Some people are expressing concern that many people could lose their jobs in coming years due to automation. We are already seeing this in certain industries, especially in manufacturing. It is sometimes said that manufacturing is in decline in the United States and Canada. However, in the United States at least, production has been rising. The 2015 report The Myth and the Reality of Manufacturing in America cites numbers by the U.S. Bureau of Economic Analysis showing that manufacturing production increased by 17.6% from 2006 to 2013, despite an 11.5% drop from 2006 to 2009 due to the “Great Recession”. However, the number of jobs in the sector has been in decline- and clearly this decline is not wholly due to companies moving factories to lower wage countries, because if it was production wouldn’t be increasing in the United States. So what’s happening?
According to the authors of The Myth and the Reality of Manufacturing in America, the answer is productivity. We can define productivity simply here by saying it’s the ratio of stuff produced to the number of workers involved in producing it. From 2000 to 2010, production per worker increased by 67.5%. Without this increase in productivity, 2010 levels of production would have required employing 20.3 million U.S. Workers. Instead, only 12.1 million were employed – down from 17.7 million ten years earlier.
This increase in productivity appears to be mainly due to automation. It is true, as some point out, that while historically automation has eliminated many jobs, it has also freed people up to do other jobs. That is why many more people are employed now than before the Industrial Revolution. For example, The Economist notes that
“automated teller machines (ATMs) might have been expected to spell doom for bank tellers by taking over some of their routine tasks, and indeed in America their average number fell from 20 per branch in 1988 to 13 in 2004, (James) Bessen notes. But that reduced the cost of running a bank branch, allowing banks to open more branches in response to customer demand. The number of urban bank branches rose by 43% over the same period, so the total number of employees increased. Rather than destroying jobs, ATMs changed bank employees’ work mix, away from routine tasks and towards things like sales and customer service that machines could not do. “ (The Economist, June 2016).
The problem is that a lot of the jobs people have been “freed up to do” by being shed by an automating manufacturing sector have lower pay and fewer benefits. Worse, many of those “routine” jobs may themselves be lost to automation in coming years:
What determines vulnerability to automation, experts say, is not so much whether the work concerned is manual or white-collar but whether or not it is routine. Machines can already do many forms of routine manual labour, and are now able to perform some routine cognitive tasks too.
In a widely noted study published in 2013, Carl Benedikt Frey and Michael Osborne examined the probability of computerisation for 702 occupations and found that 47% of workers in America had jobs at high risk of potential automation. In particular, they warned that most workers in transport and logistics (such as taxi and delivery drivers) and office support (such as receptionists and security guards) “are likely to be substituted by computer capital”, and that many workers in sales and services (such as cashiers, counter and rental clerks, telemarketers and accountants) also faced a high risk of computerisation. They concluded that “recent developments in machine learning will put a substantial share of employment, across a wide range of occupations, at risk in the near future.” Subsequent studies put the equivalent figure at 35% of the workforce for Britain (where more people work in creative fields less susceptible to automation) and 49% for Japan. (The Economist, June 2016).
The Economist article concludes:
pretty much everyone agrees on the prescription: that companies and governments will need to make it easier for workers to acquire new skills and switch jobs as needed. That would provide the best defense in the event that the pessimists are right and the impact of artificial intelligence proves to be more rapid and more dramatic than the optimists expect.
Here’s the problem – there is little sign that companies and governments have much interest in spending the money needed, or when they do, have much of an idea of how to do it effectively. In some cases it’s not really going to be possible anyway. What exactly are these workers going to be retraining to do? There may be demand for more computer graphic artists and surgeons, but a 55 year old who’s been working in a machine shop for 40 years isn’t going to be filling any of those vacancies.
So what do we do to keep a large number of people from being left out in the cold?