I personally put weight on this type of scenario, namely, that progress might stall and then resume once some complementary supply-side and demand-side innovations have been made and other economic progress has happened to support more investment in the area.
Yeah, so do I.
I’m not sure it makes a lot of difference in terms of long run predictions, though. Let’s say that for the next 10 years, we cut the amount of research we are doing into computers in half in percentage terms (so instead of putting X% of our global GDP into computer research every year, we put X/2%.) Let’s say we take that and instead invest it in other forms of growth (other technologies, biotech, transhuman technologies, science, infrastructure, or even bringing the third world out of poverty and into education, ect) and maintain the current rate of global growth. Let’s further say that the combination of global GDP growth and science and technology growth is roughly 7% a year, so that the global economy is doubled every 10 years in how much it can devote to research. And then at the end of that period, computer research goes back up to X%.
In that case, that 10 year long research slowdown would put us getting to where we “should” have been in computer science in 2044 now happening in 2045 instead; if that’s the point we need to be at to get a singularity started, then that 10 years long research slowdown would only delay the singularity by about 1.75 years. (edit: math error corrected)
And not only that, after a 10 year slowdown into computer science research, I would expect computers to become the new “low hanging fruit”, and we might end up devoting even more resources to it at that point, perhaps eliminating the time loss all together.
Basically, so long as exponential growth continues at all, in technological and economic terms in general, I don’t think the kind of slowdown we’re talking about would have a huge long-term effect on the general trajectory of progress.
As a general observation, you don’t want to model growth (of any sort) as X% per year. You want to model it as a random variable with the mean of X% per year, maybe, and you want to spend some time thinking about its distribution. In particular, whether that distribution is symmetric and how far out do the tails go.
Yeah, so do I.
I’m not sure it makes a lot of difference in terms of long run predictions, though. Let’s say that for the next 10 years, we cut the amount of research we are doing into computers in half in percentage terms (so instead of putting X% of our global GDP into computer research every year, we put X/2%.) Let’s say we take that and instead invest it in other forms of growth (other technologies, biotech, transhuman technologies, science, infrastructure, or even bringing the third world out of poverty and into education, ect) and maintain the current rate of global growth. Let’s further say that the combination of global GDP growth and science and technology growth is roughly 7% a year, so that the global economy is doubled every 10 years in how much it can devote to research. And then at the end of that period, computer research goes back up to X%.
In that case, that 10 year long research slowdown would put us getting to where we “should” have been in computer science in 2044 now happening in 2045 instead; if that’s the point we need to be at to get a singularity started, then that 10 years long research slowdown would only delay the singularity by about 1.75 years. (edit: math error corrected)
And not only that, after a 10 year slowdown into computer science research, I would expect computers to become the new “low hanging fruit”, and we might end up devoting even more resources to it at that point, perhaps eliminating the time loss all together.
Basically, so long as exponential growth continues at all, in technological and economic terms in general, I don’t think the kind of slowdown we’re talking about would have a huge long-term effect on the general trajectory of progress.
As a general observation, you don’t want to model growth (of any sort) as X% per year. You want to model it as a random variable with the mean of X% per year, maybe, and you want to spend some time thinking about its distribution. In particular, whether that distribution is symmetric and how far out do the tails go.