in the first place. If Drexler had done that, it would be much easier to compare his forecasts to others.