http://www.asymptosis.com/can-rich-people-provide-all-the-necessary-demand.html

I feel many of your questions are indeed worth more serious consideration. To me it appears that we’ve propped up effective demand (ability to pay) with a combination of redistribution and easy credit, and we’re finding that the easy credit solution only goes so far.

http://www.google.com/search?hl=en&q=define%3Adeserts&sourceid=navclient-ff&rlz=1B7GGLL_enUS365US365&ie=UTF-8

The lifting of the computational limit meant that humans were increasingly unnecessary in production (’supply’). The effects were small at first, and the concurrent elimination of the costs of information (also enabled by the transistor and increase in computational power) masked it, but improving computational power and better algorithms have resulted in it being able to take on an increasing number of roles in production and in the computational side of creativity. Hence, due to what I have already laid out in another post, there are no longer any limits to supply or controls on creative pursuits. We now have the problem that we have far too much information and have not developed the tools to evaluate or sort it. Therefore, investors and creators have no negative signal and can continue pursuing activities and novel ideas way beyond what is prudent. Until those mechanisms are developed (and they will be), we are likely to see a continuing series of bubbles driven in large part by the unconstrained application of innovation (innovation itself will be hindered by information overload).

In the mean time, people who normally filled computational roles are increasingly displaced (United States manufacturing share is about equivalent to its share in 1980 even while its work force has dropped significantly). Those who are able to fill more creative or highly skilled human service rolls will (we’ll likely see an increasing amount of innovation in all sectors of the economy due to this, but also more competition at the top). Whereas those who are incapable of providing either of these roles will increasingly compete for the dwindling number of production computational roles that are not readily automated and low skilled human services positions (which society doesn’t require enough of to take in all of those displaced in production), hence the massive rise in the services sector in the last couple decades.

As a side note, fiscal and monetary policy will likely become increasingly ineffective as a means to create jobs due to supply’s increasing independence from the human population.

Human economic activity can be broken down into three primary areas:

A. Production – the acquisition and fashioning of resources to create items of value as well as distributing them

B. Creative/Problem Solving – the creation of novel ideas and tools as well as fixing problems in both tools and society as well as directing the distribution of resources

C. Human services – dealing with, helping, controlling, and administering people

For almost all of human history, people were primarily focused on A. The acquisition and creation of the means of survival, namely food, was their highest priority.

The three economic activities can be further broken down in to their primary inputs:

Production: Energy, labor (the work necessary to produce something of value), and computation (the execution of a series of logical steps for a desired result)

Creativity/Problem Solving: Information (the gathering and communication of novel data and ideas), computation (the aggregation and transformation of data into a usable form), and creativity (the generation of new, useful ideas)… See More

Human Services – Information (data on human desires and states), human interaction

Again, most human economic activity was focused on production (primarily energy in the form of food), although people did stray into the other two from time to time.

Up until the industrial revolution people were primarily limited to producing food. The industrial revolution made people unnecessary for the energy and labor parts of production, but they were still critical for computation. Since society’s food needs are finite the massive boost in farm production made having large numbers of people unnecessary. This freed them up for industry (and other activities such as creativity and human services) where machines were able to provide energy and labor, but computation was still critical. Demand is also far less finite and the new machines and energy sources opened up entire new areas of demand. Therefore, society was able to redeploy the population into a computational role in a vastly expanded economy (not over night mind you, it took the better part of two centuries and some would say longer). This defined the social/economic order up until the late 1970’s/early 1980’s (the industrial order).

The invention of the transistor is, along with realizing seeds can be grown into plants, the single most important invention in human history. Scientific and technological advancement was requiring more and more computation, something humans tend to be inefficient at. The first artificial computers were huge, slow, and limited. This kept them constrained to a few niche applications. The transistor was initially like this, too limited due to its size, but it could be made smaller, much, much smaller. For a time, shrinking it simply broadened the number of niche applications it could be used for. In the late 1970’s it became small enough (and thereby powerful enough) to begin filling computational roles held by humans. The computational limit had been lifted and this marked the end of the industrial era.

*Very* good point, which I had not brought up. Spectacularly efficient cognitive sorting since 1900, and especially post-war, while the waterline rises.

At this time, in the United States, this sorting is mostly finished (although it is by no means perfect) as judged by decreasing social mobility. Most of those that could benefit from much greater access to education (it wasn’t really ‘improved’) have benefited. Now we’re going to see an increasingly widening gap between ‘haves’ (creative elite) and ‘have nots’ (people who would have traditionally filled computational roles) and accelerating social problems associated with it.

This is all feeding the feeling that many seem to have: that some fundamental aspect(s) of the economic dynamic have changed since the 70s, at least in the U.S. (And that it’s not all due to the 30-year hegemony of Reaganomics–though I believe that has exacerbated the effects.)

It strikes me that the increase in technology (capacity and distribution) vis-a-vis human cognitive capacities may be a key aspect. Because human cog caps don’t change much, and tech obviously does.

Improved education maintained the ratio for most of the twentieth century. Can it continue to do so? Has it, since the 70s? The numbers suggest “maybe not.” If not, will increasing numbers of people fall below the waterline?

If as a society we’re hitting this cognitive limit (which was not true when the Luddites held sway, or for the past 200 years), that fact may answer the challenge of The Luddite Fallacy.

Which I guess would make it the Luddite Fallacy Fallacy…

I personally think we’re undergoing two simultaneous technological revolutions. The first is that machines are increasingly able to challenge people in the one major remaining role they have in production – computation (which is also critical in other areas). Thereby humans are no longer necessary for supply (I would date this to the late 70’s early 80’s, the peak of American manufacturing employment). The second is that information has essentially become free (Generating novel information still has a price).

I would suggest that both of these are a major cause of the series of bubbles we’re undergoing. Since people are no longer necessary for supply, the number of people employed can no longer serve as a check on the economic growth (in the industrial era, supply was bounded by how many people you could find to fulfill the requisite computational rolls). It can grow regardless, therefore a valuable signal to investors and ‘creators’ has been lost. Combined to that, novel ideas (‘memes’) can be spread and implemented quickly, but we have yet to develop ways to properly evaluate them (kept in check in the past by the cost of preserving and distributing distributing it). One idea can cause growth, people know about it and before long everyone is adopting it before all of its implications are understood. Therefore, it is used in excess without any of the traditional brakes until the flaws in the idea(s) aggregate and the system becomes too unstable.