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WHO IS READY FOR THE COMING WAVE OF AUTOMATION? THE AUTOMATION READINESS INDEX Supported by3 The Economist Intelligence Unit Limited 2018 THE AUTOMATION READINESS INDEX: WHO IS READY FOR THE COMING WAVE OF AUTOMATION? Contents About the report 4 Executive summary 5 Introduction: A need for policy 7 The automation readiness index: Overview 10 Chapter 1: Innovation for automation 12 Chapter 2: Skills for an automated economy 15 Chapter 3: Managing workplace transitions 18 Conclusion: Trial and error 21 Appendix: Framework and methdology 234 The Economist Intelligence Unit Limited 2018 THE AUTOMATION READINESS INDEX: WHO IS READY FOR THE COMING WAVE OF AUTOMATION? About the report M e r ce d e s C reg o , head, Open Innovation EU, Philips Lighting D i c k E l s y , chief executive officer, High Value Manufacturing Catapult J u l i e Hu x l e y - J o ne s , head of automation, GSK R o s e L u c k i n , professor of learner centred design, University College London A l a n M a n n i n g , professor of economics, London School of Economics F r a n c e s c Pe d r o, chief of section, Sector Policy Advice and ICT in Education, UNESCO G e o ff P e g m a n , managing director, R U Robots S a a di a Z a hi di , head of education, gender and employment initiatives, World Economic Forum Elena Alfaro Martinez, global head, Data and Open Innovation, BBVA J a m e s B e s s e n , professor of economics, Boston University D a y C h i a - p e n g , general manager, automation technology, Foxconn L or e n z o F i or a m on t i , professor of political economy, University of Pretoria E l i z a b e t h F or d ha m , senior advisor for global relations, Directorate for Education and Skills, OECD N e i l L a w r e n c e , director of machine learning, Amazon; professor of machine learning, University of Sheffield S h e r i e N g , managing director, NICE H a rr y P a t ri n o s , practice manager for education, East Asia and Pacific, The World Bank M i l a n S h e t h , partner and technology sector lead, EY S iim S ik k u t , chief information officer, Government of Estonia Marco Henrique Terra, director, Center for Robotics, Universidade de So Paulo We would like to thank the panel and other experts for their time and insights. The Automation Readiness Index: Who is ready for the coming wave of automation? is an Economist Intelligence Unit report, commissioned by ABB. The analysis in the report is based on a new and original index, built by The Economist Intelligence Unit, as well as a series of in-depth interviews with subject matter experts from around the world. The project has benefitted from counsel provided at various stages by a panel of experts consisting of prominent authorities on different facets of automation. These include the following: Interviews were also conducted with: 5 The Economist Intelligence Unit Limited 2018 THE AUTOMATION READINESS INDEX: WHO IS READY FOR THE COMING WAVE OF AUTOMATION? There are few terms as emotive, and few subjects that elicit as much angst, within societies as that of automation. This might seem odd, given that automation technologies have long been present in our factories and offices. The advent, however, of highly intelligent technologies such as robotics and those based on the different forms of artificial intelligence (AI), which have the ability to perform more than just assembly-line types of tasks, has added a new dimension to discussions of future automationnamely the prospect that large numbers of roles performed today by humans, wearing white or blue collars, will be eliminated by machines. Business leaders are not displaying much fear. Such anxieties as they have about these technologies are more about being caught out by market disruption. Thus many are speeding ahead to integrate AI or advanced robotics into their operations. That pace will accelerate in the next few years, and the actual impacts on economies and workforces will begin then to become clearer. To avoid a vacuum, countries will need to put policies and plans in place to help individuals (and to some extent businesses) take maximum advantage of the opportunities that these technologies offer. Policies will also be needed to mitigate the negative impacts resulting from the displacement of some categories of workers from their familiar roles. In both cases it is a matter of policies and strategies that help workforces make the transition to a more automated economy. The Automation Readiness Index compares countries on their preparedness for the age of intelligent automation. In assessing the existence of policy and strategy in the areas of innovation, education and the labour market, the study finds that little policy is in place today that specifically addresses the challenges of AI- and robotics-based automation. No country has yet to “take the bull by horns”, in the view of several experts interviewed for the study. A small handful, however, including South Korea, Germany and Singapore the overall index leadershave undertaken individual initiatives in areas such as curriculum reform, lifelong learning, occupational training and workplace flexibility. Other findings from the research include the following: The challenges and opportunities of intelligent automation require a robust policy response informed by multi-stakeholder engagement but, so far, both are lacking. Although there is little agreement on the likely net impact of AI and robotics on employment, there is a consensus that governments will need to take action. Businesses, meanwhile, are forging ahead with adoption, meaning there is little time for dalliance. The lack of engagement between policymakers, industry, educational specialists and other stakeholders that must inform this action is therefore alarming. Unsurprisingly, the policy response to intelligent automation is nascent in even the top-ranked countries. Middle-income countries will find adapting to automation tougher than others. With the exception of China, there is a large gap separating high-income countries from those in middle- and lower-income brackets. But lower-income countries with agriculture-based economies are less exposed than middle-income countries with large manufacturing bases. Shortcomings in basic skills education, among other weaknesses, will severely hamper countries in South and South-East Asia, for examplewhich are looking to use AI and robotics to emulate the East Asia “tigers”as they attempt to capitalise on the opportunities offered by automation. Index leaders earmark considerable funding and other support to AI and robotics research. Most types of support that governments provide for innovation and entrepreneurship are technology-agnostic. Fundamental research is different: the governments of Japan and South Korea, for example, channel hundreds of millions of dollars worth of funds to public- and private-sector organisations that are conducting AI and robotics research. Germany, the US and Singapore do the same, although much of German funding is channeled to the manufacturing sector and supports research in other technologies such as the Internet of things (IoT) and data analytics. Executive summary6 The Economist Intelligence Unit Limited 2018 THE AUTOMATION READINESS INDEX: WHO IS READY FOR THE COMING WAVE OF AUTOMATION? Few countries have begun to address the impact of automation through educational policy. Intelligent automation is expected to boost the importance of both education related to STEM (science, technology, engineering and mathematics) and of so-called soft skills, which allow workers to trade on their uniquely human capabilities. However, in all but the highest-scoring countries, little has been done to prepare future workers through school curricula or, just as importantly, teacher training. At the same time, some experts warn that a focus on soft skills would be a distraction in countries where basic education is still not up to scratch. Lifelong learning is becoming a rich area of experimentation. Several governments are looking for the right formula to encourage citizens to voluntarily undergo periodic skills upgrading. Singapore, for example, is experimenting with funding “individual learning accounts”, which adults use to support training courses throughout their lives. Germanys Federal Ministry of Labour and Social Affairs is examining a similar scheme, as well as a modified form of “employment insurance” to fund skills upgrading throughout peoples lives. In most countries, vocational training is not up to the challenges posed by intelligent automation. Germanys system of vocational and technical education has long been held up as a model for other countries. Its system, along with those of South Korea and Singapore, help these three countries share leadership of the labour market policy category of the index. Experts interviewed for the study, however, warn that vocational training in most countries remains too focused on low-skilled occupations to be of use in preparing young people for the automated workplace.7 The Economist Intelligence Unit Limited 2018 THE AUTOMATION READINESS INDEX: WHO IS READY FOR THE COMING WAVE OF AUTOMATION? Introduction: A need for policy T here are few areas of consensus among experts about how automation will affect economies and workforces. For example, some believe the gathering wave, based on the widescale diffusion of AI, machine learning and advanced robotics, will be no more disruptive than previous ones. This is the view of Alan Manning, a professor at the London School of Economics: “Every new wave of technology diffusion has impacts that are different, but I see no evidence that this is going to be radically different from what has come previously.” Others believe that whats coming will be different. “Traditionally technologies have automated a range of tasks that humans might not have wanted to do or might not have defined them as humans,” says Elizabeth Fordham, senior advisor for global relations in the OECDs Directorate for Education and Skills. “AI and robotics, however, are starting to automate higher order, non-routine tasks, some of which require critical thinking and creativity.” For Julie Huxley-Jones, who is head of automation at GSK, a life sciences firm, it is the accelerated pace of change that most distinguishes the emerging wave of automation. “The major difference with the past is that todays automation technologies are highly intelligent and able to learn.” Lorenzo Fioramonti, professor of political economy, University of Pretoria The net impact on employment is another area of divergence. Estimates of potential job losses due to automation range from an oft-cited figure of 47% for the US 1to more conservative estimates of around 9% for OECD countries. 2Mr Manning believes the net impact on jobs of AI, robotics and other automation technologies will be zero, as new jobs will be created that offset the elimination of older ones. 3James Bessen, a professor of economics at Boston University, believes that such automation may well create more jobs than it eliminates. “AI and robotics will likely lead to the creation of new demand for services that didnt exist before,” he argues. “In this case job creation will benefit, possibly exceeding the labour saving that these technologies enable.” There are two areas of broad consensus. One is that automation technologies will replace certain tasks performed by workers as much, or more, than they replace entire jobs. Automation thus points toward the augmentation of work, potentially leading to greater job satisfaction, as well as to outright displacement. Humans will continue to play a role in designing or operating these systems, and it is expected that many activities will continue to require the distinct skills of humans. Work performed by people will be continuously redefined, requiring the constant updating of skills. The other point of consensus is that seizing the opportunities and alleviating the strains that intelligent automation poses to economies require co-ordinated efforts by multiple stakeholders. Governments, businesses, educators, labour unions and civil society organisations all have roles to play in developing an understanding of what the impacts of automation are likely to be and to plan initiatives that will help their societies adapt. In many cases these will be policies developed and implemented by governments. “Governments need to have a strategy for automation,” says Mr Manning. “I dont think you can just leave this to the market and believe it will deliver the right level of innovation.” To the starting blocks Policies are required to help manage the transitions that businesses, schools and workforces will need to make in the areas of innovation, education and occupational skills development. To inform such policies, considerable dialogue should take place between governments and other stakeholders, most of whom, at least in developed countries, are studying the uses and implications of AI and robotics themselves. Unfortunately, there is not yet much evidence of either policymaking or multi-stakeholder dialogue on this topic. “The vast majority of countries inside or outside the OECD are only starting to think about planning for the challenges of automation,” says Ms Fordham. Ms Huxley-Jones rues a lack of dialogue between government and industry, as well as between different industries, on the challenges of automation. Other experts observe a similar dearth of dialogue between key stakeholders when it comes 8 The Economist Intelligence Unit Limited 2018 THE AUTOMATION READINESS INDEX: WHO IS READY FOR THE COMING WAVE OF AUTOMATION? to adapting educational systems. In this sense, no countries are genuinely ready for the age of intelligent automation. This is the case even for Germany, which has been a standard-bearer for the propagation of Industry 4.0 digital manufacturing strategies in which AI and robotics, along with the IoT, play a central role. The same may be said of East Asian countries, where governments are actively supporting the diffusion of these technologies in manufacturing and other sectors. At this early stage, then, comparing nations efforts to meet the challenges of automation is a case of examining the starting points for their policy responses. This is the purpose of the Automation Readiness Indexto determine which countries are better positioned to take up the policy challenges that automation poses. Its attention is focused on three areas: on innovation policies that directly or indirectly support research into and business adoption of AI, robotics and other adv
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