Computerization, atomization, crowdsourcing and the new economics of employment
Beginning with the earliest stages of industrialization and Ned Ludd’s supposed 1779 attack on two textile machines — the source of the term Luddite — worries about the future of work have passed in phases. Charles Dickens portrayed gritty factory realities in the 1800s, while the 1936 movie Modern Times showed Charlie Chaplin swallowed whole and spit out by an enormous machine. Science fiction has long been spinning out dystopian scenarios, with robots marginalizing, replacing or enslaving humanity.
Beyond cultural and media images, important research questions also emerge with each new economic phase. Globalization has been a dominant concern in recent decades, but increasingly media reports and academic work have focused on computerization. In years past, analysts have looked at the changes in cost and output — and analyzed socioeconomic shifts — as work has moved to the developing world, and as certain job functions have been automated. However, a profound, emerging question is how the calculus changes when jobs are broken apart and atomized through Internet-enabled technologies. What is the future of work when micro-tasks are farmed out to disparate people and groups globally? And how does this change the economic analysis?
The scholarship on these and related questions is diverse — and very much still in its nascent stages.
Research models, contentions and findings
It should first be said that the subject is complicated, and pessimistic generalizations and oversimplifications are a danger in this area. A 2014 paper by MIT’s David Autor on machine displacement of human labor stresses the need for caution, noting that “journalists and expert commentators overstate the extent of machine substitution for human labor and ignore the strong complementarities that increase productivity, raise earnings, and augment demand for skilled labor.” In any case, economists have long criticized the “lump of labor fallacy,” in which people assume there is a finite number of jobs and changes result in zero-sum outcomes. But as technology can eliminate jobs, it also can create new ones.
Other economists have begun to explore how a much more automated future may play out. In a February 2015 paper for the National Bureau of Economic Research, “Robots Are Us: Some Economics of Human Replacement,” a group of scholars create a model of the future and conclude that the likely scenario is not altogether positive for workers: There were will be a “long-run decline in labor share of income (which appears underway in OECD members), tech-booms followed by tech-busts, and a growing dependency of current output on past software investment.” The researchers — Boston University’s Seth G. Benzell, Laurence J. Kotlikoff and Guillermo LaGarda; and Columbia University’s Jeffrey D. Sachs — conclude that public policy is the only way to mitigate future problems: “Absent appropriate fiscal policy that redistributes from winners to losers, smart machines can mean long-term misery for all.”
Nobel laureate Michael Spence of New York University has written that “information technologies that automate, dis-intermediate, and reduce the costs of remoteness are also enabling the construction of increasingly complex and geographically diverse global supply chains and networks.” He notes that the development towards atomized global supply chains leads to rising competition in sectors of the global economy previously protected from competition. (The U.S. economy and labor market face a number of related structural challenges, Spence has noted.)
A January 2014 report in the Economist magazine identified a trend in technological innovations: Whereas innovation during times of industrialization focused on the automation of physical work, innovation today focuses on the automation of brain-work. This notion implies that innovations in robotics and computing impact different kinds of labor in different ways. In a 2013 study, University of Oxford researchers Carl Benedikt Frey and Michael A. Osborne analyzed different jobs and their susceptibility to being automated through computerization.
New forms of labor such as “crowd-work” have emerged as a result of the disruptive technological changes of recent years. Crowd-work systems such as Amazon Mechanical Turk combine atomized tasks and globalized completion for tasks. (To take just one example, the U.S. Defense Department used Turk to translate into English hundreds of thousands of Arabic-language social media posts, at about one-tenth of the cost of using professional translators.) A 2010 study by scholars from the University of California, Irvine, identified a trend towards a more globalized workforce among crowd-workers in Mechanical Turk. A follow-up study in 2013 described the occupational hazards connected to employment in crowd-work systems.
Harvard’s Jonathan Zittrain has long been warning about the ethics of “cloud labor” and what he’s called “minds for sale”:
Of course, crowdsourced work is not always paid. New York University’s Clay Shirky has pointed out that the Internet allows people to harness the “cognitive surplus” of the crowd, wherein small amounts of free time spent by individuals on interactive projects — when spread out over a larger community — can result in the creation of things of enormous value. Increasingly small increments of time and work might be harnessed to ensure high participation rates in crowdsourced projects, as U.C. Santa Cruz and Stanford researchers suggest in a May 2014 paper.
The Pew Research Center has surveyed a wide variety of experts about their views on computerization, robotics, artificial intelligence and the future of work. Although many of those surveyed agreed that these trends are important and will grow, the experts were “deeply divided on how advances in AI and robotics will impact the economic and employment picture over the next decade.” Further, in the New York Times, reporter Claire Cain Miller reviews some of the research on how technology is polarizing the job market.
Below is a further selection of academic research on new technologies and their impact on labor markets and job design in the United States and across the global economy:
Abstract: “Will smart machines replace humans like the internal combustion engine replaced horses? If so, can putting people out of work, or at least out of good work, also put the economy out of business? Our model says yes. Under the right conditions, more supply produces, over time, less demand as the smart machines undermine their customer base. Highly tailored skill- and generation-specific redistribution policies can keep smart machines from immiserating humanity. But blunt policies, such as mandating open-source technology, can make matters worse.”
Abstract: “This paper begins by tracing changes in employment patterns since the middle of the 20th Century, arguing that the mid-2000s marked the beginning of a fourth distinctive phase, the earlier ones having begun, respectively, after the end of World War II, after the 1973 oil crisis, and after the end of the Cold War, around 1990. In this new phase, dubbed here the ‘Internet Age,’ various tendencies with their origins in earlier periods have reached critical mass. These include a developed international division of labour, in both manufacturing and services and an employment landscape dominated by large transnational corporations able to draw on this global labour pool, using ICTs to manage their increasingly elaborate value chains. Many of these corporations have grown on the basis of the commodification of activities which previously lay outside the scope of profit making, including public services. The paper then discusses how and why online workers are at the front line of many of these developments, before going on to introduce the contents of this volume.”
Conclusion: “The next decade, we believe, will be an exciting time for research about people doing work in organizational settings. What comes next certainly will be informed by all the research that has been done over the last few decades. But its specific features will have little in common with the studies we and others carried out back in the early days of research on the attributes of specific jobs. The reason, as is seen in this issue (and especially in the commentaries), is that the design of work is now inextricably bound up with the structures and processes of organizational systems more generally. That is, rather than specific jobs it is the often-fluid relationships among people and their various work activities that are most in need of empirical research and conceptual attention. Work design is everywhere in organizations, which attests to the importance of the topic — but also requires fresh thinking about the phenomenon and about the most productive ways to continue to learn about it.”
“The Future of Crowd Work” Kittur, Aniket; Nickerson, Jeffrey V.; Berstein, Michael S.; Gerber, Elizabeth M.; Shaw, Aaron; Zimmerman, John; Lease, Matthew, Horton, John J. ACM Conference on Computer Supported Cooperative Work, February 2013.
Abstract: “Paid crowd work offers remarkable opportunities for improving productivity, social mobility and the global economy by engaging a geographically distributed workforce to complete complex tasks on demand and at scale. But it is also possible that crowd work will fail to achieve its potential, focusing on assembly-line piecework. Can we foresee a future crowd workplace in which we would want our children to participate? This paper frames the major challenges that stand in the way of this goal. Drawing on theory from organizational behavior and distributed computing, as well as direct feedback from workers, we outline a framework that will enable crowd work that is complex, collaborative, and sustainable. The framework lays out research challenges in twelve major areas: workflow, task assignment, hierarchy, real-time response, synchronous collaboration, quality control, crowds guiding AIs, AIs guiding crowds, platforms, job design, reputation, and motivation.”
Abstract: “This paper examines shifts over time in the relative demand for skilled labor in the United States. Although de-skilling in the conventional sense did occur overall in 19th century manufacturing, a more nuanced picture is that occupations ‘hollowed out’: the share of ‘middle-skill’ jobs (artisans) declined while those of ‘high-skill’ (white collar, non-production workers) and ‘low-skill’ (operatives and laborers) increased. De-skilling did not occur in the aggregate economy; rather, the aggregate shares of low-skill jobs decreased, middle-skill jobs remained steady, and high-skill jobs expanded from 1850 to the early 20th century. The pattern of monotonic skill upgrading continued through much of the 20th century until the recent ‘polarization’ of labor demand since the late 1980s. New archival evidence on wages suggests that the demand for high-skill (white collar) workers grew more rapidly than the supply starting well before the Civil War.”
Abstract: “We offer a unified analysis of the growth of low-skill service occupations between 1980 and 2005 and the concurrent polarization of U.S. employment and wages. We hypothesize that polarization stems from the interaction between consumer preferences, which favor variety over specialization, and the falling cost of automating routine, codifiable job tasks. Applying a spatial equilibrium model, we corroborate four implications of this hypothesis. Local labor markets that specialized in routine tasks differentially adopted information technology, reallocated low-skill labor into service occupations (employment polarization), experienced earnings growth at the tails of the distribution (wage polarization), and received inflows of skilled labor.”
“Trade in Tasks” Lanz, Rainer; Miroudot, Sébastien; Nordås, Hildegunn K. 2011, OECD Trade Policy Papers No. 117. doi: 10.1787/5kg6v2hkvmmw-en.
Abstract: “This paper analyses the task content of goods and services and sheds light on structural changes that take place following trade liberalisation. The task content of goods and services is estimated by combining information from the O*Net database on the importance of a set of 41 tasks for a large number of occupations and information on employment by occupation and industry. The study shows that tasks that can be digitised and offshored are often complementary to tasks that cannot. Therefore, the assessment of the offshorability of a job requires that one take into account all tasks being performed. The paper finds that import penetration in services has a small, but positive effect on the share of tasks related to getting and processing information being performed in the local economy. In other words, offshoring complements rather than replaces local information processing. As distortions in the market for intermediate inputs, including offshored tasks, have a larger negative impact the more diversified and complex the economy, possible adverse effects of offshoring on the labour market should be dealt with through social and labour market policy measures, not trade restrictions. In addition, if trade restrictions are imposed, they should be levied on imported value added, not on the total import value.”
Abstract: “The stability of the labor share of income is a key foundation in macroeconomic models. We document, however, that the global labor share has significantly declined since the early 1980s, with the decline occurring within the large majority of countries and industries. We show that the decrease in the relative price of investment goods, often attributed to advances in information technology and the computer age, induced firms to shift away from labor and toward capital. The lower price of investment goods explains roughly half of the observed decline in the labor share, even when we allow for other mechanisms influencing factor shares such as increasing profits, capital-augmenting technology growth, and the changing skill composition of the labor force. We highlight the implications of this explanation for welfare and macroeconomic dynamics.”
Abstract: “The paper examines the relationship between the rapid pace of trade and financial globalization and the rise in income inequality observed in most countries over the past two decades. Using a newly compiled panel of 51 countries over a 23-year period from 1981 to 2003, the paper reports estimates that support a greater impact of technological progress than globalization on inequality. The limited overall impact of globalization reflects two offsetting tendencies: whereas trade globalization is associated with a reduction in inequality, financial globalization — and foreign direct investment in particular — is associated with an increase in inequality.”
Keywords: technology, crowdsourcing, technology, research roundup