it's only a temporary extension before the exponential starts stagnating
In Little Science, Big Science Derek J de Solla Price does a great job talking about stagnation of exponential scientific growth curves. In general, an exponential growth curve must flatten at some point. He did things like look at the number of scientists in relation to the population. A quote:
It is clear that we cannot go up another two orders of magnitude as we have climbed the last five. If we did, we should have two scientists for every man, woman, child, and dog in the population, and we should spend on them twice as much money as we had. Scientific doomsday is therefore less than a century distant. -Derek J De Solla Price
It's been years since I read it, (and it's a good 50 years old) but I remember it was a good book, that was one of the founders of scientometrics. I would definitely recommend.
Ray Kurzweil's writings are the best-known expression of Singularity memes, so I figured it's about time I read his 2005 best-seller The Singularity is Near.
Though earlier users of the term "technological Singularity" used it to refer to the arrival of machine superintelligence (an event beyond which our ability to predict the future breaks down), Kurzweil's Singularity is more vaguely defined:
Kurzweil says that people don't expect the Singularity because they don't realize that technological progress is largely exponential, not linear:
Kurzweil has many examples:
He emphasizes that people often fail to account for how progress in one field will feed on accelerating progress in another:
Kurzweil's second chapter aims to convince us that Moore's law of exponential growth in computing power is not an anomaly: the "law of accelerating returns" holds for a wide variety of technologies, evolutionary developments, and paradigm shifts. The chapter is full of logarithmic plots for bits of DRAM per dollar, microprocessor clock speed, processor performance in MIPS, growth in Genbank, hard drive bits per dollar, internet hosts, nanotech science citations, and more.
The chapter is a wake-up call to those not used to thinking about exponential change, but one gets the sense that Kurzweil has cherry-picked his examples. Plenty of technologies have violated his law of accelerating returns, and Kurzweil doesn't mention them.
This cherry-picking is one of the two persistent problems with The Singularity is Near. The second persistent problem is detailed storytelling. Kurzweil would make fewer false predictions if he made statements about the kinds of changes we can expect and then gave examples as illustrations, instead of giving detailed stories about the future as his actual predictions.
My third major issue with the book is not a "problem" so much as it is a decision about the scope of the book. Human factors (sociology, psychology, politics) are largely ignored in the book , but would have been illuminating to include if done well — and certainly, they are important for technological forecasting.
It's a big book with many specific claims, so there are hundreds of detailed criticisms I could make (e.g. about his handling of AI risks), but I prefer to keep this short. Kurzweil's vision of the future is more similar to what I expect is correct than most people's pictures of the future are, and he should be applauded for finding a way to bring transhumanist ideas to the mainstream culture.