Autor is a credible voice in this area, since he has been writing about the relationship between technology and labour markets for several decades now, so has the benefit of context. But it is also a reminder that thinking about models is more useful in addressing uncertainty than just pumping out modelling data.

Skill premium

The title of the article, on the NBER website, conveys the tone: ‘The Labor Market Impacts of Technological Change: From Unbridled Enthusiasm to Qualified Optimism to Vast Uncertainty’. It’s a long article, though never technical, and so I’ll only have the space here to pick up some of the main points.

This is his starting point:

what workers earn in a market economy depends substantially, though not exclusively, on their productivity–that is, the value they produce through their labor. Their productivity depends in turn on two things: first, their capabilities (concretely, the tasks they can accomplish); and second, their scarcity… In conventional terms, the skill premium depends upon the supply of skills and the demand for skills.

So, if that is the structure of the market, what is the impact of technology? The answer is not obvious, and different models of the relationship between technology and work generate very answers. Autor reviews four models, briefly summarised here by me.

1. The education race

This is the most influential model, originally proposed by Jan Tinbergen and popularised by Claudia Goldin and Lawrence Katz. Tinbergen started by observing that the wages of Dutch workers with post-high school education were rising, even though their numbers were increasing. He concluded the modern economies had a race between increasing demand for skills and being able to supply it.

There’s more to this, but it leads to an important question:

what is it about technology that raises the demand for better-educated workers?

The model doesn’t really have an answer to this. In theory, at least, technology should help all workers by augmenting their productivity, if by differing amounts. But, as we know, this is not what the data says.

2. The task-polarisation model

The task model tries to explain why the real wages of some groups of workers fall even while technology is increasing the productivity of issues. In this, jobs are construed as a bundle of tasks, and the extent to which the tasks can be replaced by technology is then assessed.

In this model, automation replaces some of the tasks in the bundle. In turn, this also helps to explain why computerisation has benefitted high-skilled workers. In brief, the tasks that have been harder to automate have involved non-routine, cognitive, and inter-personal tasks that are more likely to part of a high-skilled bundle. And a bit more:

The productivity and earnings power of workers who specialize in abstract reasoning, expert judgment, and interpersonal interactions and leadership rises as the inputs into their work—information access, analysis, and communication—becomes less expensive and more productive.

Although there are also tasks (such as care work) that technology can’t easily substitute, neither does technology help their productivity.

The task model thus underscores that technological change, like most economic transformations, creates both winners and losers. … (It) further implies that a substantial component of this effect stems from the adverse impacts of technological change on the earnings of less-educated workers rather than (exclusively) the positive effect of factor-augmentation on the earnings of high-skill workers.

3. New work and task reinstatement

As described above, the task model doesn’t capture the emergence of new tasks, but we know that work is continually evolving. One innovative way of assessing this, at least in the US, is by looking at the emergence of new job titles in the Census. Acemoglu and Restrepo have integrated this into the task model by proposing that

automation displaces workers from existing job tasks as before; but now, new task creation potentially ‘reinstates’ demand for workers by generating new tasks that require human expertise.

In this version, the labour market effects of automation are effectively a race between task automation and task reinstatement. And it’s also possible to identify both technology innovations that automate tasks, and those that augment tasks, enabling reinstatement.

4. The era of AI uncertainty

So the question is whether this framework is well-placed or not to assess the impact of AI:

Does AI fundamentally change the relationship between technological change, labor demand, and inequality—and if so, how do we characterize these changes analytically?

The task model assumes that those tasks that can be automated involve explicit instructions, and AI undermines this assumption. AI is able to infer certain relationships.

Despite this, Autor concludes that the task model is still analytically useful. But AI still raises important questions:

“what work tasks will AI prove capable of accomplishing in the years (and decades) ahead?”

“what new demands for human skills and capabilities will emerge as AI displaces a growing set of traditional human work tasks? “

‘Ungrounded speculation’

Having gone through all the evidence in a lot of detail—I’ve summarised ruthlessly—Autor concludes with a section called ‘ungrounded speculation’. In brief summary here, he makes four observations:

• First, “further improvements in AI’s capabilities may accelerate the process of task automation relative to task augmentation. Broadly, this will mean that labor’s share of national income will decline further.”
• Second, AI reshapes the type of tasks (and therefore worker skills) that are substituted for and complemented by technologies. However, at the moment, “there is an upper limit to this substitution process at present… People effortlessly do extraordinary things on an ongoing basis, such as applying common sense to tease apart otherwise intractable problems.”
• Third, he does not expect AI to reach deep into the areas of low paid service work. Human interaction matters in this work, and the robotics involved is complex. The economics of displacement, in other words, are unattractive.
• Fourth, “while it is easy to imagine which tasks and what jobs will succumb to automation, it is far harder to forecast what and where new work will emerge… new innovations almost always generate new work as people deploy, master, maintain, refine, and improve new technologies, tools, and services.”

Autor is clear that the advent of AI has created greater uncertainty about the future of the labour market, and he isn’t necessarily optimistic. But it is right to underline the uncertainty. And, as he observes, a lot of these issues aren’t about technology. They’re about policy and politics.

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A version of this article is also published on my Just Two Things Newsletter.

The current discussion about the future of work seems to be monopolised by the version of the future in which technology destroys jobs. It has gained an air of inevitability, as if it is the only possible future. NESTA’s open minded report suggested that the “robots hypothesis” resonated because it connected “two powerful themes in popular culture: the rapid advance of IT, and the startling growth in inequality.” But there is a problem: it hasn’t happened before.

So it is worth considering reasons why it might just be a phase. The economic historian Carlota Perez has a model of technological development that describes five long waves, or surges, since the Industrial Revolution. Each is around 50–60 years and follows an S-curve pattern; the last quarter of each is marked by saturated markets, diminishing investment opportunities and declining returns. The first part of the 20th century was dominated by the oil and auto surge; the latter part by ICT. The ICT wave is now reaching the turning point at which returns start to fall.

On this model, finance is looking for new opportunities, and although it is too early to say what the next platform will be, and we’re still 10–15 years away from it, it is possible to imagine that the next technological surge might be built around, say, a material such as graphene.

Labour market woes

David Autor concludes that much of “the labor market woes” of the past decade are not down to computerisation, but to the financial crisis and reduced investment (starting with the dot.com collapse) and the impact of globalisation on labour markets. He suggests that many middle-skill jobs will prove more resistant to unbundling than advertised; while computers can do specific tasks, turning collections of tasks into self-contained jobs, and then automating them, requires substantial investment. In the long run, people are both more flexible and cheaper.

One implication is that the question of the future of work may actually be about power in the labour market. This leads to broadly political interpretations of the future of working conditions, ranging from Guy Standing’s formulation of the fragile “precariat”, facing intermittent, insecure work, David Weil’s description of the “fissured workplace”, in which many functions are sub-contracted, and the rise of campaigns for the Living Wage.

The technology cycle

The way ahead depends on how you read this bifurcation between the technologists and the sceptics. We don’t know who is right: there are no future facts. But there are some observations that can help shape our perspectives on this.

The first is that these widely divergent views are a feature of this point in the technology cycle. The most excitable projections of the future of the car were seen at just this point on the oil and auto curve in the 1950s.

The technology S-curve in Figure 1, based on the work of Carlota Perez, helps us to understand why. At this point, when the S-curve is at or approaching its second inflection point, people have been experiencing rapid technological change for the best part of two generations. The notion that “the only constant is change” has become a breathless platitude. The technologists’ perspective (point ’t’ in Figure 1) is a projection of this steep ramp. The sceptics note instead sign of falling returns and declining customer utility — and see a flattening of the line (point ’s). The gap is large, and one’s perspective on it is a matter of worldview, not evidence.

Figure 1: the technology S-curve and the future expectations gap

Source: Carlota Perez/ additional analysis by The Futures Company

Second, almost all business innovation and new business value is driven by the application of knowledge, and the way it is embedded in individuals, teams, and systems. The Futures Company has explored this in recent research with the Association of Finnish Work on the idea of ‘high value work.’ This is true of a whole range of knowledge, including knowledge of service and customers, and knowledge of culture and place, as well as technological knowledge. You don’t have to be Google to make this work for you. The most successful businesses use technology to complement and enhance this knowledge, not to replace it.

Third, the trend towards values and purpose in work is a deep and powerful one. If Millennials express a desire for meaningful work, this is also true more broadly. We are on the cusp of a transition to a world where, as Hardin Tibbs (2011) has argued, half of the populations of Europe and the United States subscribe to post-modern values (drawing on Inglehart) of autonomy and diversity. The workplace will not escape this trend.

Fourth, the bargain that businesses struck in the 1980s and 1990s, as they enforced flexibility and “downsized” headcount, may turn out to be a Faustian pact. Shedding jobs and exerting tight control of labour markets increased short-run profits. But at the same time that same control squeezed out their sources of growth. As both the OECD (Cingano, 2014) and the IMF (Ostry et al, 2014) have noted recently, wage inequality has been a further drag on economic growth. To regain growth, they are likely to have to increase wages and give back some control and power to their workforces.

A ‘perfect storm’

My own best guess is that we are not headed for long-run technological unemployment. I have changed my mind about this over the past year as I have spent more time with the evidence.

The explanation that seems best to fit present state of work and labour markets is that it has been through a “perfect storm” of a globalised workforce, the deskilling of routine work (which was highly vulnerable to automation) and the shift of these workers into manual or service work, and aggressive deregulation of labour markets driven by a neoliberal political agenda.

But, and it is a big but, we’re only part of the way through the dislocation to work and to labour markets caused by this perfect storm. Things will not get better quickly.

Looking at the shorter-term impacts, then, it’s possible to see a range of approaches to this turbulence in the world of work. Governments have options, largely about whether to intervene in labour markets to influence work outcomes, or not. But employers are also moving to new strategies, not out of goodwill but through self-interest.

Some scenarios

These options, highly simplified, are shown in the matrix (Figure 2), which contrasts laisser-faire approaches with interventionist approaches.

Figure 2: Indicative scenarios for the future of work

The race to the bottom: This laisser-faire option operates on the principle that labour market flexibility is the secret to increased employment in a globalised labour market. In practice, nearly all countries have increased flexibility and permitted more casualised work over the past decade. The evidence increasingly suggests, however, that the pursuit of low value jobs leads to a vicious cycle of low productivity, low investment, low growth, and low tax and social contribution from business.

This policy approach also involves government subsidy to employers, as low-paid workers are supported by state payments. Increasingly this looks like a political choice that is no longer supported by economic evidence.

Enlightened self interest: It appears that employers who pay better and create better working environments do better financially. Walmart is a relevant case. Over the last decade, its share price has been broadly stagnant, while Costco has outperformed it “by a considerable margin”, in terms of sales, earnings or stock market returns. One reason: according to HBR, far lower staff turnover means knowledge is kept in the company — and drives customer engagement. The Spanish retailer Mercadona similarly invests heavily both in training and stock management systems.

Wages and labour performance are also becoming part of businesses’ reputational capital. See, for example, the increasing success of the UK Living Wage campaign in signing up large companies as “living wage employers”. The public sector can encourage this, for example by giving tax breaks or other forms of support to companies who deliver such commitments.

Keeping the market honest: Turning to more interventionist approaches, the state can take the view that it wants to drive unscrupulous low-wage employers out of the market as a way of driving up standards and investment (low-wage employers spend less on training, and under-invest in capital equipment, which reduces productivity.) They would enforce (and increase) minimum wages, through regulation, law and procurement.

This removes free-riders from the market. Although conventional wisdom has argued in the past that minimum wage legislation costs jobs, this seems to be a weaker effect than claimed.

Re-imagining work: Much of our intervention in the labour market is driven by a view that it creates social goods, from an economic and  But it is possible that such findings are linked to a set of “modernist” social values that are rapidly giving way to “post-materialist” values. People with some income and a degree of social capital who do not have to work already worthwhile things to do, including volunteering. This is part of the argument for the Basic Income: that as we move to the “post-industrial” world envisioned by Daniel Bell, in which skills are more embodied in personal knowledge, that encouraging traditional work is no longer the only, or the best, way to get the social benefits from productive engagement.

The rise of the basic income

Until very recently, the idea of a basic income, a minimum sum paid to all people regardless of their work status, was right of the fringe of political discourse. But it has been moving rapidly towards the mainstream. The idea has deep roots: it goes back to H.G Wells, George Bernard Shaw, even Tom Paine. Betrand Russell promoted it as “a vagabond’s wage.”

The analysis in this provocation helps to explain why. It is a policy idea that helps to improve outcomes whether the technologists or the sceptics turn out to be right. And in the meantime it helps to shore up economies, and individuals, that are struggling in the slow readjustment of labour markets.

If the “robots” hypothesis is right, we’ll need a basic income to make the economy work (markets need people who can afford to buy products). If the market power argument is right, then basic income keeps employers honest, by ensuring they have to pay good enough wages, in good enough conditions, to attract and keep their workers. One interesting side effect is that it would mean that our fundamental notions of the value of paid work could be about to shift, for the first time since the Industrial Revolution.

The full-length essay was originally published at Future Agenda. The image at the top of the post is Ford Madox Ford’s painting Work, in the Birmingham Museum and Art Gallery, via Wikipedia under a Public Domain licence.