“Economics Of The Singularity: Stuffed into Skyscrapers by the Billion, Brainy Bugbots Will Be the Knowledge Workers of the Future”, 2008-06-01 (; backlinks; similar):
So we have perhaps five eras during which the thing whose growth is at issue—the universe, brains, the hunting economy, the farming economy, and the industrial economy—doubled in size at fixed intervals. Each era of growth before now, however, has eventually switched suddenly to a new era having a growth rate that was between 60 and 250× as fast. Each switch was completed in much less time than it had taken the previous regime to double—from a few millennia for the agricultural revolution to a few centuries for the industrial one. These switches constituted singularities…A few exceedingly rare innovations, however, do suddenly change everything. One such innovation led to agriculture; another led to industry.
…If current trends continue, we should have computer hardware and brain scans fast and cheap enough to support this scenario in a few decades…Though it might cost many billions of dollars to build one such machine, the first copy might cost only millions and the millionth copy perhaps thousands or less. Mass production could then supply what has so far been the one factor of production that has remained critically scarce throughout human history: intelligent, highly trained labor.
…The relative advantages of humans and machines vary from one task to the next. Imagine a chart resembling a topographic cross section, with the tasks that are “most human” forming a human advantage curve on the higher ground. Here you find chores best done by humans, like gourmet cooking or elite hairdressing. Then there is a “shore” consisting of tasks that humans and machines are equally able to perform and, beyond them an “ocean” of tasks best done by machines. When machines get cheaper or smarter or both, the water level rises, as it were, and the shore moves inland.
This sea change has two effects. First, machines will substitute for humans by taking over newly “flooded” tasks. Second, doing machine tasks better complements human tasks, raising the value of doing them well. Human wages may rise or fall, depending on which effect is stronger. Wages could fall so far that most humans could not live on them. For example, in the 1920s, when the mass-produced automobile came along, it was produced largely by machines, with human help. So machines dominated that function—the assembly of cars. The resulting proliferation of machine-assembled cars raised the value of related human tasks, such as designing those cars, because the financial stakes were now much higher. Sure enough, automobiles raised the wages of machinists and designers—in these cases, the complementary effect dominated. At the same time, the automobile industry lowered the pay of saddle makers and stable hands, an example of the substitution effect.
So far, machines have displaced relatively few human workers, and when they have done so, they have in most cases greatly raised the incomes of other workers. That is, the complementary effect has outweighed the substitution effect—but this trend need not continue. In our graph of machines and humans, imagine that the ocean of machine tasks reached a wide plateau. This would happen if, for instance, machines were almost capable enough to take on a vast array of human jobs. For example, it might occur if machines were on the very cusp of human-level cognition. In this situation, a small additional rise in sea level would flood that plateau and push the shoreline so far inland that a huge number of important tasks formerly in the human realm were now achievable with machines. We’d expect such a wide plateau if the cheapest smart machines were whole-brain emulations whose relative abilities on most tasks should be close to those of human beings.
…Together these effects seem quite capable of producing economic doubling times much shorter than anything the world has ever seen. And note that this forecast does not depend on the rate at which we achieve machine intelligence capabilities or the rate at which the intelligence of machines increases. Merely having computer-like machines able to do most important mental tasks as well as humans do seems sufficient to produce very rapid growth.