Automation and the Future of Work. Aaron Benanav
losses.3
In making their case, automation theorists often point to the manufacturing sector as the precedent for what they imagine is beginning to happen in services. In manufacturing, the employment apocalypse has already taken place.4 To evaluate these theorists’ claims, it therefore makes sense to begin by looking at what role automation has played in that sector’s fate. After all, manufacturing is the area most amenable to automation, since on the shop floor it is possible to “radically simplify the environment in which machines work, to enable autonomous operation.”5 Industrial robotics has been around for a long time: the first robot, the “Unimate,” was installed in a General Motors plant in 1961. Still, until the late 1960s, scholars studying this sector were able to dismiss out of hand Luddite fears of long-term technological unemployment. Manufacturing employment grew most rapidly precisely in those lines where technical innovation was happening at the fastest pace, because it was in those lines that prices fell the fastest, stoking the growth of demand for products.6 That era is long over. Over the past fifty years, industrialization has given way to deindustrialization, and not just in any one line, but across the manufacturing sectors of most countries.7
The Productivity Paradox
In the scholarly literature, deindustrialization is “most commonly defined as a decline in the share of manufacturing in total employment.”8 That share fell first of all across the high-income world, starting in the late 1960s and early 1970s. Manufacturing employed 22 percent of all workers in the United States in 1970, a share that declined to just 8 percent in 2017. Over the same period, manufacturing employment shares fell from 23 percent to 9 percent in France, and from 30 percent to 8 percent in the UK. Japan, Germany, and Italy experienced smaller but still-substantial declines: in Japan, from 25 percent to 15 percent; in Germany, from 29 percent to 17 percent; and in Italy, from 25 percent to 15 percent. In all cases, the declines were eventually associated with substantial falls in the total number of people employed in manufacturing. In the US, Germany, Italy, and Japan, the overall number of manufacturing jobs fell by approximately a third from postwar peaks; in France, it fell by 50 percent, and in the UK, by 67 percent.9
It is commonly assumed that deindustrialization in these high-income countries must be the result of production facilities moving offshore. Offshoring has certainly contributed to deindustrialization in the United States and UK, which boast the world’s largest trade deficits. Yet in none of the countries named above, including the Unites States and UK, has manufacturing job loss been associated with declines in absolute levels of manufacturing output. On the contrary, the volume of manufacturing production, as measured by real value added, more than doubled in the United States, France, Germany, Japan, and Italy between 1970 and 2017. Even the UK, whose manufacturing sector fared worst of all among this group, saw a 25 percent increase in manufacturing real value added over this period. To be sure, low- and middle-income countries are producing more and more goods for export to high-income countries; however, deindustrialization in the latter cannot simply be the result of productive capacity moving to the former, since the high-income countries produced more manufactured goods at the end of the 2010s than they had anytime in the past. In line with automation theorists’ core expectations, more goods are being produced but by fewer workers.
It is on this basis that commentators typically cite rapidly rising labor productivity, rather than an influx of low-cost imports from abroad, as the primary cause of industrial job loss in advanced economies.10 On closer inspection, however, this explanation also turns out to be inadequate. Manufacturing productivity has been growing at a sluggish pace for decades, leading economist Robert Solow to quip, “We see the computer age everywhere, except in the productivity statistics.”11 Automation theorists discuss this “productivity paradox” as a problem for their account—explaining it in terms of weak demand for products, or the persistent availability of low-wage workers—but they understate its true significance. This is partly due to the appearance of steady labor-productivity growth in US manufacturing, at an average rate of around 3 percent per year since 1950. On that basis, Erik Brynjolfsson and Andrew McAfee suggest, automation could show up in the compounding effects of exponential growth, rather than an uptick in the growth rate.12
However, official US manufacturing growth-rate statistics are vastly overinflated, since they log the production of computers with higher processing speeds as equivalent to the production of more computers.13 For that reason, government statistics suggest that productivity levels in the computers and electronics subsector rose at a galloping average annual rate of over 10 percent per year between 1987 and 2011, even as productivity growth rates outside of that subsector fell to around 2 percent per year over the same period.14 Starting in 2011, trends across the manufacturing sector worsened: real output per person employed in the sector as a whole was lower in 2017 than in 2010. Productivity growth rates in manufacturing collapsed precisely when, according to automation theorists, they were supposed to be rising rapidly due to advancing technologies.
Correction of US manufacturing-productivity statistics brings them more into line with trends in countries like Germany and Japan, where manufacturing-productivity growth rates have fallen dramatically since their postwar peaks. In Germany, manufacturing productivity grew at an average annual rate of 6.3 percent per year in the 1950s and ’60s, falling to 2.4 percent from 2000 to 2017. This downward trend was to some extent an expected result of the end of an era of rapid catch-up growth. However, it should still be surprising to the automation theorists, since Germany and Japan have raced ahead of the United States in the field of industrial robotics. Indeed, the robots used in Tesla’s largely automated car factory in California were made by a German robotics company.15 As of 2016, German and Japanese firms deployed about 60 percent more industrial robots per manufacturing worker, compared to the US.16
Yet deindustrialization has continued to take place in all these countries, despite lackluster manufacturing-productivity growth rates; that is, it has taken place as the automation theorists expect, but not for the reasons they offer. To explore the causes of deindustrialization in more detail, I rely on the following definitions. Output, as used both above and below, is a measure of the volume of production (how much is produced), in terms of real or inflation-adjusted “value added” in a given economic sector.17 Gross domestic product, or GDP, is just value added for the economy as a whole. Employment, as I use it here, is a measure of the number of workers rather than of hours worked—the latter are typically unavailable outside of wealthier countries—while productivity is the ratio of output to employment: the more output is produced per worker, the higher that worker’s productivity level. For any economic sector, the rate of growth of output (ΔO) minus the rate of growth of labor productivity (ΔP) equals the rate of growth of employment (ΔE). Thus, ΔO – ΔP = ΔE.18 This equation is true by definition. If the output of automobiles grows by 3 percent per year, and productivity in the automotive industry grows by 2 percent per year, then employment in that industry must have risen by one percent per year (3 – 2 = 1). Contrariwise, if output grows by 3 percent per year and productivity grows by 4 percent per year, employment will have contracted by 1 percent per year (3 – 4 = –1).
Disaggregation of manufacturing-output growth rates in France provides us with a sense of the typical pattern playing out across the high-income countries (Figure 2.1).19 During the so-called golden age of postwar capitalism, productivity growth rates in French manufacturing were much higher than they are today—5.2 percent per year, on average, between 1950 and 1973—but output growth rates were even higher than that—5.9 percent per year. As a result, employment had to have grown steadily, at a pace of 0.7 percent per year. Since 1973, both output and productivity growth rates have declined, but output growth rates fell much more sharply than productivity growth rates. By the early years of the twenty-first century, productivity was rising at a much less rapid pace than it had during the postwar era, at 2.7 percent per year. However, slower productivity growth rates were now faster than their corresponding industrial output growth rates, at 0.9 percent. The result was that manufacturing employment contracted rapidly, by 1.7 percent per year. Even before that contraction got going, deindustrialization had already