Terry McKinley Professor and Director Centre for Development Policy and Research, SOAS

1. The ‘Fourth Industrial Revolution’ and The Implications for Inequality • Terry McKinley • Professor and Director • Centre for Development Policy and Research, SOAS • Conference on • Work and Well-Being in the 21st Century • Johannesburg, 5-7 April 2019

2. Introductory Remarks • In this short presentation I want to quickly present some key points for consideration on the Current and Projected Impact on Inequality of the so-called ‘Fourth Industrial Revolution’. • The preferred focus is Emerging and Developing Economies, but most of the relevant research at this point has been on Developed Economies. • Separating the effect of the on-going Third Industrial Revolution from that of the Fourth Industrial Revolution also poses some problems. • The First Industrial Revolution: It took place in the 18th and 19th Centuries in Europe and North America. Many of the current Developed Economies ‘developed’ during this Revolution. This dramatic change represented the transition from predominantly rural, agrarian societies to urban, industrial societies. The iron and textile industries played a prominent role. And the ‘Steam Engine’ was a signature innovation. • The Second Industrial Revolution: This Revolution took place between 1870 and 1914 (before the First World War). While previously developed industries continued to flourish, new ones, such as steel, oil and electricity, rapidly expanded. Key was the use of Electric Power to support Mass Production. The major signature technological innovations were Telephones, Light Bulbs, Phonographs and the Internal Combustion Engine.

3. Introductory Remarks • The Third Industrial Revolution: We are already living through this Revolution. It started in the 1980s and continues to this day. Digital Technology has become widespread and dominant in many arenas. Signature innovations have been the Personal Computer, the Internet and Information and Communications Technology. • The Fourth Industrial Revolution: While building on the Third Industrial Revolution, the so-called ‘Fourth Industrial Revolution’ has been marked by substantial technological breakthroughs in a number of major fields. The most well-known and prevalent areas have been Robotics and Artificial Intelligence. But also increasingly prominent have been Quantum Computing, Biotechnology, ‘The Internet of Things’, 3D Printing and Autonomous Vehicles. • Most of the recent focus of research has been on Robotics and Artificial Intelligence. But the field of innovation continues to rapidly expand. • There is a continuing debate on the degree to which Emerging and Developing Economies are already being affected, and will be further affected, by the Fourth Industrial Revolution (4IR). For example, are such Economies more susceptibleor less susceptible to a negative shock from Automation than Developed Economies? • A Key Point: because of the rapidly spreading influence of Artificial Intelligence and Robotics, traditional ‘middle-income’, ‘blue-collar’ jobs, especially those that are routine, have been placed under noticeable pressure. • But this appears to be the case mainly in higher-wage Developed Economies. Hence, a Key Question: Will the Lower Wages in Emerging and Developing Economies tend to slow the pace of 4IR Technological Change and Retard the Rise of Inequality?

4. Some Thumbnail Definitions • Robotics: This field deals with the design, construction, operation and use of Robots. • Artificial Intelligence: Intelligence demonstrated by Machines. • Internet of Things: A Network of Devices, such as vehicles and home appliances, that are enabled to connect, interact and exchange data. • Biotechnology: A Broad area of Biology that involves living systems and organisms in order to develop or make products or processes for a specific use. • Nanotechnology: The manipulation of matter on an atomic, molecular and supra-molecular scale. • 3D Printing: Processes by which material is joined or solidified under computer control in order to create a Three-Dimensional Object.

5. The Effects on Economic Development and Inequality • Are current Emerging and Developing Economies going to have their Economic Development Short-Circuited by the Fourth Industrial Revolution? In other words, their prospects for expanding their Manufacturing Sectors, in particular, could be limited. (So, would the Service Sector represent an Alternative Source of Economic Growth (the IMF thinks so)? • Their main hope could be to expand the set of jobs that cannot fully or even partially be automated. For example, these could be low-paid Service-Sector jobs that require face-to-face interactions (such as hairdressers or housekeepers). These are likely to be safe from Automation—for a while at least. • How about even low-paid labour-intensive Manufacturing Jobs, such as those based on garment and shoe assembly lines (often located now in Lower-Income Developing Economies)? • Will their low wages (and negligible benefits) postpone the expensive initial investment in Robotics that could replace them? Technically, such standardised, repetitive jobs could be ‘Roboticised’ relatively easily. • Within the Income Distribution of Developing Economies, such Low-Skilled Manufacturing Jobs might well be situated, in fact, towards the Middle of the Income Distribution.

6. The Effects on Economic Development and Inequality • In contrast, Middle-Skilled Jobs in Developing Economies tend be more concentrated towards the top of the Income Distribution. And the jobs that might escape Automation for a longer period of time would likely be 1) low-paid unskilled workers, especially those doing non-routine jobs and 2) highly paid skilled workers also performing non-routine jobs but requiring some degree of creativity and/or technological know-how. (Note, however, that the latter set of workers is likely to be a small minority). • In Developed Economies, by contrast, Middle-Skilled jobs are more likely to be in the Middle of the Income Distribution. And there already appears to be an international research consensus that such Middle-Skilled Jobs in Developed Economies have been under the most immediate and intense pressure from Automation. • The Economic Outcome from such pressure would tend to produce a Polarisation in the Labour Market, namely, a growing Chasm between High-Skilled Workers and Low-Skilled Workers—leading, in effect, to a sharp rise in Wage Inequality. • Such anticipated Trends have led to a debate, for example, on the kind of Public Policies that should be introduced to deal with such growing inequalities. For instance, how will unemployed Middle-Skilled Workers in Developed Economies be retrained to access more Skill-Intensive Employment? Will Social Protection, such as Cash Transfers or a Universal Basic Income, have to be introduced? • There is an on-going lively debate on what should be the priority Policy Responses? But an additional problem (not yet emphasised) is to identify what policies would be most helpful for Emerging and Developing Economies.

7. The Effects on Economic Development and Inequality • There is a minor sub-current of research that suggests that the general movement of income away from Labour and towards Capital will lead to growing Wealth Inequality: the Rich will be able to invest in the new cutting-edge Technology; thus, because they will own the Robots, i.e., the Productive Capital, they will reap most of the rewards. Though this should be a vital concern, there has not been much research yet in this particular area. • Importantly, it is argued that the increased use of Robots in Developed Economiescould compete with, and eventually overcome, the labour-cost advantage of outsourced Manufacturing to Emerging and Developing Economies. So the Fourth Industrial Revolution is likely eventually to have a substantial impact on these latter economies, though this might happen with a delay. • However, when the 4th Industrial Revolution does end up impacting significantly on Emerging and Developing Economies, the results are likely to be substantial. • Note that one of the key arguments for this position is that the nature of Current Technological Change is different from that in earlier ‘Industrial Revolutions’: 1) the pace of technological change has noticeably quickened, 2) the scope of such change has also widened considerably and 3) the benefits are not being widely shared (such as across the working class). This latter trend should exacerbates inequality, which already appears to be rising in more technologically advanced Developed Economies.

8. The Effects on Economic Development and Inequality • It seems clear already that on-going technological change is not likely to respect the ‘colour of one’s collar’, i.e., whether you are a ‘blue-collar’ manual worker or a ‘white-collar’ office worker. The key parameter will be whether your job is routine and thus ‘codifiable’ (amenable to being programmed for a computer). • Exceptions might be jobs that require a lot of human interaction since they would be difficult to replace with ‘computerisation’. These jobs could include social work and nursing care, for example. Such jobs are often done by women. So there could be complex gender-based impacts as a result of Automation and Robotics. • Moreover, on-going Digitalisation (the Third Industrial Revolution) has already led to a significant increase in self-employment and online work. Some analysts argue that such flexible work arrangements could benefit women, youth, older workers and the disabled—since they could enjoy the flexibility of working from home as well as having flexible working hours. • But such workers are potentially quite vulnerable and will definitely need strong systems of Social Protection, especially against low pay and stunted career opportunities. And they will need new, more innovative systems of Skill Development and Training as the 4IR progresses.

9. The Pace of Technological Change Has Accelerated • It could well be the case that Emerging and Developing Economies will soon be affected by the 4IR because the Pace of Technological Change Has Definitely Accelerated since the Global Financial Crisis (2007-8). This has been due to three major factors: • Rapid Wage Gains (as well as Aging Populations) in some Large Manufacturing Emerging Economies, such as China, have stimulated greater investment in Automation. In fact, China has been investing heavily in Robotics in recent years. While in 2015 it had made less than 300 thousand Robots, by 2018 it had produced over 800 thousand units. • The prices of ‘hardware’ and enabling software have been declining markedly in recent years. • Recent significant technological advances in Robotics have accelerated their use: they are ‘smarter’, ‘safer’ and more adept across a larger spectrum of production processes. But will they also be cheaper—eventually? • Moreover, the ‘Internet-enabled’ Offshoring of Jobs to Emerging and Developing Economies has continued to be an important global trend. Key parts of this Offshoring have been in Banking and Financial Services (such as bookkeeping) and in Telecommunications (e.g., Call Centres). • These are Tradable Services and potentially higher paying occupations by Developing-Economy standards at least. Thus, this trend could certainly worsen within-country Income Inequality.

10. Differentiating Jobs from Tasks • The ILO defines a ‘job’ as “a set of tasks and duties, performed, or meant to be performed, by one person, including for an employer or in self-employment”. • But the Tasks within a Job could be complex.They could also be routine or non-routine, as well as manual or cognitive. Automation first replaces manual, routine jobs. But increasingly it has begun to replace more complex, non-routine jobs. This is indeed a worrying trend. • One of the working assumptions of analysts has been that human beings would become more concentrated in doing Complex Tasks. But as Technologies have become more sophisticated, even this assumption might not prove valid for the longer term. • The ILO is left to emphasise, for example, that human beings will have to concentrate on ‘Soft Skills’ that are acquired through experience—namely, good judgement, creativity and problem-solving. (Not an encouraging sign). • For example, Worker/Managers will be employed to frame the questions that computers are tasked to answer and address exceptional or ambiguous circumstances. • But what is a major matter of concern is how training and educational institutions will have to change significantly in order to adequately prepare people for new, complex and rapidly changing job tasks and skills. For example, how will such institutions deal with the likelihood that workers will have to change jobs more frequently over the course of their careers?

11. Policy Issues: How Should Educational Systems Be Reformed? • The nature and structure of current educational systems need to be urgently reviewed, evaluated and transformed. What kind of education will be necessary in an era of rapidly advancing Automation? There are no immediately easy answers. • A number of researchers have stressed that a ‘well-educated’ worker in an economy that is rapidly automating needs to possess an array of essential skills, such as problem solving, critical thinking, the ability to work in teams, sound interpersonal skills and creativity. Of course, well-developed IT skills will also be necessary. • But this is indeed a potentially demanding skills agenda! Is this realistic?? • In addition, because of expected rapid changes in employment conditions, workers will need the ability of life-long learning in order to continuously adapt and upgrade their skills. But what training institutions should be built to respond to these needs? • Educational systems have been slow to react to these growing challenges. The quality of teaching will have to improve markedly. There will also have to be extensive teacher training and retraining. • The economic returns to Tertiary Education do still remain high but even this kind of Education will have to change substantially and evolve. And children will have to be exposed to coding and basic ITC concepts relatively early—especially young girls. (Note that there is a very noticeable Gender Gap in such skills—another source of inequality)

12. Policy Issues: Should Skill Development and Training Be Prioritised? • Personal Note: in the extensive work I did for the Asian Development Bank in twice supervising the gathering and interpretation of data on Social Protection Programmes across Asian Economies, I was particularly struck by the finding that Active Labour Market Programmes in this region accounted for only 3% of all forms of social protection (compared to Social Insurance and Social Assistance). • Moreover, Skill Development and Training in particular, one of the major components of Active Labour Market Programmes, comprised a mere 1% of all forms of Social Protection. Passive Labour Market Programmes, such as unemployment benefits (which are part of Social Insurance) were indeed larger (though still limited in their coverage to workers in established, formal-sector enterprises). • The above trend on Skill Development and Training is particularly worrying in light of the job-displacing potential of the Fourth Industrial Revolution. Yet discussions on such initiatives have often taken a back seat to the widespread discussions of Social Transfers of various kinds, such as Cash Transfers and a Universal Basic Income. • But, instead of treating human beings primarily as rightful but essentially passive recipients of benefits, should the emphasis be centred more on helping them to actively expand and enhance their human capabilities? (Is this approach more consistent with Human Development?)

13. What Is a Universal Basic Income? • A Universal Basic Income essentially involves an Unconditional Cash Transfer to everyone in society—regardless of their income or employment. • Traditional Forms of Social Protection target people with particular problems or conditions, such as being poor, unemployed, elderly or disabled. Often such programmes take into account the recipients’ means of income—namely, these programmes are conditional upon people’s own means of support; they are not unconditional. • Often advocates of a Universal Basic Income assume that the amount of income should be sufficient to cover all essentials. So such a programme could not be cheap. • What are the arguments in favour of a Universal Basic Income? • Because Economic Security would be guaranteed, workers would be less likely to accept low-quality or exploitative working conditions. • Workers enjoying a Basic Income could also afford to take time to acquire more education and training (needed for the 4th Industrial Revolution). • There would be no danger of Stigmatization nor any need for ‘Means-Testing’ to determine qualification. • There would also be reduced Administrative Costs because any complex processes needed to justify particular people’s income support would be eliminated.

14. Criticisms of a Universal Basic Income • Provision of a Universal Basic Income implies that labour income might not serve as the primary source of income for a person. • Employers might be less motivated, as a result, to offer decent wages and working conditions. • There is also an Operational Question about whether UBI would completely replace other forms of Social Protection. Or would it, instead, merely complement other programmes? • Despite the recognised ease of administration, the overall costs of such a universal programme might be high—since it should cover the entire population. This would especially be the case if such a programme sought to ensure that people enjoy a decent standard of living. • For example, the ILO has estimated that if the Basic Income were set at a country’s Poverty Line, it could cost a large chunk of GDP for some countries. Would this be feasible for many Developing Economies, for example? • Also, the Basic Income would not be Redistributive. The Rich and the ‘Middle Class’ would benefit as much as the Poor. No discrimination.

15. Human Capabilities, Robots and Redistributive Taxation • There needs to be more debate on such Social Protection initiatives. It is noteworthy that the Fourth Industrial Revolution is substantially altering the terms and conditions for Social Protection. • Moreover, there would be the major problem of figuring out how to Finance Social Transfers under a scenario in which a significant number of workers would be continuously losing their jobs, and their sources of income. Would the Robots have to pay for workers’ unemployment benefits? (The Owners of Robots Would have to Pay?) • Theoretically, there are three major forms of Taxation: 1) on Labour 2) directly on Expenditures and 3) on Capital (e.g., Owners of Robots). • In 2017 Bill Gates put forward the novel proposal that the Use of Robots should be taxed, much as human workers are now taxed. And he argued for a relatively High Tax on Capital (the Robot). • In contrast, human workers should receive the income benefits of such taxation. In other words, they would face a ‘negative tax’ (i.e., they should be able to draw on the income generated by the Robot tax). • Moreover, Gates argued that the incomes received from taxing Robots could conceivably be used to subsidise work for which humans are particularly suited, such as caring for the young or the elderly.

16. Assessing Projections of the Impact of the 4th Industrial Revolution • In recent years, there have been various projections into the future about the likely impact of the 4th Industrial Revolution. • Initial ‘Dooms-Day’ Projections of Jobs Losses in the early literature on the Fourth Industrial Revolution are now generally regarded as being too pessimistic. • Such projections assumed that Entire Occupations would be automated. But critics have pointed out, usefully, that occupations are composed of many different ‘Tasks’. Some ‘Tasks’ are highly susceptible to Automation while others are not. Hence, Many Affected Occupations Are More Likely to Have to Change than Be Eliminated. • As a result, more recent projections are less dramatic. For example, the McKinsey Global Institute projected in late 2017 that 14% of the global workforce would need to change their occupation by 2030—but this ‘general-equilibrium’ scenario still assumed a relatively fast rate of technological change. • (Note the McKinsey publication Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation (December 2017). • McKinsey utilised three different projections for the Period 2016-2030: 1) a projection that assumes slow change, 2) a projection that assumes fast change and 3) a ‘mid-point’ projection calibrated to be between the fast and slow projections. I will focus on the Mid-Point Scenario, as does McKinsey in its publications.

17. Assessing Projections of the Impact of the 4th Industrial Revolution • In its December 2017 publication, the McKinsey Projections cover 46 economies that account for about 90% of Global GDP. • It estimates (perhaps over-estimates) that by 2030 as many as 375 million workers globally would likely need to transition to new occupations and learn new skills. • So McKinsey notes that the title of its Report should not really be ‘Jobs Lost, Jobs Gained’, but rather ‘Jobs Lost, Jobs Changed, Jobs Gained’. In other words, McKinsey believes that more occupations will change than be lost. • Nevertheless, it estimates that Half of the Work Activities that people are paid to do globally now could theoretically be automated based already on currently available technologies. • But only 5% of occupations consist entirely of activities that could be fully automated. • However, it estimates that in about 60% of occupations, 33% of their constituent activities could be automated. • Of course, the cost of developing and deploying new Automation Technology has to be taken into account as well as other key factors, such as the quality of available labour, the prevailing wages and skill levels.

18. Assessing Projections of the Impact of the 4th Industrial Revolution • McKinsey notes in its Mid-Point Projection that the impact of the Fourth Industrial Revolution on Developed Economies is likely to be more dramatic than the impact on Emerging and Developing Economies. • For example, when McKinsey gauges the projected impact of the Fourth Industrial Revolution on Current Work Activities across Developed Economies, it estimates that between about 20% and 27% of such activities could be displaced by Automation. • For example, Japan—which is estimated to be the most affected Developed Economy—is estimated to have about 26.5% of its Work Activities displaced by Automation. (Note: Japan does need Automation because of an Ageing Population). The United States would have about 23% of its Work Activities displaced. And the United Kingdom would be close to the lower bound for Developed Economies—namely, about 20%. • In Other Developed Economies, job displacement would represent, for example, 21% for France, 23.5% for Spain, 24% for Canada, 24.5% for Germany and 25% for Italy. • In contrast, for Emerging and Developing Economies, the estimates of the Percentages of Work Activities likely to be displaced are below 20%. • Tables 1a and 1b, which follow, provide McKinsey’s rough estimates of the percentages of Current Work Activities likely to be displaced across 18 Emerging and Developing Economies by 2030.

19. Table 1a. % of Current Work Activities Displaced by Automation (2016-2030 Projection) (McKinsey)

20. Table 1b. % of Current Work Activities Displaced by Automation (2016-2030 Projection) (McKinsey)

21. McKinsey Projections to 2030 on the Displacement of Work • The McKinsey Projections of the Percentage of Work Activities that could be displaced by 2030 in 18 Emerging and Developing Economies are significant but not as dramatic as earlier, more dire projections by other researchers and analysts. (Still Global Inequality would likely rise) • Not surprisingly, McKinsey takes a fairly Optimistic Stance on the overall impact of the 4th Industrial Revolution. It states that Job Gains Could More than Offset Job Losses and More Occupations Will Likely Change Than Be Lost. • Why? McKinsey assumes that the Economic Growth that is Stimulated by Automation Will Likely Create Demand for Additional Work and Workers. Productivity Growth will also Have a Positive Income Effect. • However, Income Polarization in Advanced Economies could intensify because of the Declining Importance of Middle-Wage Occupations (thereby increasing Wage and overall Income Inequality). Moreover, if the Re-Employment of Displaced Workers Is Slow, Frictional Unemployment Would Rise, making the impact of Inequality worse.

22. McKinsey Projections to 2030 on the Displacement of Work • In contrast, in China and other Major Emerging Economies, Middle-Wage Occupations are projected by McKinsey to have the Most Net Job Growth. But what effect will this have on overall Income Inequality? This is not yet clear. • In Ageing societies in particular, such as China, more rapid Automation could be considered an absolute necessity. In fact, next to the USA, China is probably the most ambitious economy in terms of aggressively adopting and advancing the technology of the Fourth Industrial Revolution. • The Chinese Government has been leading a “Made in China 2025” industrial master plan under which the number of its industrial Robots would expand tenfold from 2015 to reach 1.8 million units. By 2025 China seeks to manufacture 70% of the Robots that it uses—up from 30% at the end of 2018. Such objectives are requiring, of course, massive Government fiscal support. • But how will Income Inequality in China respond to such initiatives? Inequality has already risen rapidly in the wake of its Industrialisation drive. For example, the overall Gini Coefficient had already risen to 0.49 in 2012 (Beijing University). Is it feasible for it to rise even more in the wake of the Fourth Industrial Revolution?? Which stratum of workers will benefit and which will suffer?

23. Recent McKinsey Projections to 2030 on Absorbing Artificial Intelligence • A more recent McKinsey Publication (Notes from the Frontier: Modelling the Impact of AI on the World Economy, Sept 2018) compares the capacities of Emerging and Developing Economies in AI adoption and absorption. • This report identifies China and the United States as clearly the global leaders in the adoption of Artificial Intelligence. Hence the potential economic benefits in both economies are projected to be substantial. • Other Emerging and Developing Economies either have only a moderate ability to capture the economic benefits from Artificial Intelligence or a decidedly weak ability. • For example, Malaysia and India have a moderate ability. While India has an underdeveloped digital infrastructure and a low automation potential, it still produces 1.7 million graduates a year with STEM degrees (more than all such graduates from G-7 countries) and a substantial share of its exports are ICT-related. • But major Emerging Economies such as South Africa, Thailand, Turkey, Brazil and Indonesia are much less likely to capture significant economic benefits from Artificial Intelligence because of their lower absorption and related employment capacities. • And the prospects for Developing Economies such as Peru, Cambodia and Zambia are bleak: they currently have very limited abilities to adopt, assimilate and benefit from Artificial Intelligence. End