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The idea that these were not literal predictions but theoretical examples is just laughable. If that were the case, he wouldn't have written a 150 page article desperately trying to rebut the suggestions that his predictions about 2009 weren't very accurate. ("How My Predictions Are Faring"). Or he would at least have tried to be event remotely honest with the grading.

Have a look at the document. You'll find that if you apply his reasoning for why some predictions should be considered correct, they'd already have been true at the moment he made them. Predicting in 1999 that documents will routinely embed moving images? Truly a bold prediction to make during the golden age of the animated gif banner. Computers will exist the size of a thin book? Even if no technical progress at all had happened, he could just have pointed at a 1999 Palm Pilot or GSM phone.

He also marks things that are clearly failed predictions as "correct". For example he made the claim that most students and parents would have accepted for years that software is as effective as teachers. No. Way. But he marked that as "correct" with no relevant evidence at all.




Thanks for the suggestion, have the PDF downloaded and will read. Since I haven't read it I can't comment on your rebuttals but have a follow-up question...

If we imagine a scenario where all of his predictions of applied tech are wrong but the mathematical thesis of accelerating returns is correct how would that impact your perspective on him?

My argument wasn't that he did not make literal predictions, he did and still does, but that these predictions are just his best guess based on what he observes through his demonstrated law of accelerating returns.


I’m not very familiar with his work, but when theory does not align with empirical data, does that not often indicate the theory should be revisited?

I read your link and his ideas seem very interesting. But I would think the real test of his ideas will be if the “law” he has extrapolated from observing historic phenomena like the rate of human genome processing or growth of ISP cost performance can be generally and reliably applied to predict the growth rate of new technologies.

If predictions made using the law of accelerating returns are unreliable, how useful is it?


Unlimited exponential growth is a horrible way to model anything. The real world has all kinds of limits, nothing can grow for ever. First those limits are going to be soft economic limits, slowing the rate of growth. Eventually they become hard physical ones, making growth literally impossible. It won't be exponential growth, it'll be logistic.

So the seemingly innocent "let's assume that this mathematical thesis is correct" is a pretty high bar. Unlimited growth is an exceptional claim, it needs exceptional evidence.


To be clear nothing in his model suggests unlimited. He has mentioned in his writings that it is in fact limited, but that limit may as well be unlimited for you and i (within our lifetimes)


>>he made the claim that most students and parents would have accepted for years that software is as effective as teachers

For at least 10 years now I have learned things without talking to a human teacher, so I guess that prediction was correct.


For hundreds of years humans have read printed books to learn things, without talking to teachers. Seems like a weak argument.


It isn't.

Software has enabled learning unlike any other even before in human history, the only previous time being when Gutenberg invented the printing press.

These days there isn't a thing on earth that I can't learn sitting at home. There is a huge difference.

Today only barrier to learning is your own motivation. Access to quality information has become so easy and cheap, that its hard time to blame somebody else for your failure.




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