Are robots going to render the human worker obsolete? These claims are inaccurate and misleading, says MIT economics professor David H Autor, as the role of the computer will typically be to complement, not compete with, the human touch.

In 1966, the philosopher Michael Polanyi observed: "We can know more than we can tell... The skill of a driver cannot be replaced by a thorough schooling in the theory of the motorcar; the knowledge I have of my own body differs altogether from the knowledge of its physiology." Polanyi's observation largely predates the computer era, but the paradox he identified – that our tacit knowledge of how the world works often exceeds our explicit understanding – foretells much of the history of computerisation over the past five decades.

Computers are ubiquitous in contemporary life, but the tasks that have proved most vexing to automate are those that demand flexibility, judgement and common sense – skills that we understand only tacitly. The interplay between machine and human comparative advantage allows computers to substitute for workers in performing routine, codifiable tasks while amplifying the comparative advantage of workers in supplying problem-solving skills, adaptability and creativity.

The human touch

Understanding this interplay is central to interpreting and forecasting the changing structure of employment in the US and other industrialised countries. This understanding is also is at the heart of the increasingly prominent debate about whether the rapid pace of automation threatens to render the demand for human labour obsolete over the next several decades.

Computers do not think for themselves, do not have common sense, and do not improvise solutions for unexpected cases. For a computer to accomplish a task, a programmer must first fully understand the sequence of steps required to perform that task, and then must write a program that, in effect, simulates these steps. When a computer processes a company’s payroll, alphabetises a list of names, or tabulates the age distribution of residents in a Census enumeration district, it is 'simulating' a work process that would, in a previous era, have been done by humans using nearly identical procedures.

The principle of computer simulation of workplace tasks has not fundamentally changed since the dawn of the computer era. But its cost has; and as the price of computing power has fallen, computers have increasingly displaced workers in accomplishing explicit, codifiable tasks. This force has led to a substantial decline in employment in clerical, administrative support and, to a lesser degree, production and operative employment. Many refer to this phenomenon – which is ubiquitous across EU countries – as job ‘polarisation’ because it primarily displaces middle-educated, middle-wage clerical and production workers, while leaving both high-paid professionals and low-paid service and manual workers (such as food service workers and cleaners) comparatively unscathed.

Familiarity problems

But the scope for substitution is bounded: engineers cannot program a computer to simulate a process that they (or the scientific community at large) do not explicitly understand. This constraint is more binding than one might initially surmise because there are many tasks that we understand tacitly and accomplish effortlessly for which we do not know the explicit 'rules' or procedures.

Following Polanyi’s observation, the tasks that have proved most vexing to automate are those demanding flexibility, judgement and common sense – skills that we understand only tacitly. When we break an egg over the edge of a mixing bowl, identify a distinct species of birds based only on a fleeting glimpse, write a persuasive paragraph, or develop a hypothesis to explain a poorly understood phenomenon, we are engaging in tasks that we only tacitly understand how to perform.

At a practical level, Polanyi's paradox means that many familiar tasks, ranging from the quotidian to the sublime, cannot currently be computerised because we don't know 'the rules'. At an economic level, Polanyi's paradox means something more. The fact that a task cannot be computerised does not imply that computerisation has no effect on that task. On the contrary: tasks that cannot be substituted by computerisation are generally complemented by it.

This point is as fundamental as it is overlooked. Most work processes draw upon a multi-faceted set of inputs: labour and capital; brains and brawn; creativity and rote repetition; technical mastery and intuitive judgement; perspiration and inspiration; adherence to rules and judicious application of discretion. Typically, these inputs each play essential roles; improvements in one do not obviate the need for the other. If so, productivity improvements in one set of tasks almost necessarily increase the economic value of the remaining tasks. When the quality of our tools improves, the productivity of workers who expertly use these tools increases as well. If you doubt this proposition, ask yourself if you’d be more or less valuable in your work if you threw away your computer.

There is a long history of leading thinkers overestimating the potential of new technologies to substitute for human labour and underestimating their potential to complement it. The green revolution displaced labour from farming. The industrial revolution replaced skilled artisanal labour with unskilled factory labour. The mass-produced automobile drastically reduced demand for blacksmiths, stable hands and many other equestrian occupations. Successive waves of earth moving equipment and power tools displaced manual labour from construction. In each case, groups of workers lost employment and earnings as specific jobs and accompanying skill sets were rendered obsolete.

The complementary tasks

One can find fresh examples daily in which technology substitutes for human labour in an expanding – though still circumscribed – set of tasks. The complementarities are always harder to identify. Despite these uncertainties, there are inferences in which we can be fairly confident:

A first is that the technological advances that have secularly pushed outward the demand for skilled labour over many decades will continue to do so. As physical labour has given way to cognitive labour, the labour market's demand for formal analytical skills, written communications and specific technical knowledge has risen spectacularly.

A second observation is that employment polarisation will not continue indefinitely. While many middle-skill tasks are susceptible to automation, many middle-skill jobs demand a mixture of tasks from across the skill spectrum. To take one prominent example, medical support occupations – radiology technicians, phlebotomists, nurse technicians, etc – are a numerically significant and rapidly growing category of relatively well-remunerated, middle-skill employment. While not all of these occupations require a college degree, they do at least demand two years of post-secondary vocational training.

My conjecture is that many of these middle-skill jobs are likely to persist and, potentially, to grow because the tasks currently bundled into these jobs cannot readily be unbundled – with machines performing the middle-skill tasks and workers performing the residual – without a substantial drop in quality.

Consider, for example, the commonplace frustration of calling a software firm for technical support only to discover that the support technician knows nothing more than what is on his or her computer screen – that is, the technician is a mouthpiece, not a problem solver. This example captures one feasible division of labour: machines performing routine technical tasks, such as looking up known issues in a support database, and workers performing the manual task of making polite conversation while reading aloud from a script. But this is not generally a productive form of work organisation because it fails to harness the complementarities between technical and interpersonal skills. Rather, the quality of the service improves when the worker combines technical expertise, augmented by computers, with human flexibility.

Many of the middle-skill jobs that persist in the future will combine routine technical tasks with the set of non-routine tasks in which workers hold comparative advantage – interpersonal interaction, flexibility, adaptability and problem-solving. Medical support occupations are one leading example of this virtuous combination, but this example is not a singularity. This broad description also fits numerous skilled trade and repair occupations – plumbers, builders, electricians, automotive technicians – marketing occupations, and even modern clerical occupations that provide coordination and decision-making functions rather than simply typing and filing.

Indeed, even as some formerly middle-skill occupations are stripped of their routine technical tasks and arguably deskilled – for example the stockbroking occupation – other formerly high-end technical occupations are made accessible to workers with less esoteric technical mastery, for example, the nurse practitioner occupation that increasingly performs diagnosing and prescribing tasks in lieu of physicians.

Global factors

A final observation is that while much contemporary economic pessimism attributes the labour market woes of the past decade to the adverse impacts of computerisation, the evidence for this inference remains weak at best. Clearly, computerisation has shaped the structure of occupational change and the evolution of skill demands. But it is harder to see the channel through which computerisation could have dramatically reduced labour demand after 1999. The onset of the weak US labour market of the 2000s coincided with a sharp deceleration in computer investment – a fact that appears first-order inconsistent with the onset of a new era of capital-labour substitution.

Moreover, the US labour market woes of the past decade occurred alongside extremely rapid economic growth in much of the developing world. Indeed, frequently overlooked in US-centric discussions of world economic trends is that the 2000s was a decade of rising world prosperity and falling world inequality. It seems implausible to me that technological change could be enriching most of the world while simultaneously impoverishing the world's technologically leading nations.

My suspicion is that the deceleration of the US labour market after 2000, and further after 2007, is more closely associated with two other macroeconomic events. A first is the bursting of the dot-com bubble, followed by the collapse of the housing market and the ensuing financial crisis, both of which curtailed investment and innovative activity. A second is the employment dislocations in the US labour market brought about by rapid globalisation, particularly the sharp rise of import penetration from China following its accession to the World Trade Organisation in 2001. China's rapid rise to a premier manufacturing exporter had far-reaching impacts on US workers, reducing employment in directly import-competing US manufacturing industries and depressing labour demand in both manufacturing and non-manufacturing sectors that serve as upstream suppliers to these industries.

Globalisation, as with technological change, is not typically Pareto-improving, particularly in the short run. While the long-run effects of these developments should in theory be positive, the adjustment process, as with technological adaptation, is frequently slow, costly and disruptive.

David H Autor is professor of economics and associate head of Massachusetts Institute of Technology's economics department.

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