(These are excerpts from my book "Intelligence is not Artificial")
Jobs in the Age of the Robot - Part 1: What Destroys Jobs
During the Great Recession that ravaged the Western world in 2008-2011, both analysts and ordinary families were looking for culprits to blame for the high rate of unemployment, and automation became a popular one in the developed world. Automation was indeed responsible for making many jobs obsolete, but it was not the only culprit nor the main one.
The first and major factor that accounts for the demise of many jobs in the Western world is the end of the Cold War. Before 1991 the economies that really mattered were a handful (USA, Japan, Western Europe). Since 1991 the number of competitors for the industrialized countries has skyrocketed, and they are becoming better and better at competing with the West. Technology might have "stolen" some jobs, but that factor pales by comparison with the millions of jobs that were exported to Asia. In fact, if one considers the totality of the world, an incredible number of jobs have been created precisely during the period in which critics argue that millions of jobs have been lost to automation. If Kansas loses one thousand jobs but California creates two thousand, we consider it an increase in employment. These critics make the mistake of using the old nation-based logic for the globalized world. When counting jobs lost or created during the last twenty years, one needs to consider the entire interconnected economic system that spreads all over the planet. Talking about the employment data for the USA but saying nothing about the employment data (over the same period) of China, India, Mexico and so forth is distorting the picture. If General Motors lays off one thousand employees in Michigan but hires two thousand in China, it is not correct to simply conclude that "one thousand jobs have been lost". If the car industry in the USA loses ten thousand jobs but the car industry in China gains twenty thousand, it is not correct to simply conclude that ten thousand jobs have been lost by the car industry. In these cases jobs have actually been created.
That was precisely the case: millions of jobs were created by the USA in the rest of the world while millions were lost at home. The big driver was not automation but, on the contrary, cheap labor.
Then there are sociopolitical factors. Unemployment is high in Western Europe, especially among young people, not because of technology but because of rigid labor laws and government debt. A company that cannot lay off workers is reluctant to hire any. A government that is indebted cannot pump money into the economy. This is a widespread problem in the Western economies of our age. It has to do with politics, not with automation.
Germany is as technologically advanced as the USA. All sorts of jobs have been fully automated. And, still, in Germany the average hourly pay has risen five times faster between 1985 and 2012 than in the USA. This has little to do with automation: it has to do with the laws of the country. Hedrick Smith's "Who Stole the American Dream?" (2012) lays the blame on many factors, but not on automation.
In 1953 Taiichi Ohno invented "lean manufacturing" at Japan's Toyota, possibly the most important revolution in manufacturing since Ford's assembly line. Nonetheless, Japan created millions of jobs in manufacturing; and, in fact, Toyota went on to become the largest employer in the world of car-manufacturing jobs. Even throughout its two "lost decades" (1991-2010) Japan continued to post very low unemployment. Japan has perhaps the highest number of industrial robots of any country, and it also enjoys one of the lowest unemployment rates in the world. Germany is a close second in automation, and it has the lowest unemployment of any major country in Western Europe.
Another major factor that accounts for massive losses of jobs in the developed world is the management science that emerged in the 1920s in the USA. That science is the main reason that today companies don't need as many employees as comparable companies employed a century ago. Each generation of companies has been "slimmer" than the previous generation. As those management techniques get codified and applied across all departments, companies become more efficient at manufacturing (world-wide), at selling (using the most efficient channels) and at predicting business cycles. All of this results in fewer employees not because of automation but because of optimization.
In May 2016 Challenger, Gray & Christmas estimated the companies that had laid off the most workers. The top job cutter of the first four months of 2016 was National Oilwell Varco, a Texan company making equipment for the petroleum industry. Job cutters #3 (Schlumberger), #5 (Halliburton), #7 (Chevron) and #10 (Weatherford) were all involved in the petroleum business. This had nothing to do with robots or artificial intelligence but simply with record-low oil prices. Walmart was the second job cutter in the country, but, like all retail chains, its problem was simply the competition from online sales. Meanwhile, the US economy was adding about 200,000 new jobs each month, and those jobs were consistently in high-tech sectors. Intel (#4) and Dell (#6) too were in that list. Both missed the mobile revolution and were being replaced by other firms. Their job cutting was not due to more automation in the factories.
Additionally, in the new century the USA has deliberately restricted immigration to the point that thousands of brains are sent back to their home countries even after they graduated in the USA. This is a number that is virtually impossible to estimate, but, in a free market like the USA that encourages innovation and startups, jobs are mostly created via innovation, and innovation comes from the best brains, which account for a tiny percentage of the population. Whenever the USA sends back or refuses to accept a foreign brain that may become one of those creators of innovation, the USA is de facto erasing thousands of future jobs. Those brains are trapped in places where the system does not encourage the startup-kind of innovation or where capital is not as readily available. They are wasted in a way that equivalent brains were not wasted in the days when immigration into the USA was much easier, up until the generation of Yahoo, eBay and Google. The "Kauffman Thoughtbook 2009" by the Kauffman Foundation contains a study that foreign-born entrepreneurs ran 24% of the technology businesses started between 1980 and 1998 (in Silicon Valley a staggering 52%). In 2005 these companies generated $52 billion in revenue and employed 450,000 workers. In 2011 a report from the Partnership for a New American Economy found that 18% of the Fortune 500 companies of 2010 were founded by immigrants. These companies had combined revenues of $1.7 trillion and employed millions of workers. If one includes the Fortune 500 companies founded by children of immigrants, the combined revenues were $4.2 trillion in 2010, greater than the GDP of any other country in the world except China and Japan.
Technology is certainly a factor, but it can go either way. Take, for example, energy. This is the age of energy. Energy has always been important for economic activity but never like in this century. The cost and availability of energy are major factors to determine growth rates and therefore employment. The higher the cost of energy, the lower the amount of goods that can be produced, the lower the number of people that we employ. If forecasts by international agencies are correct, the coming energy boom in the USA (see the International Energy Agency's "World Energy Outlook" of 2012) will create millions of jobs, both directly and indirectly. That energy boom is due to new technology.
When the digital communication and automation technologies first became widespread, it was widely forecasted a) that people would start working from home and b) that people would not need to work as much. What i have witnessed is the exact opposite: virtually every company in Silicon Valley requires people to show up at work a lot more than they did in the 1980s, and today virtually everybody is "plugged in" all the time. I have friends who check their email and text messages all the time while we are driving to the mountains and even while we are hiking. The digital communication and automation technologies have not resulted in machines replacing these engineers but in these engineers being able to work all the time from everywhere, and sometimes their companies require it. Those technologies have resulted in people working a lot more. (The willingness of people to work more hours for free is another rarely mentioned factor that is contributing to higher unemployment).
At the end of 1994 Netscape released the first major browser for the World-wide Web and within a few years the web had become a center of e-commerce. Since then there has been a steady exodus of jobs from the "brick-and-mortar" economy. Jobs were lost in post offices, bookstores, photo shops, stationery shops, travel agencies, newspapers/magazines, record stores, music labels... you name it. It was a slaughter. I have never seen a total number but it certainly affected tens of millions of workers, as the entire economy was redesigned in just about 20 years. And, still, 23 years later (and despite two massive economic recessions) the unemployment rate in the USA stands at 4.4%, lower than it was in 1994 (6.1%) I strongly doubt that Artificial Intelligence will cause as many job losses as the dotcom revolution did, especially if its impact will be felt mainly among white-collar workers, who are a much smaller group than the groups replaced by the dotcoms.
It is misleading to say that Artificial Intelligence is automating or will automate "white-collar" jobs. In reality, Artificial Intelligence is doing very little, and certainly very little that qualifies as "intelligent". The change is happening in the jobs themselves: they are becoming more and more structured. They are becoming routine. The expression "White collar" evokes the image of someone who is thinking, but increasingly these white-collar workers are performing trivial tasks that simply require following some rules. The insurance agent or the bank loan agent are typical examples. These used to be professions that required a lot of skills, a lot of intuition and a lot of knowledge. Now they are performed by people with little or no education who simply enter your data into a computer and press a button to get an answer. Any job that becomes a routine can easily be automated. You don't need to call it "artificial intelligence": "automation" suffices. White-collar jobs can be automated just like blue-collar jobs when they become as repetitive and unimaginative as blue-collar jobs. What has improved is not the technology, but the standardization of white-collar work.
India is a particularly vulnerable economy because so many of its I.T. jobs (white-collar jobs) are about routine work that can be easily automated. It hasn't been automated before mainly because it was cheaper to offsource the routine to Indians than to machines. As software gets cheaper and better, and Indian workers demand higher salaries, those jobs become very vulnerable.
According to a 2017 survey by the European Commission, 80% of Swedes are optimistic about robots and Artificial Intelligence, whereas, according to a survey by the Pew Research Center, 72% of US citizens are “worried” about robots. The different psychological reactions are probably due more to the health care system than anything else. If a robot steals your job in Sweden, the state will take of you, including your health insurance. You are neither going to die nor going bankrupt to pay hospital bills. In fact, education is mostly free: your children will still have the same chance to attend a top university, and you will have a chance to attend a training program while enjoying generous unemployment benefits. In the USA the situation is the exact opposite: most workers depend on employers for health insurance, and sending their children to school is extremely expensive, and therefore these workers can be legitimately alarmed that a robot may take their job. The socialist regime of Sweden is making people more willing to experiment with their jobs. The backwards regime of the USA makes people extremely conservative about their jobs: voters don't demand jobs, they demand their existing jobs (forever) even if it's coal mining (one of the most terrible jobs on the planet).
The fear of automation dates from the dawn of machines. In 1921 the New York Times featured a book review titled "Man Devoured by His Machines." In 1961 Time magazine ran a story titled "The Automation Jobless" (24 February). In 1980 the New York Times carried a story titled "A Robot is After Your Job" (3 September). In 2009 Mike Konczal wrote in The Atlantic the piece "Robots and the Future of Unemployment".
One of the least prescient books ever written on jobs is Jeremy Rifkin's "The End of Work" (1995) that predicted worldwide unemployment due to the automation of jobs in the manufacturing, agricultural and service sectors. Twenty years later millions of jobs have been created, and high unemployment is a chronic problem only in countries with relatively little automation like Greece.
A 2017 study by Robert Atkinson and John Wu of the Information Technology and Innovation Foundation titled "False Alarmism: Technological Disruption and the U.S. Labor Market, 1850-2015" (that examined 165 years of labor history in the USA) found that technology is disrupting fewer (not more) jobs than usual. In 2017 Greg Ip wrote a piece in the Wall Street Journal titled "Robots Aren't Destroying Enough Jobs" that argues (quote): "Economic predictions of massive job losses to automation are missing indicators that show just the opposite". JP Morgan's report "Big Data and A.I. Strategies" of May 17 outlines the army of people that will be needed by corporations to acquire, sort out and label data, and, in particular, lists more than 40 programming languages that the data center of the near future will need to master.
All the predictions of a job apocalypse have been proven wrong over and over again, so much so that in 2015 the MIT economist David Autor felt he had to write an article titled "Why Are There Still So Many Jobs?"
There is an evil, but it is not the machine per se. Marx already realized this 150 years ago. The Luddites were British workers who protested against the machines that were stealing their jobs. The rebellion started in 1811 and lasted until 1817, when six of their leaders were hanged. The Luddites were terrified by the power-loom, a machine that, like the computer of two centuries later, could be programmed to weave any pattern through the use of punched cards. Karl Marx, who was born the year after the Luddite rebellion ended, criticized the Luddites in his book "The Capital" (1867) because they fought the machines instead of fighting the way in which society (namely the capitalist) was using them.
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