HOW ROBOTS CHANGE THE WORLD - WHAT AUTOMATION REALLY MEANS FOR JOBS AND PRODUCTIVITY JUNE 2019 - Oxford Economics
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How Robots Change the World TABLE OF CONTENTS Foreword 3 Executive summary 4 Introduction 11 What drives the robot rise? 13 Three reasons for the robot surge 16 The impact of robots on manufacturing jobs 19 Global impacts 19 Regional impacts 22 The Robot Vulnerability Index 25 United States 27 Germany 28 United Kingdom 29 France 30 Japan 31 South Korea 32 Australia 33 The robotics dividend 35 Reshaping the labour market 37 Robots are coming to the service sector 40 The future impact of robots on five key service industries 43 Where service robots go from here 49 How to respond to the rise of robots 51 A framework for action 53 Appendix: econometric analysis 56 1
How Robots Change the World FOREWORD: The Shape of Things to Come The robotics revolution is on poorer local economies. In rapidly accelerating, as fast- many places, the impact will paced technological advances aggravate social and economic in automation, engineering, stresses from unemployment energy storage, artificial and income inequality in times intelligence, and machine when increasing political learning converge. The result polarisation is already a will transform the capabilities worrying trend. of robots and their ability to take over tasks once carried At Oxford Economics our out by humans. mission is to help our clients better understand an ever- The number of robots in more complex and fast- Adrian Cooper use worldwide multiplied changing world economy, in CEO and Chief Economist three-fold over the past two all its dimensions—and how to Oxford Economics decades, to 2.25 million. Trends successfully operate in it. Our suggest the global stock of clients look to us to explain the robots will multiply even faster forces shaping their economic in the next 20 years, reaching environment, help them as many as 20 million by 2030, anticipate the future, and plan with 14 million in China alone. for its uncertainties. The implications are immense, and the emerging challenges That is why we brought for governments and policy- together a team of our makers are equally daunting in economists, econometricians, their scale. modellers and technology experts from across our The rise of the robots will worldwide network of over boost productivity and 250 analysts to conduct an economic growth. It will lead, extensive research study too, to the creation of new to analyse the robotics jobs in yet-to-exist industries, phenomenon. We are pleased in a process of ‘creative to share our findings not destruction.’ But existing only with our clients but with business models across many all who want to understand sectors will be seriously the implications of one of disrupted. And tens of millions the most profound shifts of existing jobs will be lost, the world economy will with human workers displaced experience this century. by robots at an increasing rate as robots become steadily more sophisticated. For both people and businesses, the effects of these job losses will vary greatly across countries and regions, with a disproportionate toll on lower-skilled workers and 3
How Robots Change the World EXECUTIVE SUMMARY 20m Over the past decade, a robotics revolution has captured the world’s imagination. As their capabilities expand, so does the rate at which industries purchase and install these increasingly intelligent machines. Since 2010, the global stock of industrial robots has more than doubled—and innovations in engineering Number of manufacturing and machine learning portend an accelerated adoption of robots in service sector occupations over the next five years. jobs that could be displaced by industrial robots by This report sheds new light on both the current impact of robots 2030—8.5% of the global on manufacturing jobs around the world and the potential for robots to transform the much larger (but as-yet far less manufacturing workforce. automated) global services sector. To evaluate the implications of this ongoing robot revolution, we have brought together the combined expertise of Oxford Economics’ economists, econometricians, modellers, and subject-matter experts. The rise of robots has already had a profound effect on industrial employment around the world: today, approximately one of every three new manufacturing robots is being installed in China, the world’s great workshop. Our econometric modelling finds that on average each newly installed robot displaces 1.6 manufacturing workers. By 2030, we estimate that 1 as many as 20 million additional manufacturing jobs worldwide could be displaced due to robotization. 2 Lower-income regions are more at risk This great displacement will not be evenly distributed around the world, or within countries. Our research shows that the negative effects of robotization are disproportionately felt in the lower-income regions of the globe’s major economies—on average, a new robot displaces nearly twice as many jobs in lower-income regions compared with higher-income regions of the same country. At a time of worldwide concern about 3 growing levels of economic inequality and political polarisation, this finding has important social and political implications. Given the stakes, policy-makers need an early warning system to help them mitigate the risks of automation on employment. As part of this study, we have developed a Robot Vulnerability Index that ranks every region of seven developed economies in terms of how susceptible their respective workforces are to the installation of industrial robots (see page 18). 4 1 This finding is based on an analysis of a large, regional panel-dataset of robot stock, and other labour market indicators, over a 11 year timeframe, for 24 EU countries (minus Croatia, Cyprus, Luxembourg and Malta), along with Norway, the United States, Japan, and South Korea. 2 Countries included in this estimate account for more than 90% of industrial robot installations: EU 28, US, Japan, South Korea, Australia, China, Taiwan, Thailand, Mexico, India, Canada, Singapore, Brazil, Turkey, Malaysia. We assume the rate of robot installations in manufacturing up to 2030 follows the latest projections by the International Federation of Robotics, and we also account for long-term depreciation of existing robot stock. 3 Throughout this report, higher- and lower-income regions are defined as those with average household income levels above and below the national average, respectively.
How Robots Change the World In many cases, our Index highlights that the most vulnerable regions are somewhat removed from the wealthier districts of their home countries—such as Cumbria in the UK, Franche- Our research shows Comté in France, and the high desert of Eastern Oregon in the the negative effects US. These rural regions often include towns or cities with strong of robotization are manufacturing heritages that play a surprisingly large part in the regional economy. In contrast, regions that surround knowledge- disproportionately felt in intensive cities, such as Toulouse and Grenoble in France, or the lower-income regions Munich and Stuttgart in Germany, typically show much lower of major economies. levels of vulnerability to the rise of the robots. This is also true of capital cities such as London, Paris, Seoul, and Tokyo. Fig.1: Job losses from robots hit lower-income regions harder 4 Change in number of jobs due to one additional robot -1.6 Average effect Lower- -2.2 income regions Higher- -1.3 income regions -2.5 -2.0 -1.5 -1.0 -0.5 0.0 Long-term impact Short-term impact Source: Oxford Economics 4 Our modelling differentiates between a “short-term” effect, within the year of a robot installation, and a longer-term effect that builds over 10 to 15 years. 5
How Robots Change the World The $5 trillion robotics dividend While regional impacts vary, fears about permanent global job As the pace of robotics destruction generated by robots appear somewhat exaggerated. adoption quickens, Our study shows that the current wave of robotization tends policy-makers will be to boost productivity and economic growth, generating new employment opportunities at a rate comparable to the pace faced with a dilemma: of job destruction. We estimate that a 1% increase in the stock while robots enable of robots per worker in the manufacturing sector leads to 0.1% growth, they exacerbate boost to output per worker across the wider workforce. income inequality. These increases are large enough to drive meaningful growth. Using Oxford Economics’ Global Economic Model (GEM), we calculated how changes in the rate of installation of industrial robots could affect the global economy. Overall, we found that a faster adoption of robots has a positive impact on both short- and medium-term growth. For example, boosting robot installations to 30% above the baseline forecast by 2030 would lead to an estimated 5.3% boost in global GDP that year. This equates to adding an extra $4.9 trillion per year to the global economy by 2030 (in today’s prices)—equivalent to an economy greater than the projected size of Germany’s. The future of service robots Robots are steadily gaining traction in specific segments of the service economy, from baggage handling in airports to loading inventory in warehouses. In this report, we assess the likely impact (and timeframe) of service robot roll-outs in five key sectors: healthcare, retail, hospitality, transport, and construction and farming. For the purposes of this study we are considering robots only as physical machines, and not including the already-popular service-industry software like robotic process automation (RPA) that can speak, hear, read, conduct transactions, automate processes, and so on. One key consideration for anticipating the pace of robot deployment in service industries is the environment in which these robots may be asked to operate—in particular, the extent to which service jobs include repetitive functions. Jobs like warehouse work are in imminent danger, while other jobs in less structured environments will likely be carried out by humans for decades to come. 6
How Robots Change the World It will be difficult for machines to replace humans in service sector occupations that demand compassion, creativity, and social intelligence. Physical therapists, dog trainers, and social It will be difficult for workers are likely to remain secure in their jobs, for instance, machines to replace even if truckers and warehouse workers see the future of their humans in service sector jobs jeopardised. occupations that demand Policy implications compassion, creativity, As the pace of robotics adoption quickens, policy-makers will and social intelligence. be faced with a dilemma: while robots enable growth, they exacerbate income inequality. Automation will continue to drive regional polarisation in many of the world’s advanced economies, unevenly distributing the benefits and costs across the population. This trend will intensify as the impact of automation on jobs spreads from manufacturing to the services sector, making questions about how to deal with displaced workers increasingly critical. The challenges will be daunting. Our analysis of the job moves of more than 35,000 US individuals over the course of their careers shows that more than half the workers who left production jobs in the past two decades were absorbed into just three occupational categories: transport, construction and maintenance, and office and administration work. Ominously, our analysis found that these three occupational areas are among the most vulnerable to automation over the next decade. These findings, however, should not lead policy-makers and other stakeholders to seek to frustrate the adoption of robot technology. Instead the challenge should be to distribute the robotics dividend more evenly by helping vulnerable workers prepare for and adapt to the upheaval it will bring. Policy- makers, business leaders, technology companies, educators, and workers all have a role to play. We conclude the report with a framework for action for each of these groups to navigate the challenges and opportunities that robotization will bring. Robots are on the rise as never before. Preparing for and responding to the social impacts of automation will be a defining challenge of the next decade. 7
A vision of human-free production in Italy.
How Robots Change the World INTRODUCTION Over the past decade, the warned the disruption global stock of industrial caused by the automation of robots has risen dramatically, cognitive skills could have “as This era of automation and is projected to grow even wrenching and lengthy [an] presents significant faster in the next 10 years, impact on the jobs market” as opportunities for led by China’s record pace Britain’s industrial revolution. 5 of installation. The robotics He urged policy-makers to businesses to boost industry has experienced learn the “lessons of history,” productivity. But there exponential investment growth, with governments stepping will be winners and losers upending decades-long up to train workers for the trends of gradual and steady new world of work while in the labour market. expansion. A convergence providing a welfare state of innovations in digital to cushion the blow from technologies (e.g., artificial technological change. intelligence and machine learning) along with advances To shed new light on the future This multi-disciplinary in robotics engineering and impacts of automation, Oxford approach enables us to energy storage, is dramatically Economics combined the construct a set of questions transforming the capabilities expertise of its economists, for policy-makers about of robots. New breeds of econometricians, modellers, the impact of increased “cobots”—small, highly mobile, and other subject-matter robotization—as well as other and dextrous machines that experts around the world. Our processes of automation— can readily collaborate with analysis begins by modelling on economies and societies humans—are entering the the latest and best data for around the world. Greater manufacturing and logistics industrial robot installations understanding of these issues arenas, and can be easily in all manufacturing sectors will be key to making the most “trained” to work with humans around the world. These are of robot-driven gains in the to optimise productivity. credible, longitudinal datasets future while supporting and from which we draw fresh protecting those who stand This era of automation presents insights regarding the impact to lose out from this era of significant opportunities of robots on employment dramatic technological change. for businesses to boost and productivity in different productivity. But there will countries, and in the higher- and be winners and losers in lower-income regions within the labour market as these those countries. opportunities are seized. Millions of workers around the Building on these insights, we world, across all sectors of the then assess the future impact economy, will see many of the of increased robotization on functions they were once paid global service sectors—an area to perform handled instead where rates of robot adoption by new technology. Millions have been much lower than more will see the nature of in manufacturing to date, their jobs altered significantly but which employs a much as they are required to master greater proportion of the global new skills to collaborate with workforce. Around three- intelligent machines. In autumn quarters of workers across 2018, Andy Haldane, the Bank advanced economies earn their of England’s chief economist, wages from service labour. 5 Haldane warns AI threatens lengthy widespread unemployment’ (Financial Times, 20/08/2018). 11
How Robots Change the World WHAT IS OUR DEFINITION OF A ROBOT? The quantitative modelling industrial robots at the end the impact of robots on aspects of this study are of 2016, according to the employment and productivity focused on industrial International Federation of levels. But the story will robots used in all types of Robotics. Automation has long 6 continue to unfold as manufacturing around the been a critical component of manufacturing itself undergoes world. These automatically manufacturing, particularly rapid technological change. In controlled, reprogrammable in the automotive industry, recent years, new, collaborative machines are typically which in 2016 accounted for categories of AI- and cloud- used for a host of physical more than 43% of the total enabled robots have emerged activities in production, operational stock of industrial that seamlessly bridge the such as processing materials robots in global manufacturing. gap between skilled manual (laser cutting, mechanical The industry is at the leading assembly and automated grinding), assembling and edge of robotic applications. production. These “cobots” disassembling, precision create new opportunities for welding, painting, and The quantitative analysis in this automation—even on short, handling a wide range of report is focused on physical mixed production runs that operations for measurement, machines for which rich, require both high levels of inspection, packaging, longitudinal data exists. We do precision (at which robots bending, and casting. not incorporate into this aspect excel), and sophisticated These robots can be fixed of the analysis the growing vision, handling, and creativity installations or mobile, role of disembodied software (where human workers and the latest versions are applications sometimes continue to add great value). increasingly powered by referred to as robots or bots, artificial intelligence, so they including programmes used in are “smart” and responsive to call centres and in RPA. their surroundings. Based on robust data, our Manufacturing accounted analysis of the manufacturing for more than 86% of the sector offers the best world’s operational stock of perspective to date on 12 6 International Federation of Robotics (2017) “World Robotics: Industrial robots”
How Robots Change the World WHAT DRIVES THE ROBOT RISE? 20% Since 2010, the global stock could have as many as 14 of robots in industry has more million industrial robots in than doubled: as many robots use, dwarfing the rest of the were installed in the past world’s stock of industrial four years as over the eight robots as it reinforces its Proportion of the world’s previous. During this period, position as the world’s primary the centre of gravity in the manufacturing hub. robot stock located in world’s robot stock has shifted China. Approximately towards new manufacturers, In contrast, though it has every third robot is now mainly in China, Korea, and grown by around 370,000 Taiwan but also India, Brazil, units since 2000, the installed there. and Poland. combined robot inventory of the US and Europe has fallen Approximately every third to under 40% of the global robot worldwide is now share from its peak of close installed in China, which to 50% in 2009. And Japan— accounts for around one- formerly the world leader in fifth of the world’s total automation—has reduced stock of robots—up from its active stock of robots by just 0.1% in 2000 (see Fig. around 100,000 units since 2). In 2017, China expanded the start of the millennium, its lead as the world’s largest in line with a rebalancing market for industrial robots, of its economy away from accounting for 36% of global manufacturing and the sales, up from 30% in 2016. If migration of many production this trajectory of investment facilities offshore, especially continues, by 2030 China to China. Fig. 2: Robot installations by country, 2000 to 2016 7 New robot installations 350,000 300,000 250,000 Rest of World 200,000 China 150,000 South Korea US 100,000 Rest of Europe 50,000 Germany 0 Japan Source: IFR 00 01 02 03 04 05 06 07 08 09 10 0 11 0 12 0 13 0 14 0 15 0 16 20 20 20 20 20 20 20 20 20 20 20 2 2 2 2 2 2 7 Note: US data include immaterial robot installation numbers for Mexico and Canada prior to 2010 13
How Robots Change the World The automotive sector has of new robot installations in long been the predominant high tech manufacturing grew 8 user of robots: innovations to 31% in 2016, from 21% in in autonomous and electric 2000, reflecting rapid growth vehicle manufacturing requires both in the sector and in the increasingly sophisticated integration of robots into production chains, and this production. Robots have also has sparked demand for new, been increasingly introduced more powerful, and intelligent into the production of rubber machines to build them. and plastics, and are slowly However, other manufacturing finding their way into the food industries are now taking a and beverage manufacturing more prominent role in robot industry (see Fig. 3). use. For example, the share Fig. 3: New industrial robot installations across the world by usage, 2000 vs. 2016 Rubber & Other plastic products 0 53,000 16,000 84,000 25,000 21,000 103,000 91,000 Automotive High tech Inner circle—2000 Outer circle—2016 Numbers refer to global robot installations in each sector for that year. Source: Oxford Economics 8 High tech manufacturing is defined as electronic devices, semiconductors, LCDs, LEDs, computer equipment, telecommunication equipment, medical 15 equipment, and electrical appliances
How Robots Change the World THREE REASONS FOR THE ROBOT SURGE Our analysis of the use of of a robot fell by 11% between Innovations have made today’s industrial robots across the 2011 and 2016. 9 robots smaller, more sensitive manufacturing sector identifies to their environments, and more three main drivers behind this Rising labour costs in major collaborative. Thanks to AI, they new pace of adoption: price, manufacturing economies can learn from their experiences innovative applications, and also contribute to increasingly and make decisions informed consumer demand. attractive pricing dynamics. In by data from a network of other China, for example, unit labour robots. These developments Trend #1: Robots are becoming costs in manufacturing have have helped propel robot cheaper than humans increased by more than 65% adoption in sectors beyond the since 2008. Wage rates have automotive industry (see Fig. 4). The rapid expansion in robot also been rising consistently installations is driven in part in Korea, Japan, the US, and by the plummeting real costs Germany, in part due to the of the machines. As with ageing of the population in other advanced technologies, these countries. exponential growth in the processing power of Trend #2: Robots are rapidly microchips, extended battery becoming more capable lives, and the benefits of ever-larger, smarter networks As robot technologies improve, have all dramatically increased they are being used in ever- the per-unit value of many more sophisticated processes, technological components, in more varied contexts, and while the average unit price can be installed more rapidly. Fig. 4: Robot adoption growing faster outside the automotive sector Percentage change in robot densification between 2011 and 2016 United States 14% 40% China 199% 267% - Japan -22% 7% South Korea 51% 83% - -1% Germany 27% -50% 0% 50% 100% 150% 200% 250% 300% Dark bar=Automotive sector Source: IFR, Oxford Economics Light bar=Other sectors 16 9 Figures may be subject to upward bias by a trend in robot sales toward smaller installations
How Robots Change the World Trend #3: Demand for journey. Despite its rapidly and the establishment of manufactured goods is rising, growing inventory, China high-tech manufacturing, and China is investing in only uses 68 robots per we expect China will likely robots to position itself as the 10,000 workers in general continue its acceleration in global manufacturing leader manufacturing, compared robot investments for the with 303 per 10,000 in next decade. By 2030, if the Much of the growth in robot Japan, and 631 per 10,000 in investment in industrial robots stock over the past decade South Korea. The imbalance continues to grow at its current can be attributed to rising between stock and density is trajectory, China will have close demand for manufactured shown in Fig 5. Large sections to eight million industrial robots goods. China is at the heart of China’s workforce are still in use, as its robot density of this change: it has become engaged in manual processes, approaches levels comparable the world’s largest automotive meaning vast potential remains with the average across the manufacturing site, and a for further robotization of its European Union. 10 major producer of consumer manufacturing sector—moreso electronic devices, batteries, than in any other country. and semi-conductors— all highly robot-intensive With government policies manufacturing sectors. aimed at expanding the This trend is set to continue, use of electric vehicles as China is still only at the (which will require large- beginning of its automation scale battery production), Fig. 5: Chinese scope for catch-up in robot density (2016) Column=Robots per 10,000 workers (LHS) Stock of robots in manufacturing (RHS) 1,000 300,000 900 250,000 800 700 200,000 600 500 150,000 400 300 631 100,000 200 309 303 50,000 100 189 0 68 0 South Korea Germany United States Japan China Source: IFR, Oxford Economics Robotization Potential 10 2030 projections based on short-term International Federation of Robotics forecasts, controlling for longer-term stock depreciation. 17
How Robots Change the World THE IMPACT OF ROBOTS ON MANUFACTURING JOBS While China leads the way in manufacturing also create in robot investment, many employment across the wider other major manufacturing economy. We explore this Throughout history, economies have also rapidly positive economic impact in the geographical expanded their use of greater detail on page 35. imbalance between the industrial robots in recent years. We quantified the At a regional or local level, positive and negative impact of this global rise in however, the impact on jobs effects of automation has industrial robot inventory on varies greatly. Since most had significant economic, manufacturing employment manufactured goods are highly since 2000. We also forecast tradable (because they are social and political the number of manufacturing cheap to transport and have a implications. jobs that could be lost to long shelf life), the households robotization around the world that benefit from cheaper by 2030, and the distribution goods are widely dispersed. of potential changes across By contrast, the communities higher- and lower-income most reliant on manufacturing as it adopts automation: regions within countries. jobs—and thus most affected the true productivity gains by the introduction of new can take several years to It’s important to note that technology—are typically materialise as workers receive despite the rising pace of much more concentrated. appropriate training, and as robotics investment and Throughout history, this firms understand how best to installation, popular fears geographical imbalance reorganise their production that robots will create huge between the positive processes and business swathes of unemployment and negative effects of models to exploit the benefits around the world are automation has had significant of the new technology at scale. somewhat misplaced. economic, social, and political This is because the value implications. We developed an created by robots across econometric model to quantify the economy more than the impact on manufacturing offsets their disruptive jobs in each country’s higher- impact on employment. and lower-income regions. Manufacturers automate their production processes to boost GLOBAL IMPACTS productivity. Since 2004, each new This creates a “displacement industrial robot installed in the effect” on manufacturing jobs, manufacturing sector displaced since the new technology an average of 1.6 workers from can perform a worker’s job their jobs. The full impact takes more cost-effectively for a time to materialise, however. given standard of quality. It Within the first year of a robot’s also reduces unit-production installation, roughly 1.3 workers costs that, in a competitive are displaced, on average, from market, translate into lower their job; this extends to 1.6 prices and effectively raises workers over subsequent years. the real spending power of consumers. Therefore, the This finding is consistent with same robots that displace jobs other evidence from industry 19
How Robots Change the World A NOTE ABOUT OUR ECONOMETRIC MODELLING Our study presents our labour markets—these include econometric analysis of the changes in real wages, shifts link between robot installations in global trade patterns, and and manufacturing job losses other unobservable regional at both the national level and and industry-related factors. for regions within specific countries. Our model focuses See Appendix for a on 29 manufacturing-intensive full explanation of this countries using 11 years of methodology. data, offering unprecedented levels of detail about the past and future impacts of robotization on manufacturing Fig. 6: Our econometric modelling framework jobs around the world. Source Variable In addition to providing absolute figures, we have calculated the marginal impact Momentum of each additional robot Oxford Manufacturing jobs per Economic’s installation on manufacturing Global capita in previous year jobs across the countries Economics Data used for 29 countries over 11 years from 2004 to and studied. Our modelling Global Economic 2016, disaggregated by region and sector. performance establishes how this impact Cities databanks compares between lower- and GDP per capita higher-income regions within Employment impact a country (defined as regions with average household Outsourcing income levels above and below Share of Comtrade manufacturing jobs the national average). database; Trade with China in local economy Oxford Economics Drawing on data from the calculations Export Manufacturing jobs per 1,000 workers International Federation of aptitude Trade with the rest Robotics (IFR), an industry of world trade group, we investigated the ways in which the installation of additional Region-specific industrial robots affected local factors We isolate the average marginal manufacturing employment Panel data techniques impact on manufacturing jobs at local level from each in Japan, the European Union, additional robot intsalled. the United States, South Korea, IFR; Robot and Australia. By constructing 11 Oxford densification Economics a large, regional panel dataset calculations Robots per 1,000 workers of robot stock alongside other labour market indicators over an 11-year timeframe, we were able to isolate the impact of robotization versus other strong influences on local 20 11 Despite its prominence in global manufacturing, China was omitted from our econometric modelling exercise due to a lack of data in other important modelling variables.
How Robots Change the World We also calculated the total workforce (some 400,000 We have projected the growth amount of manufacturing jobs jobs). In China, as many as in the active robot stock lost to robotization throughout 550,000 manufacturing across major manufacturing the world since the turn of jobs have been displaced economies to 2030, based on the century, considering 12 by robotization since 2000, the IFR’s three-year growth factors such as redundancies equivalent to around 1% of projections for new robot caused by off-shoring and the its current manufacturing installations and including globalisation of supply chains. workforce. the need to replace some In all, we estimate that around robots over time as they 1.7 million manufacturing jobs Assuming robot investments deteriorate. On this basis, have been wiped out since continue at their current we expect almost 20 million 2000 due to the global rise of pace, many millions of manufacturing jobs to industrial robots. Fig. 7 illustrates additional manufacturing disappear around the world the impact by country: in the jobs are likely to be because of robotic automation US, we estimate that more displaced by robots by (see Fig. 8). Put differently, if than 260,000 jobs have been 2030. While considerable current trends hold, the global lost to robots (around 2% uncertainties exist around manufacturing workforce of today’s manufacturing the rate of adoption of new would be 8.5% larger by 2030 workforce), while in the technologies, it is possible if robots were not remaking European Union, robots have to estimate the likely impact the market. 13 taken the place of 1.5% of of robotization in the the current manufacturing coming years. Fig. 7: Cumulative jobs losses implied by automation since 2000 Cumulative jobs lost since 2000 0 -200,000 400,000 -400,000 550,000 EU28 -600,000 China 260,000 -800,000 US -1,000,000 340,000 South Korea -1,200,000 Rest of world -1,400,000 100,000 -1,600,000 -1,800,000 01 1 02 0 03 04 0 05 06 0 07 08 09 0 10 20 1 0 12 0 13 0 14 0 15 0 16 20 20 2 20 2 20 2 20 20 2 2 2 2 2 2 Source: Oxford Economics 12 Global estimate based on more than 90% of known global industrial robot installations, according to the International Federation of Robotics. 21 13 Manufacturing employment projections from Oxford Economics’ Global Industry model.
How Robots Change the World REGIONAL IMPACTS HIT levels are either above or HARDER IN LOWER-INCOME below the national average. It Installing one extra AREAS also controls for regionally- industrial robot in a specific labour market lower-income region Our modelling also allows shocks and underlying us to look at the impact employment trends. leads to almost twice of automation on different as many manufacturing regions within each country. Why do these regional job losses as in higher- These regional differences differences occur? They are offer important social and not driven by the relative size income regions. political implications for of the manufacturing sector— policy-makers. manufacturing accounts for roughly the same share Our analysis shows that of economic activity and installing one extra industrial employment in both lower- robot in a lower-income and higher-income regions region leads to almost twice in our sample, and our model as many manufacturing job controls for sector size. But losses as in higher-income there are structural differences regions (see Fig. 9). This in the composition of finding is based on an employment in manufacturing analysis of our 29 sample that influence the impact countries, distinguishing robots have. between regions whose average household income Fig. 8: Projected cumulative jobs losses by automation, up to 2030 14 0 EU28 -5,000,000 China -10,000,000 US -15,000,000 South Korea Rest of world -20,000,000 -25,000,000 18 0 19 20 0 21 22 23 24 25 26 27 28 29 30 20 2 20 2 20 20 20 20 20 20 20 20 20 Source: Oxford Economics 22 14 Projections for ‘Rest of World’ include countries covering more than 99% of the estimated global total.
How Robots Change the World Fig. 9: Manufacturing job losses skew towards lower-income regions Change in number of jobs due to one additional robot -1.6 Average effect Lower- -2.2 income regions Higher- -1.3 income regions -2.5 -2.0 -1.5 -1.0 -0.5 0.0 Long-term impact Short-term impact Source: Oxford Economics Manufacturing workers in contrast, a significantly higher carry out are—on balance— lower-income areas tend to proportion of managers easier to automate. These have lower skill levels and are and professionals in the efficiency gains can be therefore more vulnerable to manufacturing industry are in realised by laying off staff, automation. There is typically higher-income regions. or by moving the firm to a a difference in the number This vulnerability has evolved new, more productive (and of robots per manufacturing over time. In the past, lower- likely more automated) site. worker between higher- income areas competed with Either way, the manufacturing and lower-income regions, more expensive cities and workers in those regions are indicating that those in regions for manufacturing at risk. lower-income regions are, on investment, with the lure average, less productive. Data of lower unit costs of Moreover, the regions of a from the UK Labour Force production. This competitive country most likely to shed Survey, for example, shows edge was a consequence manufacturing workers will that manufacturing workers in of relying on a lower-paid, not benefit equally from the lower-income regions of the less-productive workforce to “robotics dividend” —the UK are more likely to work in carry out lower-skilled jobs. new jobs created from the lower-skilled occupations— In the new era of automation, productivity boost that feed elementary workers and the occupational mix in lower into the wider economy. machine operatives account income areas means those Instead, increased industrial for around one-third of the same manufacturers face automation will tend to workforce in lower income the biggest opportunities exacerbate the regional regions, compared with 22% for efficiency savings. The inequalities that already exist in higher-income regions. In functions their employees within advanced economies. 23
How Robots Change the World THE ROBOT VULNERABILITY INDEX It is vital for policy-makers to economic upheaval in the understand how an uneven years ahead. Mapping the distribution of robotics will vulnerability to robot adoption Our Robot Vulnerability affect different parts of their across all regions of these five Index shows that specific country. We have developed advanced economies revealed regions that are at a Robot Vulnerability Index some common patterns, to help identify which regions which can be summarised in highest risk of labour within our chosen economies three key trends. disruption—but also (the US, Germany, UK, France, reveals some common Japan, South Korea, and Trend #1: Existing Australia) will be hardest hit by inequalities will patterns across regions. the ongoing automation of the intensify manufacturing sector. Successful economic Our index produces a performance at the regional vulnerability score for level in advanced economies each sub-national region , 15 is usually inversely correlated comprised of three equally with robot vulnerability. In weighted indicators: the UK, France, and Germany, those regions that have • Local dependence performed best in recent on manufacturing years (in terms of overall GDP employment—defined as growth) are the least exposed the manufacturing share to future robot automation, of total employment in the and vice versa. region. • Future readiness of local This means the regional industry—characterised inequalities that exist within by a region’s current countries, such as England’s intensity of robot use north-south divide, could be in manufacturing, exacerbated by the rise of controlling for the type the robots. This trend has of manufacturing activity important implications for undertaken, and measured policy design in advanced relative to international economies pursuing competitors. international competitiveness • Productivity of the local through automation. manufacturing workforce— measured relative to the national average. The index is thus designed to highlight regions that are economically dependent on a less productive (or lower-skilled) manufacturing industry and do not currently use many robots, since these areas are at highest risk of 15 Sub-national regions correspond to European NUTS 2, US States, Japanese prefectures, Australian states, and South Korean districts. 25
How Robots Change the World Trend #3: Rural Country-by-country analysis regions mask hidden The pockets of workers vulnerabilities Over the next five pages, we most vulnerable to illustrate each local region’s automation can often be The pockets of workers most relative vulnerability to future vulnerable to automation can manufacturing automation, found in rural areas. often be found in rural areas. according to our Robot Despite relatively sparse Vulnerability Index. Each populations, these regional map is colour-coded from economies are frequently “high vulnerability” to “low grounded to isolated towns vulnerability” regions (relative Trend #2: Many major with more manufacturing- to the rest of that country) cities are safe (for now) intensive industrial and includes commentary structures on which the on some of the most striking Our analysis shows that major wider region depends. This geographical results. cities are often safe havens is especially problematic for workers in the face of when manufacturing in these robot led job displacement. towns is characterised by Diversified economies depend traditional, labour-intensive less on manufacturing jobs, techniques, low levels of and higher labour costs mean productivity, and dated manufacturers located there manufacturing processes. are already highly productive and tend to employ more In many countries, such highly skilled workers. London, regions have often been left Paris, Seoul, Sydney and Tokyo behind as metropolitan centres are all examples. prospered, and those dynamics have generated political But manufacturing-intensive polarisation. This highlights the cities (including many in importance of taking policy South Korea) face a more action to cushion the likely uncertain future. Cities impact of robotization in these with large populations that vulnerable areas. are more dependent on the manufacturing sector for employment but lag their industry peers in robot intensity and labour productivity are vulnerable to disruption. Fierce competition will ultimately lead these city- based industries to pursue further automation or risk losing out to more productive competition elsewhere. Either way, additional job displacement of current manufacturing workers is likely. 26 1 Xxxxxx
How Robots Change the World UNITED STATES Oregon is the most vulnerable state in the US to a future acceleration in robot installations. The state has had success in transitioning out of traditional sectors into the production of high-tech components. But high dependence on Low vulnerability manufacturing, particularly in and Lower-medium vulnerability around Portland, and the state’s exposure to globally competitive Upper-medium vulnerability sectors, mean its workers are High vulnerability vulnerable to rapid technological progress. New England states tend to have low While Texas and its vulnerability to the future neighbour Louisiana are two spread of manufacturing particularly vulnerable states in robots, as do those with a higher the south, Indiana is equally reliance on tourism (Florida, vulnerable in the mid-west. It is Nevada, Hawaii). The same is true associated with steel-making (and for New York state, which, with heavy industry more Alaska alongside a significant generally), albeit with an Hawaii manufacturing base has a high increasing focus on developing concentration of financial the growth of its higher-value, and business services. knowledge-based industries. Most State: Index Score: Least State: Index Score: vulnerable Oregon 0.58 vulnerable Hawaii 0.17 states Louisiana 0.58 states District of Columbia (DC) 0.18 Texas 0.50 Nevada 0.25 Indiana 0.46 Florida 0.25 North Carolina 0.46 Vermont 0.26 27
How Robots Change the World GERMANY Germany’s least-vulnerable region is Hamburg. It has a low level of dependence on manufacturing jobs, and what manufacturing it does have is typically advanced and highly productive, with cutting-edge levels of automation. Low vulnerability Lower-medium vulnerability Upper-medium vulnerability High vulnerability A cluster of four eastern regions close to the Czech border—Chemnitz, Thüringen, The home regions of BMW Oberfranken, and and Mercedes—Bavaria and Oberpfalz—look to be the most Stuttgart, respectively—are vulnerable to robotization. All have examples of future-ready high concentrations of production ecosystems, featuring a manufacturing employment, and highly skilled, highly productive (typically) low levels of workforce. productivity—particularly Chemnitz and Thüringen. Most Region: Index Score: Least Region: Index Score: vulnerable Chemnitz 0.56 vulnerable Hamburg 0.06 regions Thüringen 0.49 regions Darmstadt 0.13 Oberfranken 0.49 Oberbayern 0.17 Oberpfalz 0.47 Köln 0.19 Freiburg 0.46 Berlin 0.20 28
How Robots Change the World UNITED KINGDOM East Yorkshire and Northern Lincolnshire, Shropshire and Staffordshire, Cumbria, and West Wales and the Valleys exhibit the highest vulnerability scores in the UK. Low vulnerability These regions are relatively Lower-medium vulnerability dependent on manufacturing for employment, and have a relatively Upper-medium vulnerability high incidence of low-skilled High vulnerability workers. The UK’s most Robotization will vulnerable regions to exacerbate the robotization can be found in north-south divide. Inner its more rural areas. These London is perhaps the least sparsely populated regions vulnerable part of the country to may contain towns with the rise of robots, and the South East concentrated manufacturing region is similarly well-placed for the industries. Cumbria tops next phase of industrial automation. our UK Index. Manufacturing operations in these regions tend to be more advanced and more automated than in other parts of the country, reflecting the higher cost of labour here. The West Midlands’ manufacturing processes are already among the most automated in the UK, and the region is nearly as robot-dense as international market leaders. However, it is also characterised by low levels of productivity, and with a high dependence on manufacturing employment, which could still imply a challenging future. Region: Index Score: Region: Index Score: Cumbria 0.59 Inner London (East) 0.15 Most East Yorkshire & Least Inner London (West) 0.17 vulnerable North Lincolnshire 0.59 vulnerable Outer London regions Shropshire & regions (West & NW) 0.20 Staffordshire 0.58 Berks, Bucks & West Wales & Oxfordshire 0.25 the Valleys 0.56 Surrey, East & Lincolnshire 0.54 West Sussex 0.28 29
How Robots Change the World FRANCE The Île-de-France, centred on Paris, is France’s least-vulnerable region. It is least dependent on manufacturing jobs, and what manufacturing activity it does have is (a) highly productive and (b) the most robot-intensive in Low vulnerability the country, alongside the Lower-medium vulnerability Midi-Pyrenees. This means it has already undertaken Upper-medium vulnerability significant levels of High vulnerability automation We find that the most France’s most southerly vulnerable region to regions, plus Rhône-Alpes, robotization is Franche-Comté. are collectively the ‘runners-up’ France’s most behind Paris in terms of their low manufacturing-intensive region vulnerability on our Index. These is nevertheless relatively rural and regions are home to advanced sparsely populated. Its relatively high-tech manufacturing companies, low rate of robotization means notably in leading cities such as there could be high levels of Toulouse (home to Airbus, among automation coming. others) and Grenoble, and thus benefit from I a future-ready, highly skilled workforce. Region: Index Score: Region: Index Score: Most Franche-Comté 0.61 Least Île de France 0.03 vulnerable Basse-Normandie 0.51 vulnerable Provence-Alpes-Côte regions Picardie 0.51 regions d'Azur 0.26 Limousin 0.51 Languedoc-Roussillon 0.30 Auvergne 0.49 Aquitaine 0.35 Midi-Pyrénées 0.36 30
How Robots Change the World JAPAN Hokkaido, Japan’s northernmost island—famous for brewing beer Low vulnerability and as a skiing destination and gateway to the Hokkaido Lower-medium vulnerability mountains—is one of the least Upper-medium vulnerability manufacturing-intensive parts of the country. After Tokyo, it is the High vulnerability second-least vulnerable region on our Index. Some of Japan’s most mountainous prefectures feature among the most vulnerable to job losses. Although sparsely populated, these large regions are punctuated with traditional manufacturing enclaves, which may prove highly vulnerable to change. The regions of Kochi, Nara, and rural Tottori are, in this sense, among the most vulnerable to the trends of automation. Japan’s largest and most economically important prefecture, Tokyo, is the country’s least-exposed region to robots displacing manufacturing jobs, according to our Index. Companies here have already established advanced levels of robot intensity, and the region’s diverse economy means workers are less dependent on the manufacturing sector for employment. A similar pattern is true of the regions surrounding other important cities such as Osaka, Yokohama, and Kawasaki. Region: Index Score: Region: Index Score: Most Tottori 0.54 Least Tokyo 0.09 vulnerable Kochi 0.51 vulnerable Hokkaido 0.20 regions Nara 0.49 regions Osaka 0.25 Shiga 0.49 Fukuoka 0.28 Saga 0.48 Miyagi 0.28 31
How Robots Change the World SOUTH KOREA Workers in South Korea’s largest city, Seoul, are the country’s least vulnerable to the growth of manufacturing robots. The regional economy is diverse, meaning it has a Low vulnerability low dependence on the Lower-medium vulnerability manufacturing sector for work, and the labour force is highly Upper-medium vulnerability productive. High vulnerability Some of Japan’s most mountainous prefectures feature among the most vulnerable to job losses. Although sparsely populated, these large regions are punctuated with traditional manufacturing enclaves, which may prove highly vulnerable to change. The regions of Kochi, Nara, and rural Tottori are, in this sense, among the most vulnerable to the trends of automation. Korea’s second city, Busan, and its neighbour, Ulsan, appear vulnerable to robots on our Index. Ulsan is home to major car plants, shipbuilding facilities, and oil refineries. It has very high levels of manufacturing productivity, but its relatively high robot vulnerability score is driven by a remarkable dependence on manufacturing employment. Region: Index Score: Region: Index Score: Most Daegu 0.38 Least Seoul 0.11 vulnerable Incheon 0.35 vulnerable Jeollanam-do 0.13 regions Ulsan 0.33 regions Gangwon 0.19 Gyeongnam 0.32 Chungcheongnam-do 0.21 Busan 0.29 Gyeongbuk 0.23 32
How Robots Change the World AUSTRALIA Australia’s most populous state, New South Wales, looks rather less vulnerable than either Victoria or South Australia. In this state, the labour market has become less dependent on manufacturing Low vulnerability jobs in recent years, while Lower-medium vulnerability manufacturing productivity has improved. So the impact of Upper-medium vulnerability further robot densification will High vulnerability likely be muted. South Australia is the most vulnerable Victoria is less vulnerable part of the country to future to robots than South robot rollout, according to our Australia, and also faster Index. The state is Australia’s growing. Melbourne and its most manufacturing intensive surrounding area have a diversified but has the slowest-growing manufacturing base, although one economy and low levels of that is declining in relative manufacturing importance as Melbourne’s service productivity. economy strengthens. Victoria’s manufacturing productivity is also higher than that of South Australia. Regions and Region: Index Score: territories South Australia 0.42 ranked from Victoria 0.39 most-to-least Tasmania 0.37 vulnerable Queensland 0.32 New South Wales 0.28 Western Australia 0.14 Northern Territory 0.06 Australian Capital Territory 0.06 33
A delivery robot being trialled in London, 2017.
How Robots Change the World THE ROBOTICS DIVIDEND 1% Despite the decline of To capture the potential manufacturing jobs over implications of the new era the past decade, it would of robotics on the global be simplistic to characterise economy, we used Oxford robotization as only a Economics’ Global Economic increase in the stock of destroyer of jobs. While Model (GEM). The GEM certain sets of workers lose covers 80 countries and is robots per worker in the their jobs to robots, many the foundation of all Oxford manufacturing sector in the wider population Economics’ country, industry, leads to a 0.1% boost to benefit from a “robotics and city forecasts. It enables dividend”—lower prices for us to test the sensitivity of output per worker across manufactured goods, higher macroeconomic outcomes to the wider workforce. real incomes, and stronger different rates of investment tax revenues. This will be across many advanced particularly important to economies around the world. the lower-income regions This modelling suggests that we have identified as being the rate of industrial robot 30% above baseline projections most vulnerable to the robot adoption over the coming for 2030. For China’s revolution. years will have a significant manufacturing sector, this impact on global GDP growth. would put its robot density on Our modelling shows that a par with the levels of robot robots have delivered The first step in our GEM density that currently exist in considerable productivity analysis was to establish a Japan and Germany. gains in recent years. We baseline projection for GDP analysed the impact of robot growth consistent with the By contrast, the low scenario densification on productivity short-term robot investment assumes the pace of robot growth in an international trajectories forecast by the adoption slows, leaving the sample of countries over 11 International Federation of stock of industrial robots some years, controlling for factors Robots (IFR) trade group. 17 30% lower than the baseline such as skill levels and other These trajectories for the by 2030. This would put capital investment, across US, Europe, and large Asian the robot density of China’s 29 of the world’s most economies were calibrated manufacturing sector at a advanced economies. We 16 against historical growth levels level comparable with the found that a 1% increase for both robot stock and current robot density of the in the stock of robots per robot density. Our baseline US manufacturing sector—a worker in the manufacturing projections for the growth in level significantly lower than sector alone leads to a robot stock amounted to an Japan and Germany. (For more 0.1% boost to output per annual increase of roughly 5% information on how we used the worker across the wider for China, 3% for the US, 2% GEM to simulate the impact of workforce. This confirms for both South Korea and the different robot adoption rates our hypothesis: that by Eurozone, and 0.7% for Japan. on the annual GDP performance displacing automatable jobs of key economies around the in manufacturing, robots Next, we explored “high” world, see box on page 37). free up many workers to and “low” scenarios for contribute productively robotization, relative to the elsewhere in the economy, IFR’s short-term benchmark. as they meet the demands The high scenario assumes generated by lower prices that the global stock of for manufactured goods. industrial robots will accelerate 16 The sample size for this model differs to our employment model due to data availability. 35 17 The IFR’s latest three-year growth projections for new robot installations appear in its publication World Robotics 2017: Industrial Robots.
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