The Brooklyn Rail

MAR 2017

All Issues
MAR 2017 Issue
Field Notes

Nowhere to Go:
Automation, Then and Now

Part One

It is in this serious light that we have to look at the question of the growing army of the unemployed. We have to stop looking for solutions in pump-priming, featherbedding, public works, war contracts, and all the other gimmicks that are always being proposed by labor leaders and well-meaning liberals.

– James Boggs, The American Revolution

In 1963, James Boggs, a black autoworker employed for over two decades at a Chrysler plant in Detroit, published a short book focused on the nefarious effects of automation on class struggle in the United States. The story told in The American Revolution: Pages from a Negro Worker’s Notebook begins with the early 1930s, the decomposition of the old craft unions, and a global economy in the throes of an unprecedented near-collapse; it arrives at a high point with the late 1930s, with a now-forgotten wave of sit-down strikes that tore through the tire and auto industries between 1933 and 1937, most famously at the Flint General Motors plant in early 1937.1 This was, in Boggs’s estimation, the “greatest period of industrial strife and workers’ struggle for control of production that the United States has ever known.” But this period also gave rise, under the reformist efforts of the New Deal and in a climate of mass unemployment, to the Wagner Act and the institutionalization of class struggle. The UAW, which just a few years earlier organized the sit-down strikes in the auto industry, had by 1939 banned the tactic in the plants. In the cast shadow of imminent war, the union’s no-strike pledge, along with the inevitable encrustation of a bureaucratic stratum more at home in the offices of management than on the workbenches, left workers to wildcat their way through the war. The Second World War witnessed thousands of work stoppages: an astonishing 8,708 strikes implicating over four million workers took place, according to Boggs, over one two-year period while war production was in full swing. Union pledges of discipline notwithstanding, order did not therefore always prevail. Workers, many of them from the rural South, and new to the world of the factory, consistently bucked against the dictates imposed by management and enforced by their own representatives. The wildcat strikes were not, however, always defections from the dictates of union bureaucrats and the boss. In 1943, a UAW-organized Packard plant was the site of a “hate strike” organized by white workers to push back against the influx of black workers into the factories, and the integration of assembly lines. Soon after, a tumultuous “race riot” broke out in the city, as white workers attacked black workers who now competed with them for housing. Dozens were killed, hundreds wounded; mostly black, and primarily at the hands of police and the National Guard. The city would be occupied by federal troops for a full half year after. Such was, for better and for worse, the American workers movement at its most militant.2

The onset of the post-war economic boom—with its soaring growth, surging wages, and near-full employment—did little to dampen the combativeness of workers on the line. The wildcat waves continued well into the 1950s, with the movement cresting, in Boggs’s reckoning, in the middle of the decade. The movement and its off-and-on open conflict with union brass (“porkchoppers” to rank-and-file) was chronicled in a series of broadsides (Punch-Out, Union Committeemen and Wildcat Strikes) by the irrepressible Martin Glaberman, Boggs’s longtime comrade in the Detroit-based Correspondence Publishing Committee. At stake in these struggles was what The American Revolution specifies as “control over production,” the ability of workers on the shop floor to dictate the pace and intensity of work through collective action and novel tactics. Chrysler’s management responded to this volatile situation with a weapon hitherto mostly under wraps: “A new force […] entered the picture,” Boggs writes, as management, with union blessing, “began introducing automation at a rapid rate.” Where prior efforts to speed up work rhythms met with fierce opposition from thousands of workers concentrated in massive production sites, this capacity for interruption depended upon worker control over the machinery set in motion during production. The stunning productivity gains made possible by the introduction of large-scale machinery and the moving assembly line still depended in large part on worker oversight of the production process. The lure of automation, from the perspective of Chrysler management, was obvious: many tasks performed and decisions made currently by workers could be replaced by programmable computers and cybernetic control systems. The promise of rising productivity in the workplace also entailed compromised worker control over the pace of production, threatening an outright swapping out of labor for capital on the other, with computer-assisted machines replacing potentially tens of thousands of works almost overnight. It was precisely this threat of substitution that, Boggs concludes, was decisive in the quashing of the strike movement in the middle of the 1950s: “since the advent of automation there has not been any serious sentiment for striking.”

It may be that the history of capitalism is the history of automation. Warnings about the perils of automation are as old as the capitalist mode of production. The first revolts of workers’ movement produced the myths of General Ludd and Captain Swing, and the insurrectionary forays of the canuts of Lyon. In their wake were left wrecked shearing frames and looms; barns, buildings, and goods were targeted by proletarian arsonists. Yet the development of the productive forces, and the implementation of large-scale machinery in capitalist factories, never quite made workers purely and simply redundant. To the contrary, over the course of more than a century, the demand for labor had grown exponentially, even as millions of peasants poured into cities, and entered into the wages system and the urban cash nexus. But this time, Boggs warned, was different: “Automation replaces men. This is of course nothing new. What is new is that now, unlike most earlier periods, the displaced men have nowhere to go” (my emphasis). These men and women, many of whom, like Boggs, had left the deep South for the industrial North and its factories and great cities, were loath to return to the countryside, to Jim Crow, rural isolation, and hardscrabble miseries. And the countryside wouldn’t have them: advances in mechanized farming across the South dramatically augmented agricultural productivity during the 1920s and after, in a matter of a few decades eliminating what jobs were left in the field. There was no turning back, in any case; these workers would not dare leave the cities, unless it was to “get away from the Bomb.”


Over the past hundred years or so, laments over an impending purge of workers by technological innovation have come in cyclical pulses, once every third decade. James Boggs’s variant of this complaint—to which I will return at the end of this essay—remains something of an exception: such concerns have largely been voiced, in the 20th century, by the emissaries of the dominant class charged with implementing automation, rather than by those at risk of replacement. Lord Keynes notably wrote, in 1930, of the “new disease” of “technological unemployment” visited upon a society otherwise enjoying the productivity gains reaped from a cluster of breakthroughs: the wholesale electrification of industry (Lenin’s definition of communism as “soviets with electrification” was no idle quip), the widespread use of internal combustion engines and newly paved road networks, the marvels of indoor plumbing, and the availability of cheap, plentiful steel. Another round of hand-wringing commenced in the mid-’50s—Boggs was far from alone—as technological leaps broached in the 1930s began to come online, the prospect of atomic power loomed, and primitive computers were coupled with large-scale machine production. Essays, studies, and books devoted to the marvels of “cybernation” abounded. The fascination with technological forces, typical of the capitalist class, was spoiled only when distracted by the fate of those potentially expelled from production. A booming industry in popular sociology speculated with optimism on the just-out-of-reach society of leisure delivered by these technological advances. Many worries, however, centered on a future of mass unemployment, with an attendant widespread immiseration, and even an uptick in class antagonism. Above all, those viewing this situation through the lenses of the capitalist class feared a crisis of under-consumption, as workers, deprived of the wage, would not be able to buy up all of the cheap commodities produced by such wonderful machines.

Within a decade, however, by the late 1960s, many of these same commentators would herald a coming post-industrial society and its rapidly expanding service sector, which would quickly soak up the vast majority of those Boggs claimed would have “nowhere to go” (he spoke of “surplus” people). In the 1970s, tens of millions of women began pouring into labor markets in the U.S. alone, often finding work in clerical and business services. One effect of this wholesale entry of women into workplaces was to accelerate the commodification of personal services as well, previously carried out in the form of unwaged, domestic or socially reproductive labor. Then, again, in the mid-1990s, just as the “New Economy” was said to be taking off—and the dot com bubble began to swell—another wave of worry washed over the chattering classes, with impeccable timing. Typical was this 1994 article from The Wall Street Journal, which breathlessly recycled the old tune: “technological advances are now so rapid that companies can shed far more workers than they need to hire to implement the technology or support expanding sales.”3 Jeremy Rifkin’s 1995 book, The End of Work, which counted on a “nearly automated” service sector (in 1995, almost seventy percent of unemployment by the economists’ calculations) by the mid-21st century, was as ubiquitous in the discourse of intellectuals as in the business papers. Since its publication, millions more workers have entered the service sector in high-income countries, as manufacturing has contracted still further. In the meantime, a hundred million Chinese peasants have made their own Great Migration, moving into mushrooming cities across that vast country, exchanging their labor-power day in and out for yuan.

Since the global economic meltdown of 2008, and especially over the last five years, there has once again been—in perfect sync with the cyclical pattern—an outpouring of articles and books detailing the wonders and pitfalls of an imminent rise of the robots. It is held we are living through a “second machine age” (cf. Erik Brynjolfsson and Andrew McAfee’s 2014 The Second Machine Age), dawning half a century after what was already, in the 1960s, called the “third industrial revolution.” But where that promised technological leap, to be unleashed by the conjoining of automation and atomic power, was proffered in the midst of a veritable explosion of economic growth, here the hyperbole comes on the heels of a near-fatal financial crisis, and at the end of a decade that registered “the slowest growth in productivity of any decade in American history.”4 Recent trends suggest this torpor has not been shaken. Indeed, since 1999, the height of the dot com bubble, private investment in software and computer equipment has fallen precipitously, by a full quarter: it is, today, as low as it was in 1995. This state of affairs is not lost on many commentators, who struggle to reconcile the marvels and menace of machine-learning algorithms (able, it is said, to “write their own programs”) with the prevailing conditions on the ground. Unemployment rates have only begun to ease in the U.S. as millions simply drop out of the labor market.5 Abroad, especially in southern Europe, they remain historically high. But these job losses are due less to the revenge of the robots than to a plethora of capital idling on the sidelines.

The presumption held by most contemporary discussions of automation is that new digital technologies constitute a revolutionary innovation on a par with electricity, whose cheap, networked availability by the 1920s spurred a half-century round of economic expansion. A handful of skeptics (such as Robert Gordon) contend that whatever IT-induced productivity gains are to be had were already reaped during a short period in the 1990s, tailing off by the end of the decade. The stakes of such a claim are sizable, since the implementation of any “truly general purpose technology” across the economy—not only in manufacturing, but in the massive service sector as well, a point I return to at length in part two of this essay—should, through the productivity gains they promise, bring the global economy out of its doldrums. If this new explosion in productivity were to follow the pattern set in the middle of the 20th century, we should expect not a crisis of employment but rising demand for the cheap commodities (goods or services) pumped out by newly automated production processes, with corresponding bumps in both demand for labor and wage levels: such was the “Golden Age” of the post-war boom. Ford is hardly sanguine about the effects of new automation technologies on labor markets. In Rise of the Robots, he claims that older automation technologies “tended to be relatively specialized and to disrupt one employment sector at a time, with workers then switching to a new emerging industry”; today, we are warned, information technology is spreading across all sectors simultaneously, including a huge swath of service sector occupations in health, education, and retail, leaving displaced workers—as Boggs put it fifty years before—nowhere to go.

Despite these imagined threats of a new round of technological employment hovering on the horizon, Ford, like most commentators on the subject, is at pains to explain the lag in the implementation of this “truly general purpose technology,” even as he bemoans its potential fallout. And yet at one point late in Rise of the Robots, he puts his finger on a peculiar inversion characteristic of the ongoing global recession—an inversion that could provide a key to understanding the puzzle of the present moment. While in most economic slumps productivity tends to drop off rapidly, with output falling faster than jobs can be shed, in the opening round of the recent crisis something else happened entirely. Firms on average registered modest gains in productivity, despite the hostile climate. Yet they did so despite rapid drop-offs in output: total output was shrinking, but payrolls were being slashed even faster. The uptick in productivity, in this case, was likely due not to technical innovations, but to longer, more stressful, days on the job for those who kept them. Ford: “during the Great Recession. […] productivity actually increased. Output fell substantially, but hours worked fell even more […] The workers who kept their jobs (who certainly feared more cuts in the future) probably worked harder and reduced any time they spent on activities not directly related to their work; the result was an increase in productivity.” Lest we imagine these patterns to be those of a cyclical if atypical downturn, a 2014 study by a group of researchers at MIT—like the authors of The Second Machine Age, though in this case, tellingly, not from the department of management, but from economics—detected a similar, longer-standing pattern in IT-intensive industries. Backdating this trend to the pre-crisis period, they find “little evidence of faster productivity growth in IT-intensive industries after the late 1990s”; when this evidence does appear, it is traced not to rapid productivity gains through the implementation of automation, but is instead said to be “driven by declining relative output accompanied by even more rapid declines in employment.”6 Lackluster performance like this is surely one reason investment in IT has fallen off so precipitously since the late 1990s; it rhymes, moreover, with Gordon’s claim that the period between 2004 – 14 exhibited the slowest productivity growth over a decade in U.S. history. It also gives us a hint as to why, even with central banks holding the choke open on the global economic engine, flooding it with free money, surplus capital has been shunted into short-term, speculative fixes—real estate, finance—rather into new lines of production.

This is the forbidding environment in which firms today operate. Predictions of rapid replacement of millions of jobs by machines must contend with these longer-term tendencies. Under such conditions, it is hard to imagine a sudden surge of growth in the manufacturing sector itself, even if certain lines find ways to undercut their competitors with temporary technological fixes. The 2014 MIT study just cited – the authors’ express purpose was to refute Brynjolfsson and McAfee’s 2011 book, Race Against the Machines—bears the pointed title “Return of the Solow Paradox?,” invoking the notorious comment offhandedly made by economist Robert Solow in a 1987 New York Times Book Review article: “what everyone feels to have been a technological revolution […] had been accompanied everywhere by slowing-down of productivity growth, not by a step up. You can see the computer age everywhere but in the productivity statistics.” Thirty years later, the needle hasn’t moved. If it is true that the staggering productivity gains of the 1920s and after can be attributed in part to the widespread use of electricity and the internal combustion engine, the real revolution was in the networking of these technologies, through the expansion of power grids and paved roads. Yet in a world in which seven in ten Haitians has a cell phone, the unimaginable density of global communication networks—even the planet’s poorest inhabitants are now “networked individuals”—has yet to put a dent into what many mainstream economists are calling a long-term, even “secular,” capitalist stagnation. Seen in this light, the anxious exhilaration surrounding contemporary machine-learning algorithms can feel hyperbolic. Measured against the potentially terrifying forces tapped by nuclear energy in the mid-20th century, Google Glass might seem a modest venture. Google’s parent company Alphabet speaks in exalted tones of technological moonshots, but ninety percent of its revenue and almost all of its profits still come from advertising, most of it via search engines. It is buying up smaller robotics and AI firms, but not necessarily to ramp up investment: it is to establish monopoly conditions that will guarantee super-profits and higher market share within these stagnant conditions. Today, high profits are assured for firms able to disrupt market dynamics and price signals. Such firms are often “more adept at siphoning wealth off than creating it afresh”; they thrive less through innovation than through exorbitant market shares, and streams of technological rent.7

A cursory look at the global economy over the past four decades indicates that, after the deep recession of the early 1970s, promised returns to levels of growth typical of Boggs’s time never materialized. Growth rates not only in the U.S. but in most OECD countries have on average remained listless for over forty years, expanding at less than half the rate of the so-called “Golden Years.” What accounts for this sluggishness? Many analysts point to declining profit rates for capitalist firms throughout this period. As profit rates fell, beginning as early as the mid-1960s, less capital was available for investment, both in existing and new lines of production; this blockage led in turn to job losses and high rates of unemployment. Explanations vary on why the initial decline in profit rates occurred. Some accounts suggest a high level of worker militancy in production account for the initial downturn, as full employment and high wages “squeezed” profit margins from below, leading to dwindling returns and a subsequent shakeout. Under these conditions, private firms set about restoring their profit rates through a variety of fixes, but above all by slashing wages, which have remained on average stagnant for this entire period, buoyed temporarily by a dizzying rise in consumer debt over this same period. And yet the “profit squeeze” theory cannot account for a crucial detail. If wages were slashed beginning in the 1970s, and have flat-lined since, why hasn’t the aggregate profit rate been restored to pre-1970s levels, relaunching in turn productivity gains (as rising profits are reinvested in production) and expanding employment? Robert Brenner and Fred Moseley, among others, have attempted to respond to this question in different ways (global overcapacity in manufacturing, a rising ratio of unproductive-to-productive labor, and so on). In the current climate, and in certain sectors, monopoly-like conditions for specific firms can engender abnormally high returns for firms and their shareholders. In other sectors, select companies can invest in technologies to win competitive advantage long enough to capture a larger market share, even as that market, and total output in a given sector, remains static, or even declines. This is not soil in which new shoots will grow.


Most of those ringing alarms over the course of the 20th century regarding the perils of automation have been torn between a fascination with technological development, which promises a tendential spread of worklessness to the whole of society, and a shopkeeper’s anguish over just who might consume the mountains of cheap commodities disgorged by the machines. Historically, many approaches to automation on the Left have emphasized the way the deployment of technological breakthroughs, and the substitution of capital for labor, constitute strategic moves in a raging war at the point of production. Boggs’s observation that the capitalist use of automation allowed plant owners to recapture control over production, putting paid to a long wave of strikes, is just one example in a rich vein of analysis that emphasizes the specifically capitalist nature of the complex machinery and organizational refinements characteristic of contemporary production processes. Writers as varied as Raniero Panzieri, Harry Braverman, David Noble, and Moishe Postone have all made important contributions to this strain of thought, emphasizing the way patterns of technological development increasingly reflect capitalist value-relations, making any future “socialist use” of much of this machinery onerous at best.8

Some recent examinations on the Left of the structural drive toward the replacement of labor by machines have taken a different tack. Writers like Antonio Negri have seen changes in the composition of capital in an altogether positive light, reading the rising organic composition of capital through the lens of Marx’s 1858 “Fragment on Machines”: the “monstrous disproportion” between the productive capacity of large-scale, computer-controlled machinery and the diminishing quantities of labor time required to set this system in motion.9 A common version of this position imagines an automation-induced “abolition of work” that would, as this worklessness initially takes the form of mass unemployment, be offset by the implementation of a state-administered “guaranteed basic income”; such payments supposedly would, as they stimulate effective demand and keep capitalist production ticking over, gradually sever the sacred tie between income and the time of work.

Nick Srnicek and Alex Williams’s recent Inventing the Future, heralding a post-capitalist “world without work,” takes up this legacy in its way, putting forth as its core programmatic demand the total automation of the “economy” (a term they leave unexamined). They, like the mainstream accounts they are reproducing, are compelled to grapple with the “return of Solow’s paradox”: for all of the hype about big data, the internet of things, and workerless factories, aggregate growth rates remain as we saw lackluster at best, especially compared with their mid-century peak. It is for this reason that the substitution of machines for human labor should be, they write, “enthusiastically accelerated [. . .] as a political project of the left” (my italics). Here we hit the rub in their vision of the future. They make a half-hearted stab at accounting for automation’s “diffusion lag,” but twist themselves into knots in doing so.10 “It is highly likely,” they write, that “low wages are repressing investment in productivity-enhancing technologies.”11 This is undoubtedly one factor that must be considered: why would business owners invest in fixed capital that depreciates over years, when loose labor markets allow cheap labor to be picked up and dropped at a moment’s notice? Following this line of reasoning, Srnicek and Williams argue that “in the effort to bring about full automation, fighting for higher global wages is a crucial complementary task.” Leaving aside the Herculean task of organizing a struggle across the planet for higher “global wages”—narrowing wage differentials on a global level might be a more plausible objective, but this would require lowering wages of U.S. workers, as those in east Asia rise to meet them—this proposition is a puzzling one. Rather than considering why low-wage jobs and the people compelled to work them are so plentiful in the first place, or why these workers are incapable of organizing these low-wage sectors in order to demand higher wages, the authors suggest that higher wage levels must be implemented by political fiat, or bureaucratic decree. But this would, according to this logic, be an intermediate step: since compelling employers to raise wages will require them to deploy automation, imposing higher wages on employers will have as their “desired” effect mass unemployment: putting those who’ve just won bigger paychecks out of work. Such is the strategic vision offered by social democratic accelerationism.

We must stand this problem back on its feet. The lag in implementing wholesale automation across all sectors of the economy, with the corresponding and long-standing lag in productivity gains, must be considered from the perspective of the dynamics of global capitalism as a whole. Current speculations on both the promise and threat of automation are confronted with an ongoing crisis of accumulation. In this climate, a fragmentary implementation of automation is unlikely either to liberate large fractions of humanity from work, or produce mass unemployment of the sort envisioned over and again by commentators for the past century. The conviction held by many on the Left, here following tech enthusiasts like Martin Ford, is that the technical capacity to automate most if not all occupations is virtually present. Any lag in implementation is, by this reckoning, due to “failures of government policy”: with the right cocktail of social democratic adjustments (shorter work weeks, higher minimum wage, basic income, etc.), with the correct “political choices,” a world of “tight labor markets” and a decent standard of living for all could be won.12 My own investigation starts from a different place. I want to ask why, for all of the froth churned up around the productive potential lurking in test labs, the pattern exhibited over the past fifteen years has been one of declining investment in information technology, and falling output for IT-assisted manufacturing? Why has almost all growth in employment—ninety-six percentsince 1990 “come from sectors known to have low productivity […] and sectors where low productivity is merely suspected in the absence of competition and proper measurement techniques”? Why has some ninety-four percent of new employment in the U.S. since 2000 been in education, healthcare, social assistance, bars, restaurants, and retail, that is, in the vast, motley, and above all technologically stagnant service sector?13

In the second part of this essay—to appear in the April 2017 Field Notes—I will examine the nature of the service sector in some detail. Doing so will present new challenges to the assumption made by many recent publications on automation, which take for granted the possibility of automating this enormous and poorly conceived dimension of the contemporary capitalist world, making up some four-fifths in high-income countries like Britain and the U.S. Why do we see such tepid productivity growth is so many economic sectors, especially key service sectors such as education and health care? Why has the last forty years witnessed an explosion of the low-wage service sector as a whole, as employment shifted, in high-income countries, from manufacturing to the services, the latter comprising now close to eighty percent of employment in the U.S.? Why do many of these occupations continue to entail low capital-to-labor ratios, with profit margins directly impacted by the fluctuation of wages, as employers’ outlay consists primarily of labor costs? Why is an overwhelming share of employment, in other words, shunted into sectors of the economy that are, perhaps by their very nature, technologically stagnant, and not subject to technological and organizational refinements on the order of those that have taken place in manufacturing and industry? How does the complexity and fragmentation of the so-called service sector affect workers capacity to organize themselves across occupational types, and in view of building anew forms of worker power appropriate to the 21st century?


  1. James Boggs, The American Revolution: Pages from a Negro Worker’s Notebook (New York: Monthly Review Press, 1963).
  2. In his Riot.Strike.Riot (London: Verso, 2016), Joshua Clover—who also discusses Boggs at some length— emphasizes that “the history of race riots in the United States begins with whites disciplining insubordinate other populations.” Oddly, Boggs makes no mention of these white supremacist race riots, even as his account focuses in large part on the fate of the “Negro” worker, and anticipates the “coming explosions” of the mid-to-late 1960s.
  3. Cited in Jeremy Rifkin, The End of Work: The Decline of the Global Labor Force and the Dawn of the Post-Market Era (New York: Putnam, 1995), 141.
  4. Robert Gordon, The Rise and Fall of American Growth: The US Standard of Living Since the Civil War (Princeton: Princeton University Press, 2016), 529; my italics.
  5. “The unemployment rate is not wrong, but it does not tell us much about the festering crisis of worklessness in America. For that, you need to look at the rising share of people in their prime years (between twenty-five and fifty-four) who are neither working nor looking for work: a figure that now stands—as it happens—at about twenty percent.” “America’s ‘jobs for the boys’ is just half the employment story,” Financial Times (February 7, 2017). I thank William Clare Roberts for this reference.
    Little more than half of working age adults in the U.S. are employed full-time or are part-time employees “voluntarily.”
  6. Daron Acemoglu et al., “Return of the Solow Paradox? IT, Productivity, and Employment in US Manufacturing,” American Economic Review: Papers & Proceedings 104: 5 (2014) 394, 399.
  7. “Too Much of a Good Thing,” Economist (March 26, 2016). Isabelle Kaminska has even spoken of tech monopoly conditions in tongue-in-cheek terms as “Gosplan 2.0”: Technology conglomerates (from Tesco to Google) on the other hand tend to use the information they collect to subjectively interpret or presume our consumption patterns on qualitative grounds so as to stretch existing output amongst more people, rather than to encourage its growth. This in turn leads to the n the market, the loss of price signals and the unintended support of uneconomic ventures on the hope that one day, perhaps—by driving out all ‘at cost’ competition—they’ll be the last man standing, with rights to monopoly rents.”
  8. Recently, Jasper Bernes has made an important contribution to this important if relatively marginal tradition, with specific reference to contemporary logistics “revolution.” See his “Logistics, Counterlogistics and the Communist Prospect,” Endnotes 3: Gender, Race, Class, and Other Misfortunes (September 2013).
  9. See Notebook VII of Karl Marx’s Grundrisse.
  10. An important historical account comparing the “diffusion lags” entailed in full-scale implementation of electricity and that with computers is Paul A. David’s “The Dynamo and the Computer: An Historical Perspective on the Modern Productivity Paradox,” 80:2 (1990): 355-61. This essay is very rich in historical information, and is a valiant attempt to solve the puzzle of Solow’s paradox. While it makes quite convincing arguments about the delay in the diffusion of electricity (the technology for which had been available for decades), it is worth noting that David’s paper was written in 1990: 25 years later, we are still waiting on the productivity explosion. Gordon argues, to the contrary, that the modest gains registered in the 1990s is all we’ll get.
  11. Nick Srnicek and Alex Williams, Inventing the Future: Postcapitalism and a World without Work (London: Verso, 2015), p. 112. Other important “left” discussions of automation are found in Peter Frase’s Four Futures (London: Verso, 2016) and Paul Mason’s Postcapitalism: A Guide to Our Future (London: Verso, 2016).
  12. Frase, Four Futures, 17.
  13. Matthew C. Klein, “The Great American Make-Work Programme,” Financial Times (September 8, 2016).


Jason E. Smith

Jason E. Smith writes about contemporary art, philosophy, and politics. His book, Smart Machines and Service Work: Automation in an Age of Stagnation (London: Reaktion, 2020) is part of the Field Notes series.


The Brooklyn Rail

MAR 2017

All Issues