ONE FOR THE LUDDITES

An increasing number of economists (and of those who comment on economics) worry that new technologies, such as AI, robots, and automation more generally, will destroy more jobs than they create, making many workers obsolete and causing the share of GDP that goes to pay wages to dwindle.

In their book The Second Machine Age, our MIT colleagues Erik Brynjolfsson and Andrew McAfee offer a bleak view of the impact of digitization on the future of employment in the United States.³ Digitization, they suspect, will make workers with “ordinary” skills increasingly redundant. As tasks from car painting to spreadsheet manipulation are done by computers or robots, highly educated workers who are adaptable and can program and install the robots will become more and more valuable, but other workers who can be replaced will find themselves without jobs unless they accept extremely low salaries. In this view, artificial intelligence will be the final nail in the coffin of these ordinary workers.

In the first IT revolution, as David Autor has shown, jobs involving routine repetitive tasks were the ones that went.⁴ Jobs that required quick judgment and initiative stayed put. The number of typists and assembly-line workers diminished, but executive assistants and burger flippers kept their jobs. This time, many say, it is different. Artificial intelligence means machines can learn as they go and are therefore able to carry out increasingly nonroutine tasks, such as playing Go or folding laundry. In June 2018, a restaurant offering robot-made burgers opened in San Francisco. Humans are still taking the orders and cooking the sauces, but the robots cook the gourmet burgers, such as the Tumami Burger (“Smoked oyster aioli, shiitake mushroom sauce, black pepper and salt, pickles, onion, butter lettuce—Designed by Chef Tu, Top Chef Season 15”⁵), in five minutes and for $6.

The AI revolution is thus poised to hit people across a wide spectrum of jobs. Accountants, mortgage originators, management consultants, financial planners, paralegals, and sports journalists are already competing with some form of artificial intelligence or, if not, will soon. Cynics might say it is precisely because these more high-end jobs are on the line that we are finally talking about this, and they may be right. But AI will also hurt shelf stackers, office cleaners, restaurant workers, and taxi drivers. Based on the tasks they perform, a McKinsey report⁶ concludes that 45 percent of US jobs are at risk of being automated, and the OECD estimates that 46 percent of the workers in OECD countries are in occupations at high risk of being either replaced or fundamentally transformed.⁷

Of course, what this calculation misses is that as some tasks get automatized, and the need for humans gets relieved, people can be put to work elsewhere.

So how bad will it be on net? Economists are of course intrigued by this problem, but in this case they have entirely failed to reach a consensus. The IGM Booth panel of experts were asked their opinion of the following statement: “Holding labor market institutions and job training fixed, rising use of robots and artificial intelligence is likely to increase substantially the number of workers in advanced countries who are unemployed for long periods.” Twenty-eight percent of respondents agreed or strongly agreed with it, 20 percent disagreed or strongly disagreed, and 24 percent were uncertain!⁸

The difficulty is that doomsday (if it is coming) has not arrived.

For the time being, humans have not been made redundant. Unemployment in the United States, as we write this book in the first quarter of 2019, is at a historical low and falling.¹⁰ With more and more women joining the labor force, the share of the population in the labor force rose substantially until about 2000 (when it started to plateau or reverse).¹¹ Jobs were found for all those who wanted to work, despite rapid labor-saving technological progress.

Of course, it is true we are probably just at the very beginning of the process of AI-fueled automation. The sense that artificial intelligence is a new class of technology makes it hard to predict what it might do. Futurologists talk about a “singularity,” a dramatic acceleration of the rate of productivity growth fueled by infinitely intelligent machines, although most economists are quite skeptical that we are anywhere close to seeing something like that. But it could well be that if Gordon plays spot the robot in a few years, he will have a more exciting time.

On the other hand, while this particular wave of automation is just starting, there have been others in the past. Like AI today, the spinning jenny, the steam engine, electricity, computer chips, and computer-assisted-learning machinery all automatized and relieved the need for humans in the past.¹²

What happened then is very much what one might have expected: by replacing workers with machines on some tasks, automation has a powerful displacement effect. It makes the workers redundant. This is what happened to the skilled artisans spinning and weaving at the dawn of the industrial revolution. They were replaced by machines. And as is well known, they did not like it one bit.

Yet the Luddites were less wrong than we might assume. Their particular jobs did vanish in the industrial revolution, along with the jobs of a whole range of artisans. We are told that in the long run everything was fine, but the long run was very long indeed. Real blue-collar wages in Britain were almost halved between 1755 and 1802. Although 1802 was a particularly low year, they were on a declining trend between 1755 and the turn of the century, and it is only at the turn of the century that they started increasing again. They would recover their 1755 level only in 1820, sixty-five years later.¹³

This period of intense technological progress in the United Kingdom was also an era of intense deprivation and very difficult living conditions. The economic historian Robert Fogel showed that boys in England during this period were significantly undernourished compared even to slaves in the US South.¹⁴ The literature of the time, from Frances Trollope to Charles Dickens, describes what was happening to the economy and society with a certain amount of unmitigated horror. Those were Hard Times indeed.

We know that eventually there was a turnaround in the UK. Even as some workers lost their jobs, the labor-saving innovations raised profitability of other inputs, and hence the demand for workers producing them. Improvements in weaving technology, like John Kay’s flying shuttle, for example, increased demand for yarn, creating jobs for people to produce yarn. And the burgeoning wealth of those profiting from these innovations increased demand for new products and services in a range of sectors (more solicitors, accountants, engineers, bespoke tailors, gardeners, etc.), which created more jobs.

However, nothing tells us the rebound is guaranteed to happen. There may well be no rebound from the fall in demand for labor resulting from this wave of automation and AI. Sectors that become more profitable may invest in new labor-saving technologies instead of hiring more workers. The new wealth may be used to purchase goods made in another country.

We don’t know what will happen this time around, since we haven’t seen the very long run yet, but the impact of the current wave of automation (which started in 1990, giving us a perspective of more than twenty-five years) appears so far to be negative. In a study on the impact of automatization, researchers computed, for each region, a measure of exposure to industrial robots, capturing the spread of robots in the industries in that region.¹⁵ They then compared the evolution of employment and wages in the most affected areas to that in the least affected areas. The study found, to the surprise of the authors, who had written a previous paper emphasizing the forces that should lead to a rebound,¹⁶ large negative impacts. One more robot in a commuting zone reduces employment by 6.2 workers and also depresses wages. The employment effects are most pronounced in manufacturing and they are particularly strong for workers with lower than a college education, especially those who do routine manual tasks. However, there are no offsetting gains in employment or wages for any other occupation or educational group. These local impacts of robots on employment and wages are reminiscent of the impacts of greater exposure to international trade. They are surprising for the same reasons. As many tasks in a particular industry get automatized, we might have expected displaced workers to find employment in new businesses that would have come to the region to take advantage of the freed-up labor, or to move elsewhere. It is also worrying that the automation of simple tasks did not lead to the hiring of more engineers to supervise the robots.

Even if the total number of jobs does not fall, the current wave of automation tends to displace jobs that require some skills (bookkeepers and accountants) and increase the demand, either for very skilled workers (software programmers for the machines) or for totally unskilled workers (dog walkers, for example), which are both much more difficult to replace with a machine. As software engineers become richer, they have more money to hire dog walkers, who have become relatively cheaper over time, since there is little alternative employment for those with no college education. Even if people remain employed, this leads to an increase in inequality, with higher wages at the top and everyone else pushed to jobs requiring no specific skills; jobs where wages and working conditions can be really bad. This accentuates a trend that has taken place since the 1980s. Workers without a college education have increasingly been pushed out of mid-skill jobs, such as clerical and administrative roles, into low-skill tasks, such as cleaning and security.¹⁷