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.
This series describes a trend that will reshape our world, one which has already begun but about which we have no interest. It’s of no value to military contractors. Corporations profit from it, but hardly advertise they’re generating unemployment. No benefit to “big science” (they cannot warn that $billions are needed to study and mitigate it. So we’ll remain ignorant until the effects become too large to ignore.
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“Economic Growth Given Machine Intelligence“, Robin Hanson (Asst Prof Economics, George Mason U), unpublished, date unknown: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.
Economists blindingly grapple with these issues
- “Is America facing an increase in structural unemployment?“, brief answers from a range of economists, 23 July 2010
- “Identifying Cyclical vs. Structural Unemployment“, Brad DeLong (Prof Economics, Berkeley), 24 August 2010
- “A curious unemployment picture gets more curious“, Federal Reserve Bank of Atlanta, 16 July 2010
- “Labor Force Participation and the Future Path of Unemployment“, Joyce Kwok et al, Federal Reserve Bank of San Francisco, 13 September 2010
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.
- The Economic Implications of Intelligent Machines, 26 October 2009
- The Average Worker and the Average Machine, 1 July 2010
- Structural Unemployment: The Economists Just Don’t Get It, 4 August 2010
- Econometrics and Technological Unemployment — Some Questions, 6 August 2010
- Outsourcing Jobs…that Can’t be Outsourced, 27 August 2010
- Healthcare Robotics, 14 September 2010
Other posts about robots and automation
- 4GW: A solution of the first kind – Robots!, 8 April 2008
- The coming big increase in structural unemployment, 7 August 2010
- The coming Robotic Nation, 28 August 2010
- The coming of the robots, reshaping our society in ways difficult to foresee, 22 September 2010
- Economists grapple with the first stage of the robot revolution, 23 September 2012
- The Robot Revolution arrives, and the world changes, 20 April 2012
A series at Slate about robots:
“Difference Engine: Luddite Legacy“, The Economist, 4 November 2011 — Excerpt:
AN APOCRYPHAL tale is told about Henry Ford II showing Walter Reuther, the veteran leader of the United Automobile Workers, around a newly automated car plant. “Walter, how are you going to get those robots to pay your union dues,” gibed the boss of Ford Motor Company. Without skipping a beat, Reuther replied, “Henry, how are you going to get them to buy your cars?”
Whether the exchange was true or not is irrelevant. The point was that any increase in productivity required a corresponding increase in the number of consumers capable of buying the product. The original Henry Ford, committed to raising productivity and lowering prices remorselessly, appreciated this profoundly—and insisted on paying his workers twice the going rate, so they could afford to buy his cars.
… Economists see this as a classic example of how advancing technology, in the form of automation and innovation, increases productivity. This, in turn, causes prices to fall, demand to rise, more workers to be hired, and the economy to grow. Such thinking has been one of the tenets of economics since the early 1800s, when hosiery and lace-makers in Nottingham—inspired by Ned Ludd, a legendary hero of the English proletariat—smashed the mechanical knitting looms being introduced at the time for fear of losing their jobs.
Some did lose their jobs, of course. But if the Luddite Fallacy (as it has become known in development economics) were true, we would all be out of work by now—as a result of the compounding effects of productivity. While technological progress may cause workers with out-dated skills to become redundant, the past two centuries have shown that the idea that increasing productivity leads axiomatically to widespread unemployment is nonsense.
But here is the question: if the pace of technological progress is accelerating faster than ever, as all the evidence indicates it is, why has unemployment remained so stubbornly high—despite the rebound in business profits to record levels? Two-and-a-half years after the Great Recession officially ended, unemployment has remained above 9% in America. That is only one percentage point better than the country’s joblessness three years ago at the depths of the recession.
… a crucial change that economists are loth to accept, though technologists have been concerned about it for several years. This is the disturbing thought that, sluggish business cycles aside, America’s current employment woes stem from a precipitous and permanent change caused by not too little technological progress, but too much. The evidence is irrefutable that computerised automation, networks and artificial intelligence (AI)—including machine-learning, language-translation, and speech- and pattern-recognition software—are beginning to render many jobs simply obsolete.
This is unlike the job destruction and creation that has taken place continuously since the beginning of the Industrial Revolution, as machines gradually replaced the muscle-power of human labourers and horses. Today, automation is having an impact not just on routine work, but on cognitive and even creative tasks as well. A tipping point seems to have been reached, at which AI-based automation threatens to supplant the brain-power of large swathes of middle-income employees. That makes a huge, disruptive difference. Not only is AI software much cheaper than mechanical automation to install and operate, there is a far greater incentive to adopt it—given the significantly higher cost of knowledge workers compared with
their blue-collar brothers and sisters in the workshop, on the production line, at the check-out and in the field.
In many ways, the white-collar employees who man the cubicles of business today share the plight of agricultural workers a century ago. In 1900, nearly half of the adult population worked on the land. Thanks to tractors, combine harvesters, crop-picking machines and other forms of mechanisation, agriculture now accounts for little more than 2% of the working population.
Displaced agricultural workers then, though, could migrate from fields to factories and earn higher wages in the process. What is in store for the Dilberts of today? Media theorist Douglas Rushkoff (“Program or Be Programmed” and “Life Inc”) would argue “nothing in particular.” Put bluntly, few new white-collar jobs, as people know them, are going to be created to replace those now being lost—despite the hopes many place in technology, innovation and better education.
The argument against the Luddite Fallacy rests on two assumptions: one is that machines are tools used by workers to increase their productivity; the other is that the majority of workers are capable of becoming machine operators. What happens when these assumptions cease to apply — when machines are smart enough to become workers? In other words, when capital becomes labour. At that point, the Luddite Fallacy looks rather less fallacious.
This is what Jeremy Rifkin, a social critic, was driving at in his book, The End of Work, published in 1995. Though not the first to do so, Mr Rifkin argued prophetically that society was entering a new phase — one in which fewer and fewer workers would be needed to produce all the goods and services consumed. “In the years ahead,” he wrote, “more sophisticated software technologies are going to bring civilisation ever closer to a near-workerless world.”
The process has clearly begun. And it is not just white-collar knowledge workers and middle managers who are being automated out of existence. As data-analytics, business-intelligence and decision-making software do a better and cheaper job, even professionals are not immune to the job-destruction trend now underway. Pattern-recognition technologies are making numerous highly paid skills redundant.
… In 2009, Martin Ford, a software entrepreneur from Silicon Valley, noted in The Lights in the Tunnel that new occupations created by technology — web coders, mobile-phone salesmen, wind-turbine technicians and so on—represent a tiny fraction of employment. And while it is true that technology creates jobs, history shows that it can vaporise them pretty quickly, too. “The IT jobs that are now being off-shored and automated are brand new jobs that were largely created in the tech boom of the 1990s,” says Mr Ford.
In his analysis, Mr Ford noted how technology and innovation improve productivity exponentially, while human consumption increases in a more linear fashion. In his view, Luddism was, indeed, a fallacy when productivity improvements were still on the relatively flat, or slowly rising, part of the exponential curve. But after two centuries of technological improvements, productivity has “turned the corner” and is now moving rapidly up the more vertical part of the exponential curve. One implication is that productivity gains are now outstripping consumption by a large margin.
Another implication is that technology is no longer creating new jobs at a rate that replaces old ones made obsolete elsewhere in the economy. All told, Mr Ford has identified over 50m jobs in America — nearly 40% of all employment — which, to a greater or lesser extent, could be performed by a piece of software running on a computer. Within a decade, many of them are likely to vanish. “The bar which technology needs to hurdle in order to displace many of us in the workplace,” the author notes, “is much lower than we really imagine.”
In their recent book, Race Against the Machine, Erik Brynjolfsson and Andrew McAfee from MIT agree with Mr Ford’s analysis—namely, that the jobs lost since the Great Recession are unlikely to return. They agree, too, that the brunt of the shake-out will be borne by middle-income knowledge workers, including those in the retail, legal and information industries. But the authors’ perspective is from an ivory tower rather than from the hands-on world of creating start-ups in Silicon Valley. Their proposals for reform, while spot on in principle, expect rather a lot from the political system and other vested interests. …