Surely I'm not the first to think that today's technological advances have the potential to seriously disrupt the current market economy? I eventually found that Martin Ford, founder of an unnamed software development company in Silicon Valley, wrote a book in 2009: "The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future". It turns out that his analysis of the problem is exactly the same as mine... not to mention more than four years ahead of me! Ford explains it very simply and compellingly: "the free market economy, as we understand it today, simply cannot work without a viable labor market. Jobs are the primary mechanism through which income-- and, therefore, purchasing power-- is distributed to the people who consume everything the economy produces. If at some point, machines are likely to permanently take over a great deal of the work now performed by human beings, then that will be a threat to the very foundation of our economic system."
For the more visually minded, Ford graphs capability to perform routine jobs against historical time for both humans and computer technology. I reproduce this simple graph here. Ford posits that there was a spurt in human capability after the Industrial Revolution as people learned to operate machines, but that this has now largely leveled off. As a general principle, this seems reasonable. Computer technology, on the other hand is widely accepted (via Moore's Law) to be on a geometric growth path in terms of its general capability. Unless one or both trends change dramatically, the cross-over of these two lines is inevitable. When technology becomes more efficient than a human at any particular job, competitive pressure in the market will ensure that the former replaces the latter. At some stage, the percentage of human jobs and their associated income that is automated away will be enough to disrupt the consumption side of the free market. Even increased uncertainty about income is often sufficient to cause consumers to increase savings and reduce discretionary spending. This behavior occurs in every recession and affects production in a predictable manner; production is cut back, often involving further job losses. A positive feedback cycle of reduced jobs drives reduced spending and drives further job losses. In today's cyclical economy, the trend is eventually reversed, sometimes through governmental action, or at times by war--World War II is credited by some for the end of the Great Depression. However, the graph above shows no such cyclical behavior: this is a one-way, one time transition.
Of course, the 64 million dollar questions (assuming you agree with the reasoning above) are: where we are on this timeline and how steep is the geometric rise in technological capability? It is likely that both aspects differ depending on the job involved. For some jobs, we are far from the inflection point in the technology curve, while others are much closer. For information-based jobs, the rate of growth in capability of computers may be very close to the Moore's Law formulation: a doubling in capacity every 18 months. Physical automation may grow more slowly. But the outcome is assured: the lines will cross. Ford felt that in some areas we were getting close to the inflection point in 2009. The presumed approximate quadrupling of technological ability since then has not yet, however, tipped us over the edge of the job cliff, although few would argue the extent of the technological advances in the interim. Of course, Ford--and I--may be wrong.
If would seem that the hypothesis put forward by Ford should be amenable to mathematical modeling, I have found only one attempt to do so, in an academic paper "Economic growth given machine intelligence", published in 1999 by Robin Hansen. Given the title, I hoped that this paper might provide some usable mathematical models capable of answering my questions. Unfortunately, I was disappointed. My mathematical skills are no longer up to the equations involved! More importantly, however, Hansen's framing assumptions seem strong on historical precedent (surely favoring continuation of the current situation) and fail to address the fundamental issue (in my view) that consumption is directly tied to income and its distribution among the population. Furthermore, Hansen has taken a largely dismissive attitude to Ford's thesis, as demonstrated by Hansen's advice to Ford in an online exchange: "he needs to learn some basic economics".
So, the hypothesis that I and, previously, Ford have put forward so far remains both intuitively reasonable and formally unproven. For now, I ask can any data scientist / economics major take on the task of producing a useful model of our basic hypothesis.
In the final part of the series, I look at what a collapse of the current economic order might look like and ask what, if anything, might be done to avert it.
For a broader and deeper view of the business and technological aspects of this topic, please take a look at my new book: Business unIntelligence: Insight and Innovation Beyond Analytics and Big Data.
Posted February 25, 2014 3:34 AM
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