Work in the Digital Age

Challenges of the Fourth Industrial Revolution

Max Neufeind, Jacqueline O'Reilly, Florian Ranft

• Publisher: Policy Network
• Year: 2018
• ISBN:
  9781786609076
• Edition: 1
• Topic: Politics & International Relations
• Subtopic: Social Policy
• Index: Politics & International Relations

Shining a light on the very different experiences of work in the digital age, this book provides a unique contribution to the reform discussion on the consequences of the fourth industrial revolution. Drawing on a wide range of international expertise, contributors examine important policy challenges arising from the transformation of work as a result of the introduction of digital technology at work.
Authors in this volume discuss the effects of automation, platform business models, stagnating productivity, increasing regional disparities, and rising levels of inequality within and between countries. They consider how to unlock the vast economic and social potential of new technologies and the implications for policy reform to meet these challenges.
Mastering them requires developing a new inclusive narrative and progressive reform agenda. Such an agenda would be economic and political, and not determined universally by technology. The narrative is not only about what policymakers need to do, which is rather a lot. It is also about reforming established organisations and institutions, understanding new emerging players and supporting disaffected citizens in how the effects of these changes are going to affect their lives. The authors clearly pinpoint what needs to be done to support the transition to work in the digital era.

Part I

Debating the fourth industrial revolution

A

The destructive creation of employment in the digital age

Destructive creation

Explaining the productivity paradox in the digital age

Luc Soete

The technology in itself is neither good nor bad. It is the use which human beings make of any technology which determines both the nature and extent of the benefits.

—Christopher Freeman

Debate regarding the impact of new technologies on jobs and the organisation of work has raged for decades, if not centuries. While notable, this is hardly surprising. After all, we talk today about the fourth industrial revolution, following on from the first, second and third industrial revolutions. To gain insights into what the potential impact of the current phase of disruption might be, taking a look at previous industrial revolutions is both logical and revealing.

In this short contribution, I will attempt to provide some analytical insights into the possible consequences of the fourth industrial revolution for work and incomes. In doing so, it follows the more detailed analysis of Daniel Arnold and colleagues on the digitalisation and automation of manufacturing processes (Arnold et al. 2016; see also Arnold et al. this volume). My analysis will primarily be based on comparing current developments with the immediately foregoing, third industrial revolution, the one most closely linked to the emergence and rapid diffusion of microelectronics and the computer in the last quarter of the 20th century. I limit myself to such a comparison for two reasons.

First, most of the technologies associated with the fourth industrial revolution can undoubtedly be described as ‘new’ and ‘disruptive’ in their current and future applications, but are in essence based on improvements and developments to technologies which are characteristic of the third industrial revolution, including microelectronics and in particular the continuous exponential improvements in the performance of integrated circuits following Moore’s law.¹ As Klaus Schwab of the World Economic Forum put it, this built on the foundations prepared by the third industrial revolution. The improvements of these technological advancements, and improvements to processing speeds, continuously opened new areas for further research in robotics, and many other technologies associated with the fourth industrial revolution: 3D printing, quantum computing, artificial intelligence (AI) (Petropoulos this volume), the ‘internet of things’ (Fernández-Macías this volume), nanotechnology, biotechnology, materials science, energy storage, and in many other fields. Unsurprisingly, since the 1990s, microelectronics has been identified by economists as the most characteristic example of a so-called general purpose technology – one that affects all sectors of the economy (Bresnahan and Trajtenberg 1992).

Second, having written articles and books in the 1980s and 1990s on the impact of microelectronics and computerised technologies more broadly on employment and the organisation of work,² I feel that I am well placed to highlight in these pages some of the similarities and differences that exist between these two phases of industrial transformation as they have confronted our economies over the last 40 years. In particular, when debating the possible consequences of revolutionary transformations one can enter quite quickly into debates in which speculation and visions based more on science fiction of future societies can become dominant, which ultimately offers little help to policymakers. This contribution seeks to address this shortcoming in the literature.

Similarities with the past: The fear of job losses and a productivity paradox

The first similarity when comparing the third with the fourth industrial revolution is the fear of significant job losses. The similarity between Clive Jenkins’ 1979 book The Collapse of Work and the multitude of current analyses on the likely job losses associated with AI and robotics is striking and characteristic of the intrinsic fear of the way that new technologies can replace labour and automate routine jobs (Jenkins 1979). Arntz et al. (2016) refer to a widespread “automation angst”. In the 1970s and 1980s, following the widespread adoption of microelectronics, similar references were made to the literature of the 1930s and 1940s about the fear of ‘permanent’ technological unemployment, that would be brought about by automation.³ Whereas such fears were particularly articulated in Europe in the 1980s,⁴ far fewer concerns were raised about these issues in the US, where the debate shifted quickly to a more positive vision of the potential employment ‘displacement’ aspects of new technologies and the potential ‘skill-bias’ dimension associated with it – the fact that new technologies favoured skilled over unskilled labour, which increased the productivity of skilled labour, and hence the demand for skilled labour.⁵ Thus, the temporary friction that new technologies could introduce would be solved by education and training.

Paradoxically, the debate today regarding the fourth industrial revolution appears much more a feature of the US American rather than the European academic and public discourse, with important contributions from the likes of Erik Brynjolfsson and Andrew McAfee – curiously called The Second Machine Age – focusing on past trends towards jobless growth following economic recovery in the 1990s, and the role played by new digital technologies in replacing routine jobs (Brynjolfsson and McAfee 2014). The focus of the debate on employment displacement today has also shifted from the consideration of unskilled to routine jobs. The possibility that technology could be causing jobless US recoveries was first suggested by Jaimovich and Siu (2012), who argued that middle-skilled jobs involving routine tasks are susceptible to replacement by new technologies, and were likely to become permanently destroyed during recessions, which would result in slower job growth during any recovery. The focus here was again on new computer-based technologies, but the impact of employment displacement on routine white-collar work would be far greater than in the past. As Jerry Kaplan (2015), author of Humans Need Not Apply, puts it: “automation is now blind to the colour of your collar”. Brian Arthur (2011) describes this as the arrival of an underground, totally automated, digital ‘second economy’ that involves little to no physical employment in the ‘first economy’, while the title of Martin Ford’s (2015) book is The Rise of the Robots.

The dominance of the debate on the implications of new technologies linked to the fourth industrial revolution on jobs can be explained by the fact that no evidence for such trends can be found outside the US, where modern technologies appear unlikely to be causing jobless recoveries (Graetz and Michaels 2015). This is in all likelihood also a reflection of US global dominance in the new digital technology industries, as illustrated by the impact of the public statements on these topics by some of the leading American high-tech chief executive officers such as Elon Musk and Bill Gates (Delaney 2017; Kharpal 2017). In the 1980s it was similarly IBM who asked Chris Freeman and me to write a report on the impact on employment of computers (Freeman and Soete 1985). The report had no impact in North America, however. In Europe, by contrast, with unemployment remaining stubbornly high and barely recovering from the 1982 recession, the report led to a European Commission-backed expert study on the information society (European Commission 1996) and the inclusion in the Jobs Study launched in the mid-1990s by then secretary general of the OECD, Jean-Claude Paye, of a specific chapter on the potential impact of technology on employment and skills (OECD 1994). Today despite high levels of youth unemployment in many European countries there is, paradoxically apart from Germany, little interest and attention being paid to the emergence of new technologies that affect future jobs and the organisation of work.

A second, more striking similarity between the third and fourth industrial revolutions is the puzzling evidence of trends in productivity growth following the emergence of the aforementioned radical new technologies that are identified with the fourth industrial revolution, the ‘core’ variable in any econometric analysis on the impact of research and innovation on growth and welfare. Generally speaking, productivity refers to a measure of how much output (or income) is generated for a fixed amount of input, typically an average hour of work. Productivity growth is essential for understanding any discussion on the impact of new technologies on employment. Over the long run, the only way a society can generate higher standards of living is if the average level of productivity grows.

Rather surprisingly, and in contradiction to the revolutionary evidence on the emergence of new technologies, productivity did not increase following the third industrial revolution. In the 1980s, this became known as the ‘Solow paradox’, following a remark by Robert Solow (1987):

what everyone feels to have been a technological revolution, a drastic change in our productive lives, has been accompanied everywhere, including Japan, by a slowing-down of productivity growth, not by a step up. You can see the computer age everywhere but in the productivity statistics.

Even more surprisingly, the current evidence regarding the fourth industrial revolution appears to be accompanied by a similar lack of evidence of productivity growth. As Millar and Sunderland (2016) point out:

in a period where not only many new technologies are being introduced, more firms and countries are integrated into global value chains, [and] workers are more highly educated than ever, it remains surprising that productivity growth is not rising. For sure the financial crisis may be part of the explanation, but OECD data show that productivity growth has been slowing since the early 2000s in Canada, the United Kingdom and the United States (Millar and Sunderland 2016).

The link between productivity growth and technological change is not that straightforward, however. In earlier analyses I compared the evolution of technological change and its impact on productivity growth to the movement of a snake, where the head (technological progress) moves ahead while the tail remains more or less in the same place.⁶ In this analogy, productivity growth, as expressed by the average progress of the snake, is relatively limited, versus the tail moving to join the head, which remains more or less in the same place with little or no technological progress, while average productivity increases rapidly. It is as if the gap in productivity growth between global firms and the more domestically oriented firms has grown during the fourth industrial revolution, with the body of the snake expanding. As the current OECD secretary general, Angel Gurria (2016), put it: “The knowledge and technology diffusion ‘machine’ is broken.”

A lot has been learned over recent decades from research that analyses previous productivity ‘paradoxes’. There is broad agreement that much more attention needs to be paid to the time lags involved in the diffusion of new, ‘radical’ technologies. Those new technologies might for example involve a first phase of declining capital productivity as Paul David and Gavin Wright (1999) argued on the basis of historical comparisons, or might require essential organisational changes to fully exploit the often, in the first instance at least, unnoticed efficiency gains associated with new technologies, as Chris Freeman and Luc Soete (1987) and Paul David (1990) argued with respect to the second industrial revolution and the introduction of electricity. Here the authors point to the importance of the discovery of unit electric drive replacing line shaft (Devine Jr. 1983). Such changes also required the development of new skills and on-the-job learning before new technologies would result in overall efficiency gains, dubbed “the race between technology and schooling” by Jan Tinbergen (1975).

To conclude this first section; given the current low global productivity growth trends, concerns about the negative impact of the fourth industrial revolution on employment and job displacement appear not entirely convincing. There seems to be a tendency to overestimate both the speed and the impact of the new technologies associated with the fourth industrial revolution (Atkinson this volume), including AI, robotics, 3D printing, automotive driving, quantum computing and nanotechnology. For example, just look at the complexity involved in using robots simply to lift patients in a hospital, which requires numerous physical security interaction problems, or using AI to assess written exams. Historically, the evidence of skills disappearing as a consequence of the introduction of new technologies has not ushered in mass unemployment. Rather, digital technologies appear to have dramatically increased the distribution of the gains associated with the emergence of new technologies, as if monopoly capitalism has re-emerged now in digital form. Let me turn to these concerns in the next section.

Differences with the past: From general purpose to global platform technologies

In so far as the core of the fourth industrial innovation is primarily assoc...