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Economists Grapple With the First Stage of the Robot Revolution

Summary:  The first signs of the robot revolution have appeared, automation moving from manufacturing into the service industries.  Economists see the evidence but cannot understand.  This post provides some explanations to this complex issue.  Links to other chapters of this series appear at the end.

Automation will allow amazing productivity growth.  This might be captured by our elites, or shared amongst the people.  But what would we do with the extra time, a world with less work?  A look at past societies:

The lives of ordinary people in the Middle Ages in Europe or in Ancient Greece or Rome may not have been easy, but they were certainly leisurely.  In the fourth century the Roman Empire had 175 public festival days.  In medieval England holidays added up to about 4 months a year; 5 months in Spain; 6 months in France.  {Source}

But in our world automation increases productivity — boosting business profits (now at record levels despite the recession) and reduces employment.  Especially as the automation wave moves from manufacturing into the far larger pool of service employment.

  • Fire bank tellers; install ATMs.
  • Fire workers in toll booths and parking lots; install automated payment systems  (e.g., FasTrak).
  • Fire cashiers; install automated check-out systems (e.g., gas stations and Home Depot).
  • Fire teachers for simple continuing education course; install online learning systems

It’s happening now, as the recession has sparked businesses to rationalize their business practices to fully utilize new technology.  The results appear in economists’ data, but they cannot see it because their dogma says it cannot happen.  They extrapolate results from the first waves of industrialization into a natural law — ignoring the probably painful effects of the transition.

Excerpts from interesting articles about the problem

Economic Growth Given Machine Intelligence“, Robin Hanson (Asst Prof Economics, George Mason U), unpublished, date unknown:

“This suggests that the transition from human dominated labor to labor dominated by machine intelligence might rather rapid. … Then in just 4 years machines could go from doing 25% to 75% of the job types, if computer prices halved every 2 years, and per-human product grew an average of 22% per year over this period.”

Economics Of The Singularity“, Robin Hanson (Asst Prof Economics, George Mason U), IEEE Spectrum, June 2008:

Our global economy would stupefy a Roman merchant as much as the Roman economy would have confounded a caveman. But we would be similarly amazed to see the economy that awaits our grandchildren, for I expect it to follow a societal discontinuity more dramatic than those brought on by the agricultural and industrial revolutions. The key, of course, is technology. A revolutionary speedup in economic growth requires an unprecedented and remarkable enabling tool. Machine intelligence on a human level, if not higher, would do nicely. Its arrival could produce a singularity–an overwhelming departure from prior trends, with uneven and dizzyingly rapid change thereafter. A future shock to end future shocks.

The Mythology of the Future Job Market“, Martin Ford, Angry Bear, 18 November 2009 — See links to his other articles below.  Excerpt:

{W}e are led to expect that, over time, the bulk of the workforce is going to migrate into jobs that require creativity or innovation, or jobs that depend on uniquely human traits or talents. Furthermore, these new jobs are going to require that any innovation, creativity or personal attention occur pretty much while actually holding onto your customer’s hand—so that the job can’t be offshored. Is that really a likely scenario?

The first thing to note is that the two sectors singled out as being promising—healthcare and education—are by no means exempt from automation. Specific healthcare tasks are likely to be automated, while decision making and patient monitoring may migrate increasingly into expert systems.

Automation is clearly going to be a major factor in specialized, vocational-type education and training. Today in California, you can get your real estate license completely online. You won’t encounter an actual human being until you run into a proctor at the licensing exam. A similar thing has happened with the traffic school programs that drivers have to complete after getting a ticket. If training can be offered online, it will be. I see no reason why something similar won’t eventually occur in college education, especially since new graduates have been seeing a lower financial return on their investment. It seems likely that if the credential is worth less, many people will gravitate toward less expensive, automated online learning.

… Historically, the job market has always looked like a pyramid in terms of worker skills and capabilities. At the top, a relatively small number of highly skilled professionals and entrepreneurs have been responsible for most creativity and innovation. The vast majority of the workforce has always been engaged in work that is fundamentally routine and repetitive. As various sectors have mechanized or automated, workers have transitioned from routine jobs in one sector to routine jobs in another. In many cases, skills have been upgraded, but the work has nonetheless remained routine in nature. So, historically, there has been a reasonable match between the types of work required by the economy and the capabilities of the available workforce.

Now, as it becomes clear that automation is going to ultimately consume the entire base of the job skills pyramid, the conventional wisdom is that we are going to somehow cram everyone into the very top. And even if we somehow manage to do that, the jobs will be highly susceptible to offshoring, so we also have to require that the jobs be somehow anchored locally. I think this is somewhat analogous to having the agricultural sector mechanize and then expecting that everyone will get a job driving a tractor. The numbers don’t work. The problem with the conventional wisdom is that it underestimates the long-term impact of automation, and it expects too much in the way of occupational acrobatics from the average worker.

Yet another problem is that even if all these creative jobs materialize, the result would likely be far from optimal. Jobs that rely heavily on creativity, talent or unique personality traits (think authors, actors, musicians, commission sales people) very often have a power law income distribution. In other words, a few people do phenomenally well, while nearly everyone else struggles to survive.

Okun’s Law and the Unemployment Surprise of 2009“, Mary Daly and Bart Hobijn, Federal Reserve Bank of San Francisco, 8 March 2010:

In 2009, strong growth in productivity allowed firms to lay off large numbers of workers while holding output relatively steady. This behavior threw a wrench into the long-standing relationship between changes in GDP and changes in the unemployment rate, known as Okun’s law. If Okun’s law had held in 2009, the unemployment rate would have risen by about half as much as it did over the course of the year. … Our results indicate that the main factor driving the unusual rise in unemployment relative to output was very rapid productivity growth, which allowed businesses to cut back sharply on labor while maintaining output levels.

… Anecdotal evidence suggests that efforts to contain costs and remain nimble in the face of uncertainty have become a fixture in business strategy. If productivity keeps on growing at an above-average pace, then unemployment forecasts based on Okun’s law could continue to be overly optimistic.

20100308-fedsf-productivity.jpg?w=428&h=340

Economists blindingly grapple with these issues

Martin Ford has some answers to these questions

Ford wrote The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future (2009); the ebook is free.

Other posts about robots and automation

  1. 4GW: A solution of the first kind – Robots!, 8 April 2008
  2. The coming big increase in structural unemployment, 7 August 2010
  3. The coming Robotic Nation, 28 August 2010
  4. The coming of the robots, reshaping our society in ways difficult to foresee, 22 September 2010

Originally published at Fabius Maximus and reproduced here with the author’s permission.

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