CHAPTER 2 - THE FUTURE OF JOBS AND SKILLS

CONTRIBUTED BY PROFESSOR KOSTAS MAVROMARAS, DIRECTOR, FUTURE OF EMPLOYMENT AND SKILLS RESEARCH CENTRE, UNIVERSITY OF ADELAIDE

Technology has been the driver of much of humankind’s material development in the recent and distant past and is continuing unabated, some would say accelerated, in this driving role today, through the Fourth Industrial Revolution. As new opportunities and potential benefits continue to emerge at pace, they are intensely debated, not only for their core wealth creating content and the almost boundless horizons they appear to be opening up for humanity, but also because of the uncertainty that surrounds them and the speed and depth at which they bring change. The amazement for its potential is accompanied by a fair measure of human reticence, so much so that the word “disruption” is used to portray the change that technology brings. Disruption is a word that comes with synonyms such as “disturbance, disordering, disarrangement, disarranging, interference, upset, upsetting, unsettling, confusion, confusing” and it is usually reserved for change that is more associated with difficulties rather than with benefits. In view of the stunning innovations we are experiencing, matched by an equally stunning frequency and continuity of appearance, any reticence felt about the technological change the Fourth Industrial Revolution brings would sound unjustified and possibly misplaced.

However, there is one aspect of the Fourth Industrial Revolution where future events may show that such reticence was justified, if not under-estimated, namely, the impact of technology on work, an activity that humans have historically identified themselves with. There is already sufficient evidence showing that automation and artificial intelligence are changing fundamentally the way we work within our economies and the way our economies perceive and value our work. The anticipated loss of jobs in numbers and the anticipated changes in the nature of work is already the subject of an extensive literature, the predictions of which are almost as diverse as their initial assumptions. Whilst it is not possible to foretell what the long-term impact of technology on work will be (at least not without using the right crystal ball), it is almost certain that in the short- and medium-run we are bound to see much change which will require policy interventions of a preventive and corrective nature.

This chapter is an examination of the future of work in the Asia- Pacific region. The general context we use is based on the emerging rich but in many of its aspects still inconclusive literature on the impact of technology on work and our Asia-Pacific region focus is made feasible by the latest 2018 PECC survey with its thematic focus on work and technology. It addresses several questions that are already asked by many people, governments and businesses, such as, (i) how is the Fourth Industrial Revolution changing the nature of work, (ii) what kinds of old jobs will disappear and what kind of and where will new jobs be created, (iii) how do economies of the region acquire the right skills for these new jobs, and (iv) what will happen to those who lose their jobs?

There is a strong view that, in order to enjoy the full benefits of new technologies, we will need capable institutions to develop appropriate new policies. These latter include first, education and training policies to build new skills, second, a labor market policy to enable the efficient utilization of these skills and third, a social care/ security policy to protect those who are left behind and to preserve the social cohesion and ethical foundations of our societies as change creates many new winners and losers. These general policy objectives will need to reflect and respect the economic diversity and inter-dependence of the region’s economies.

Technologies such as automation, artificial intelligence, cloud computing, 3D printing, blockchain and others, lead to better and cheaper ways to do things, but they also usually make some jobs obsolete. These technologies can be usefully differentiated by the balance between the productivity gains they achieve and the individual and social losses that worker displacement causes. It is not only the level of productivity gains and the extent of displacement that matter, but also how these are distributed, their timing and their longer term economic and social impacts.

Historically, new technologies have brought large net material gains and changed many lives and livelihoods. In the process, many workers lost their jobs, experienced lower lifetime income and in many instances completely changed the direction or even ended their working lives. Also, historically, technological change has in many instances created rather mixed outcomes with winners and losers, where losses often remained uncompensated. That is, losses suffered by displaced workers and specific communities that were not compensated by those other workers and communities that gained from the new technology. The overall impacts from past industrial revolutions (that is, both gains and losses) often took long to be realized and the benefits and losses were often unequally distributed.

The question we will ask here is whether we could expect history to repeat itself in the way today’s Fourth Industrial Revolution creates and distributes its benefits. It is often argued that the economic and social mechanisms of change are not new, so we can rely on historical evidence to guide us through change (the “we have been here before” argument).

It is counter-argued that several pertinent factors appear to be different this time, perhaps not necessarily in nature, but certainly in intensity. Such factors include the speed at which innovation happens, arguably historically unprecedented: fast change may be harder to adjust to. Also, there is the continued unbundling of production and the presence of global value chains, with the new possibilities for economic connectivity and interdependence they create: distribution would clearly be impacted. Moreover, with the co-existence of several new and powerful general-purposetechnologies, it is argued that this time around technological change and its impacts will be much deeper. So much deeper, that what we observe today is just the beginning of a very long road of deep technological change. Deeper change would require stronger economic adaptation and social assimilation and distribution efforts that would also be expected to create a larger redistribution of wealth gains.

It should come as no surprise, therefore, that there is much uncertainty about the economic, social and ethical implications of current technological change, often expressed in either overly optimistic or overly pessimistic forecasts, the differences between them based more on different assumptions than different evidence from the labor and technology markets.

HOW DO WE EXPECT THE NATURE OF WORK TO CHANGE?

Asking how technology will influence the nature of work must start with the appreciation that the nature of work has been evolving continuously throughout the industrial era. Technological change has been the main driver of the evolution of work today’s advanced economies. Work has become much more productive, increasingly more skilled, requiring higher levels of training and education, and is better paid. Work is also more widely shared within the population, especially with the rise in female participation, but an average lifetime today contains a smaller proportion of work and a larger proportion in education, leisure, retirement or other types of labour force stratus. Workers in advanced economies also have tended to work fewer hours per week than was the case some decades back, but in some cases this trend appears to be reversing. In the course of the evolution of work in the last century, many tasks became standardized and cheaper through new technologies, which made them easier to mechanize and, in many cases, fully automate.

A critical distinction for understanding the Asia-Pacific region is that its advanced economies face the Fourth Industrial Revolution from a different starting point than that of the emerging economies in the region. The differences will manifest themselves in the capabilities of relevant institutions and infrastructure, the domestic human capital endowment (e.g. education and training, health), the proportion of the population employed in the formal sector and other factors which will influence the capacity of an economy to absorb and utilize technology for development. Several of these differences could give rise to potential complementarities and therefore encourage cooperation within the region, making for different optimal workforce development pathways and differences in the evolution of work within the region.

From the 2018 PECC survey we find that the expectations in the region are that the size of workforces will decline due to the introduction of new technologies, the level of skills required will rise and that the occupational and skills structure of the workforces will change, all in ways related to the expectations in the particular part of the region the survey respondents are located.

Table 2.1 above offers a very broad picture on employment expectations showing that in Southeast Asia and Northeast Asia more respondents expect employment losses than gains, while in Oceania and the Americas the opinions are split, a bit less polarized in Oceania where survey respondents expect the least change.2 Figure 2.1 below looks at the expected size of the workforce through a more detailed lens, presenting the net difference in the proportion of expectation of gains and losses by sector following the question “By 2030, how do you think new technologies (for example but not limited to artificial intelligence, cloud-computing, 3D printing, blockchain, and advanced robotics) will impact the number of jobs in your economy overall and for the list of sectors below?”.

Respondents from both emerging and advanced economies appear to agree on the direction of change at the sectoral level. The strongest expectations that the number of jobs will increase were expressed in the following sectors: education; arts, entertainment and recreation; professional, scientific and technical activities, human health and social work activities; and information and communication.

The strongest sectors for a decline in jobs were: manufacturing; mining; and wholesale and retail trade. There was only one sector in which there was a difference in views on the direction of change – real estate. More respondents from emerging economies expect that there will be more jobs in this sector, while more from the advanced economies expect that there will be fewer jobs in that sector by 2030.

Anticipating the impact of technology on employment by sector will only describe part of the overall impact of the Fourth Industrial Revolution on work. There will be other aspects of employment that will matter, such as occupation or location. It is worth noting that as each sector utilizes several different occupations in different proportions, and that each occupation will be impacted by technology in an individual and specific way, the unique mix of occupations within each sector will play its own role in the overall impact of technology on the sector’s employment.

WHAT KINDS OF OLD JOBS WILL DISAPPEAR AND WHAT NEW JOBS WILL BE CREATED?

Figure 2.2 shows us the net difference in the expectations for an increase or decrease in the number of workers by occupation. The question asked is “how do you think new technologies will impact the number of jobs in the following occupational categories in your economy by 2030?”

In a similar way that a sector employs several occupations, and each of these occupations may be impacted by technology differently, an occupation uses several generic tasks and each task is subject to automation differently. The net percentage in Figure 2.2 above provides a very clear picture with science and engineering, information and communication technologies, health and care being the occupations that are expected to create the most jobs. Table 2.2 shows the geographic distribution of the strongest job creation by showing the occupations with the highest expectation that they will “increase greatly”.

The strongest job creation is anticipated to be in ICT professionals and ICT technicians, and the strongest overall job creation is expected in North America. Table 2.3 below shows the geographic distribution of the occupations with the strongest expectations for employment decline by 2030.

These are all occupations with a high proportion of repetitive tasks in them that make each one of them in their own way susceptible to automation. The process through which their product is created, and their services are provided will be transformed in a way that will retain human labor to provide the human element in tasks that cannot be automated, while the remainder will be provided through advanced new technologies, thus increasing labour productivity.

The speed of this transformation will be product- and servicespecific and will be greatly influenced by the institutions within which the transformation takes place. For example, one estimate suggests that the introduction of driverless cars in the United States could directly eliminate 1.3 to 2.3 million workers’ jobs over the next 30 years.5 Table 2.3 shows the average expectations for the whole region and their geographic differences within the region. Throughout the region, there is a shared expectation for strong displacement for (i) clerical support workers, (ii) plant and machine operators and assemblers (including train engine drivers, car and other transport drivers, trucks, mobile & fixed plant operators, ship deck crews), and (iii) laborers in mining, construction, manufacturing and transport.

For the remaining occupations listed in Table 2.3 the strongest expectations of displacement are found in Northeast Asia, Southeast Asia, and the Pacific South American economies and the weakest expectations of displacement are found in North America and Oceania. This list of occupations can be used to provide useful sociodemographic and economic profiling of the workers most likely to lose their jobs along with critical information on the skills, knowledge and experience that they will bring with them to support a drive to re-train and up-skill them in preparation for the new jobs that emerge.

DO WE HAVE THE RIGHT SKILLS IN THE REGION FOR THESE NEW JOBS?

Worker displacement will create surpluses of workers and skills in some occupations while there will be shortages of workers and skills in growth occupations. How well the economy adjusts to technological change will depend on its capacity to match the skills on offer by all available workers (employed or looking for work) with the skills required by all jobs (vacant or filled). Given the anticipated magnitude of the change we are expecting, one should expect extensive skills mismatch (that is, simultaneously extensive skill shortages in some areas and extensive skill surpluses in other areas), increased labor market turnover, including jobto- job transitions, and that all types and forms of education and training, labor market reform, and social care/security reform, will play a critical role in helping economic and social life recalibrate and re-balance itself. Figure 2.3 shows the extent of anticipated skills mismatch due to technological change.

The question that was asked for Figure 2.3 was “Which occupations do you anticipate will develop shortages or surpluses of workers in your economy due to new technologies by 2030 (tick one box in each category)”. The bars to the left (right) show expectations for a shortage (surplus) in the occupation and the percentage needed to reach 100% when the two are added represents the expectation that the skills will be well-matched. Thus, for example, for occupation elderly care workers, 56.3 percent of respondents expect shortages, 14.3 percent expect surpluses, and (100 – 56.3 – 14.3 =) 29.4 percent expect that skills will be well-matched in this occupation. (Note that the shorter the overall bar is in the figure, the more respondents expected well-matched skills in the future.) Overall, respondents tended to think that by 2030 there would be a surplus of workers in the lower skilled job categories and a shortage in higher skills.

Below we show the geographic distribution of two selections of occupations, first, those expected to be in intense skills shortage (Table 2.4) and second, those expected to be in intense surplus (Table 2.5), both by 2030.

Intense shortages above the region’s average are found predominantly in Southeast Asia and below the region’s average in Northeast Asian and Oceania.

A similarly diverse picture emerges for the geography of those occupations expected to be in intense surplus by 2030, with Southeast Asian respondents expecting intense surpluses, but also North America and Northeast Asia showing above average percentages for several of the shrinking occupations. 

It is important to note the difference in the geographic patterns of occupations expected to strongly increase or decrease in size presented in Tables 2.2 and 2.3, and the patterns of occupations that are expected to be in intense shortage or surplus in Table 2.4 and 2.5.

THE IMPACT OF TECHNOLOGICAL CHANGE BY OCCUPATION

Figure 2.4 below puts together the information on occupation size and shortages/surpluses for all occupations. We use the net growth information in Figure 2.2 and we derive a similar net shortage or surplus percentage from Figure 2.3 (where a negative indicates a net shortage and a positive a net surplus) and combine them in Figure 2.4. The figure clearly shows a positive association between growth and job creation. Starting from the top left with clerical and support workers (with a job shrinking expectation at 52% and a skills surplus at 42%), going through the center of the figure with ship and aircraft controllers and technicians (+2%, -2%: expected to be one of the most stable occupations) all the way to the bottom right where high growth and high skill shortages occupations are bunched up, such as science and engineering professionals and their associates, ICT professionals and their technicians.

Figure 2.4 suggests several ways in which the occupations could be bunched up in separate categories. Broadly speaking, we could have occupations split into the four quadrants in Figure 2.4:

More Jobs and Surplus of Workers (North-East quadrant)

• Hospitality, Retail and Other Services Managers
• Business, Administration, Legal, Social, Cultural and Related Associate Professionals
• Business, Administration, Legal, Social and Cultural Professionals

More Jobs and Shortage of Workers (South-East quadrant)

• Chief Executives, Senior Officials and Legislators, Administrative and Commercial Managers
• Production and Specialized Services Managers
• Science and Engineering Professionals
• Health Professionals (doctors, nurses, dentists)
• Teaching Professionals
• Information and Communications Technology Professionals
• Science and Engineering Associate Professionals
• Health Associate Professionals (e.g., medical and pharmaceutical technicians)
• Information and Communications Technicians
• Ship and Aircraft Controllers and Technicians (e.g., ships’ engineers, deck officers and pilots, traffic controllers, air traffic safety electronics technicians)
• Childcare Workers (e.g., childcare, teachers’ aides)
• Elderly care workers
• Protective Services Workers (police, fireman, security guards)

Fewer Jobs and Shortage of Workers (South-West quadrant)

• Skilled Agricultural, Forestry and Fishery Workers

Few Jobs and Surplus of Workers (North-West quadrant)

• Clerical Support Workers
• Personal services and sales workers (shopping sales assistant, waiters)
• Building and Related Trades, Metal, Machinery and Related Trade, Electrical and Electronic Trades Workers
• Handicraft and Printing Workers
• Food Processing, Woodworking, Garment and Other Craft and Related Trades Workers (butchers, tailors)
• Plant and Machine Operators and Assemblers (including train engine drivers, car and other transport drivers, trucks, mobile and fixed plant operators, ship deck crews)
• Cleaners and Helpers
• Laborers in Mining, Construction, Manufacturing and Transport
• Food Preparation Assistants & Agricultural, Forestry and Fishery Laborers
• Street and Related Sales and Services Workers

Of the four quadrants it is the South-East and the North-West that make the most intuitive sense. The former (SE) contains the growing occupations where shortages in the skills required by the occupation are strongly expected, and the latter (NW) contains the shrinking occupations where surpluses of the skills required are also strongly expected.

Another way to cut this data would be by splitting it into the high decline occupations (at the top of the NW quadrant), the stable occupations (in the middle of the diagram belonging to all quadrants), and the high growth occupations (at the bottom of the SE quadrant). This way would probably find a clearer relationship with the underlying concepts of automation and worker displacement.

Declining

• Clerical Support Workers
• Personal services and sales workers (shopping sales assistant, waiters)
• Handicraft and Printing Workers
• Food Processing, Woodworking, Garment and Other Craft and Related Trades Workers (butchers, tailors)
• Plant and Machine Operators and Assemblers (including train engine drivers, car and other transport drivers, trucks, mobile and fixed plant operators, ship deck crews)
• Cleaners and Helpers
• Laborers in Mining, Construction, Manufacturing and Transport
• Food Preparation Assistants & Agricultural, Forestry and Fishery Laborers
• Street and Related Sales and Services Workers

Stable

• Ship and Aircraft Controllers and Technicians (e.g., ships’ engineers, deck officers and pilots, traffic controllers, air traffic safety electronics technicians)
• Childcare Workers (e.g., childcare, teachers’ aides)
• Teaching Professionals
• Chief Executives, Senior Officials and Legislators, Administrative and Commercial Managers
• Production and Specialized Services Managers
• Building and Related Trades, Metal, Machinery and Related Trade, Electrical and Electronic Trades Workers
• Hospitality, Retail and Other Services Managers
• Business, Administration, Legal, Social, Cultural and Related Associate Professionals
• Business, Administration, Legal, Social and Cultural Professionals

Growing

• Science and Engineering Professionals
• Health Professionals (doctors, nurses, dentists)
• Information and Communications Technology Professionals
• Science and Engineering Associate Professionals
• Health Associate Professionals (e.g., medical and pharmaceutical technicians)
• Information and Communications Technicians
• Elderly care workers
• Protective Services Workers (police, fireman, security guards)

It is worth noting how close these categories are to those introduced earlier in Tables 2.4 and 2.5.

THE IMPACT OF TECHNOLOGICAL CHANGE BY OCCUPATION: DO EMERGING AND ADVANCED ECONOMIES EXPECT TO TRANSFORM DIFFERENTLY?

There are many reasons why emerging and advanced economies may respond differently in the way technology may impact jobs numbers and how skills are matched as their labor markets transform. As already mentioned, the starting point for this transformation will differ in its economic and institutional fundamentals between emerging and advanced economies, in ways that may influence how the region gets together to create cooperative and/or competitive solutions in its efforts to adapt to new technologies. This is a discussion that needs to be developed in the region as the transformation begins, namely, to what degree will the Fourth Industrial Revolution bring the different economies in the region closer to cooperation and/or competition and how could APEC best serve the joint interests of the region. This discussion has gained added urgency in the last two years and has been clearly stated in the 2018 PECC survey where the top risk for growth in the region in the next 2-3 years has been “increased protectionism and trade wars” (see Chapter 1 for more details).

To shed some preliminary light on possible employment-related differences between advanced and emerging economies in the region, we examine the expected impact of technological transformation on the number of jobs and the matching of skills and how these may differ between emerging and advanced economies. To this purpose we re-calculate Figure 2.4 separately for the emerging and for the advanced economies and compare the results in Figure 2.5 below.

Expectations about growing occupations differ between advanced and emerging economies. For most of the growing occupations, advanced economies have lower expectations for growth in jobs and, also lower expectations for shortages in the necessary skills. For example, jobs growth expectations for science and engineering professionals (and their associates in brackets) are 67% (63%) for emerging and 60% (51%) for advanced economies. At the same time expectations for skill shortages are -43% (-41%) for emerging and -39% (-32%) for advanced economies. This same difference is similarly prominent among slower growing occupations such as teaching professionals with emerging/advanced jobs growth at 38%/15% and skills shortages at -17%/-3% and production and specialized services managers at 34%/21% and -21%/- 5% respectively. Moving to occupations with more modest expectations of growth a similar picture emerges, namely that growth expectations are higher among emerging economies, and so are expectations of shortages.

The comparison shows an ambition on the part of emerging economies in the Asia-Pacific region to catch up with their advanced partners, but also an appreciation that this will bring even more intense skills shortages for these occupations, with all the demands that these will bring to education, training, and related labor market infrastructure and institutions. It may also reflect the current paucity of such skills in emerging economies as well as the out-migration of professionals who have those skills. The degree to which the necessary infrastructure for this transformation is in place will be looked at in the next section.

Before we move to the examination of declining jobs occupations, we must note an exception found in the data. The only high growth occupation where advanced economies have similarly strong expectations for jobs growth as emerging economies (both at around 54%) but stronger expectations for skills shortages (-34% for emerging and -50% for advanced economies) is elderly care, which could be explained by demographic and social differences in that ageing is more advanced in advanced economies and the delivery of aged care is socially and financially different.

Expectations about declining occupations are far more variable than those forgrowing ones. This is probably because the reason, the timing and the intensity of declining can be very occupation and possibly sector specific. There are the severely declining occupations such as clerical support workers and laborers in mining, construction, manufacturing and transport where emerging economies expect to shed jobs much more slowly and to suffer much less from skills surpluses than the advanced economies. For clerical support workers, the net expectation for jobs decline is 43% for respondents from emerging economies and 63% for those from advanced, with the respective skills surpluses being at 35% and 50%. Clearly respondents from advanced economies are expecting a much stronger negative employment impact than the emerging ones, presumably because they also expect that they will be transforming deeper than the emerging economies.

However, this pattern does not extend to many more of the declining occupations. For example, personal services, food preparation, and street sales all show expectations that are very similar between emerging and advanced economies for both jobs and skills mismatch. The lack of clear patterns continues with cleaners and helpers, building and related trades, and business administration all showing a very diverse picture that does not lend itself to a straightforward generalizable explanation.

Our best guess here is that without the use of multivariate regression this part of the data will remain difficult to interpret usefully. The comparison of the declining occupations between advanced and emerging economies suggests that decline will not be an orderly process and that it will be very occupation specific. The implication is that it will be hard to obtain the information needed to assess the negative social aspects of the decline and to interpret it usefully to construct social policy to help will manage this transition.

Having established some aspects of how the Fourth Industrial Revolution may impact on the number and type of jobs and occupations that will be lost and fewer aspects of the new jobs that will be created, we presented the survey respondents with a list of 12 skills that have been cited in World Economic Forum’s Future of Jobs Reports 7 and asked them if they think that such skills will be easy or difficult to find and hire in the region by 2030. This is clearly a highly speculative question and its answer should be considered accordingly. 

Figure 2.6 stresses the challenges the region faces in adapting to the Fourth Industrial Revolution with respondents highlighting the educational and hiring difficulties they anticipate within their economies. Critical thinking and problem solving, closely followed by cognitive flexibility and judgement and decision making at the shortages end of the spectrum, and the increasing mechanization expected in areas that have to do with customer service, quality control and coordinating and managing people at the surpluses (or perhaps lower shortages) end of the spectrum. Many of these skills are not taught explicitly as part of a skills-set but are facilitated to develop from the earliest education stages, starting according to educational and economic research from the early childhood pre-school stage of education, the value of which often remains underestimated by policy.

WHAT WILL HAPPEN TO THOSE WHO ARE LEFT BEHIND?

This is a very hard question to answer for two main reasons. First, because the extent of automation that will become technically feasible as the Fourth Industrial Revolution comes to its full strength is very hard to predict. Innovation is not happening in a linear fashion in time or in depth, scale, or scope. Second, even if we were able to make some reasonable predictions about the technical possibilities and their subsequent impact on automation, worker displacement, and new jobs creation, we would still need to account for human responses in the form of individual, social and political choices regarding the desirable speed and depth of the change. We would also need to account for the capacity of institutions and infrastructure that are required to support these choices. To top this uncertainty, as many of these parameters differ by economy, trade possibilities would always be a factor to consider about how groups of economies may respond to the making of individual and joint choices. For these reasons we will not venture to make any solid predictions. We will instead put the evidence we presented above in a broader context, using scenarios that have been offered in the literature and highlighting the question of how prepared the region is for the Fourth Industrial Revolution.

The evidence we have presented on jobs and employment outcomes suggests that there will be a lot of displacement in the form of occupations that are automated and many workers who will lose their jobs. At the same time, whatever forecast we can muster in this period of intense uncertainty suggests that the Fourth Industrial Revolution will also bring intense new job creation. There is too much uncertainty surrounding these two processes for us to offer an estimate of the net number of jobs lost minus jobs created in the transformed economies. It is critical to build into our thinking that there will be no guarantee that those who lose their jobs due to automation will also be the same people who will be employed in the newly created jobs. Several scenarios have been put forward, one of the most prominent ones being by McKinsey (2017) who state that the quantitative economy specific charts presented in their analysis “should not be taken as forecasts or predictions” and that they “Rather, they illustrate a range of possible outcomes”.8 In these scenarios they explain convincingly that the range of expected displacement is very broad, depending on how rapid adoption is and what the economy-specific reactions are. They also suggest that the likely outcomes will differ very much between emerging and advanced economies. These are points we have argued in our analysis, especially that economy-specific starting points will be very influential about the way the fourth industrial revolution will impact the different parts of our region.

McKinsey (2017) suggest that measured as a proportion of current work activity hours, automation will have displaced by 2030 in China between 15 and 31 percent of the total work hours, in the US between 23 and 44 percent, with Japan topping the range with displacement between 27 and 50 percent by 2030. In contrast, Mexico’s range is 13 to 26 percent and India’s 10 to 19 percent. To put this in some human perspective, these scenarios are talking about worker displacement of approximately between a quarter and half a billion people by 2030. Given the enormity of such numbers, the last question we will address in this chapter is whether the regional policy community believes that existing education, labor and education institutions and infrastructure are prepared for the Fourth Industrial Revolution and what aspects are those of more, or less concern in each sub-region.

How well developed are the relevant areas of policy in the region? How well-prepared are the institutions and how aware and ready to act are the core stakeholders when the impacts of the Fourth Industrial Revolution require economic, political and social solutions? As the current political turmoil experienced in several regions of the world indicates, core institutions are challenged and some of the benefits deriving from past progress are endangered, including the benefits from freer trade, international cooperation, and globalization. Well-prepared institutions are critical in this context.

The strong expectations that many jobs will be lost, and that new jobs will be created, alongside with the anticipated high levels of mismatch due to new technologies underscore the widely held view that education, labor and social policy will need to play a critical and active role in managing the impending technological transformation safeguarding economic development whilst also protecting the weakest and most vulnerable. Our overall assessment of the region’s preparedness to deal with the training, upskilling and possible disruption coming from new technologies is sobering and should constitute a call for action in policy circles. Social policy, education systems and labor markets are all deemed by stakeholders as starkly unprepared for dealing with the disruptions that are likely to come. Responses between advanced and emerging economies differed only minimally.

The survey asked further detail on specific aspects of education, labor and social policy in the respective economies, shown in Tables 2.6 and 2.7 below. As Figures 2.7 and 2.8 above have already forewarned us, there were very low levels of satisfaction across the region on the match between educational training and the needs of the economy as well as on the levels of cooperation between education providers and employers. These are issues that are hotly debated (see Box 3: Perspective on the Role of the Education System by Gary Hawke).

When asked how satisfied they are with specific labor and education issues in their economy (on a scale of: Not at all, Slightly; Moderately, Very; Extremely) stakeholders responded with very low levels of satisfaction: the majority of their answers were in the two lowest satisfaction categories and only rarely did the two highest satisfaction categories put together reach the 10 percent mark. Tables 2.6 and 2.7 present this rather alarming evidence in some detail.

Table 2.6 focuses on low satisfaction responses as indicators of areas of concern and shows the proportion of responses where the answer was either Not at all satisfied or Slightly satisfied, for the three categories of stakeholders, Business, Government and Nongovernment. The proportion of stakeholders who express concern is alarmingly high. The lowest concern level is about university education (with “only” 44 percent respondents expressing concern) and the highest is about the low match between educational training and the needs in the economy (with 73 percent of respondents expressing concern). The concern about “skills for growth” come through in several ways.

Concerns regarding skills and the labor market are expressed by high dissatisfaction about the ability to secure skilled staff (at 63 percent) and about the cooperation between education providers and employers (at 67 percent). These concerns are corroborated by the high level of concern about Maths, science and digital education as part of school education (at 64 percent compared with 58 percent for secondary and 61 percent for primary schooling) and STEM in the universities (at 59 percent, compared with 44 percent for business management education and 44 percent for other university education). As if these concerns were not enough by themselves, it is troubling to see that they are much more strongly expressed by businesses (in 8 out of 12 areas their concern was above average) with government respondents expressing an area as above average concern only once (about wage and working hours flexibility). Non-government stakeholders score a 5 out of 12. These differences suggest that information is not flowing optimally and that channels of communication and information as well as research in these areas should be considerably strengthened. The “common sense” question is, if satisfaction is low at this (early) stage of the Fourth Industrial Revolution’s rollout, how can we expect that our policy responses will be adequate when the change intensifies and becomes faster?

Table 2.7 below examines the geographic dimension of the dissatisfaction about labor and education issues. For reasons that need further investigation, respondents from Pacific South America express concern with all issues they are asked. With the exception of university education (other than STEM) where they are dissatisfied the least, in all other areas their expression of concern is very wide. Especially striking is their concern about Math, science and digital education at school (at 85 percent), STEM at university level (at 73 percent) and problematic match between educational training and the needs of the economy (at 80 percent). The next geographic area to show wide levels of concern is North America with 8 out of 12 areas above average, followed by Southeast Asia scoring 5 out of 12 and Northeast Asia and Oceania scoring 3 each out of 12. Notably Northeast Asia expresses the widest dissatisfaction about wage and working hours flexibility and early and primary school education, while Oceania reports low satisfaction about the cooperation between education providers and employers and the lowest dissatisfaction with labor market flexibility, in both hiring/ dismissal and wages/working hours flexibility.

The overall picture we see from Figures 2.7 and 2.8 and Tables 2.6 and 2.7 is a widespread perception of unpreparedness and low levels of satisfaction with the way education and labor markets are handled. The high levels of dissatisfaction in North America may be the result of the Fourth Industrial Revolution having already made different progress in that part of the region (e.g. with much shifting from manufacturing to services, or with capital and technology outflows due to industrial unbundling) than in Southeast and Northeast Asia where both manufacturing and services have progressed more strongly, but from a lower starting point. It is also important to note that, with the exception of Northeast Asia, which is clearly dominating the statistics of its geographic area, math and science education are of major concern everywhere else in the Asia Pacific region.

CONCLUSION

This chapter has examined the future of work in the Asia-Pacific region in the face of the Fourth Industrial Revolution. This is a vast topic and we have just begun to scratch the surface of only few of its most important aspects. The introductory section builds the context and sets the scene. The examination of “Artificial Intelligence for Everyone” in Box 1 deals with the new aspects of the change that the Fourth Industrial Revolution is bringing in terms of ambition and benefits and in terms of potential economic, social and institutional risks that will have to be managed. It highlights the role of diversity within the Asia-Pacific region and explains the need of social and economic preparedness.

As demonstrated by the results of PECC’s survey of the regional policy community, there is a clear expectation that automation will lead to sizeable workforce decreases in some sectors but that there are also likely to be increases in other sectors that will be the incubators of new technologies and growth, the view being that there will be modest overall decreases in the size of the workforces by 2030 and that these would be unevenly spread within the region.

We then focused on occupations as the most relevant categorization of work, in order to identify and possibly measure the worker displacement and jobs creation impact of the Fourth Industrial Revolution. Science and engineering, ICT, health and care related are expected to be the big winners at both higher education and vocational education levels. Job creation is expected at its strongest in North America and in SE Asia. There are strong differences by sub-region in the expectations for job displacement by occupation, we presume due to the different stage of the economies concerned.

The finding that skill shortages and skill surpluses are expected to coexist is a critical aspect of the expectations regarding the impact of the Fourth Industrial Revolution on workforces. There is no reason why we should be assuming that displaced workers would be readily employable to any of the newly created technologically advanced jobs. Mismatch will play a large role in the labor markets of the future and we already see substantial differences by geography and by occupation.

Box 2: The APEC App Challenge: Skills for a New Generation offered at this stage an example of the many practical aspects of building skills and training in the context of an emerging economy and the social and economic transformation that is facilitated by the Fourth Industrial Revolution.

The analysis of mismatch continued with a focus on the differences in mismatch between emerging and advanced economies and how the patterns of skill shortages were qualitatively rather similar (presumably because, at least in part, they are motivated by the same type technologies) but the patterns of skill surpluses were not (presumably because of the very different social and economic institutions that are designed to support displacement and retraining). We found that the more mechanical skills were predicted to be the least likely to be in shortage in the future, whilst critical thinking, complex problem solving, judgement & decision making, cognitive flexibility and creativity were predicted to be in future shortage.

Having established the degree to which we expect to see displacement and job creation and, also some of its occupational and geographic aspects we turned to the question of how prepared the region is in terms of its education, labor and social institutions and infrastructure. Even the most conservative estimates paint a very alarming picture about the extent of a global problem displacement with all its labor market mismatch, education upskilling and re-training and social care for those who are left behind without much hope of joining in. The responses from the PECC Survey on the state of the Region 2018 were sobering and the concerns they identified will require more attention and research. A very small percentage of stakeholders reported that they believe their economies to be ready and the more detailed questions revealed diverse and intense concerns about many highly important aspects of education, labor markets and social support.

APEC has already begun to lay the groundwork for addressing these issues. In 2017 at their meeting in Danang, regional leaders endorsed the APEC Framework on Human Resources Development in the Digital Age. The Framework sets policy directions and measures to support economies to prepare workers for present and future challenges. It calls for APEC to be to be used as a platform for policy dialogue and cooperation on these issues. It seeks to complement existing initiatives, including the APEC Education Strategy and contribute to global efforts including the ILO’s “future of work centenary initiative” and the United Nations’ Sustainable Development Goals, particularly Goal 4 to ensure inclusive and equitable quality education for all and promote lifelong learning and Goal 8 to create new dynamism for growth, achieve sustainable, innovative, and inclusive growth, employment and decent work for all.

This chapter is not ending in an unequivocally optimistic note. We anticipate unprecedented change, perhaps not so much in the net numbers of jobs growth, but in the very large numbers of workers that will need to find their way out of displacement and into a different labor market, which requires very different skills and where many things are done very differently. As identified in the interview with UPS’ Chief Transformation Officer, Scott Price, businesses are undertaking efforts to prepare workers for the change but these need to be scaled up. This will not be an era for people who are afraid of or dislike change. It will be an era that will unleash massive opportunities for those who embrace change. It will also be an era which will challenge our social and ethical foundations, as we try to establish new ways to ameliorate the outcomes from skills and occupational mismatch throughout the globe. Above all, this chapter is sending the message that, ready or not, the Fourth Industrial Revolution is coming to the Asia-Pacific region and the region is declaring itself woefully unprepared. The urgent need for educational and labor market reforms is clearly stated, as is the need for closer collaboration between business, government and academia. Closer cooperation by stakeholders will be required and APEC is already laying the foundations for this. A new Fourth Industrial Revolution Taskforce should be formed by APEC to produce research, advice and guidance for all stakeholders.

REFERENCES

David H. Autor, Frank Levy and Richard J. Murnane, 2003, The Skill Content of Recent Technological Change: An Empirical Exploration Source, The Quarterly Journal of Economics, Vol. 118, No. 4 (Nov. 2003), pp. 1279-1333

David Autor, David Dorn, Lawrence F. Katz, Christina Patterson, and John Van Reenen, 2017, Concentrating on the Fall of the Labor Share, American Economic Review: Papers & Proceedings 2017, 107(5): 180–185

David H. Autor and David Dorn The Growth of Low-Skill Service Jobs and the Polarization of the US Labor Market, The American Economic Review, Vol. 103, No. 5 (August 2013), pp. 1553-1597

David H. Autor, David Dorn and Gordon H. Hanson, 2013, The Geography of Trade and Technology Shocks in the United States, The American Economic Review, Vol. 103, No. 3, Papers and Proceedings of the One Hundred Twenty-Fifth Annual Meeting of the American Economic Association (May 2013), pp. 220-225 Published by: American Economic Association Stable URL: http://www.jstor.org/ stable/23469733 Accessed: 24-04-2018 07:17 UTC

Spyros Makridakis, 2017 The forthcoming Artificial Intelligence (AI) Revolution: It’s impact on Society and Firms; Futures 90 (2017), 46–60

Bakhshi, H., Downing, J., Osborne, M. and Schneider, P., The Future of Skills: Employment in 2030. London: Pearson and Nesta, 2017.

The Future of Jobs Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution, World Economic Forum; January 2016

Building Australia’s future-ready workforce, Microsoft, 2018

Delivering the Workforce for the Future, Mercer, Oliver Wyman, 2017

Jobs Lost, Jobs Gained: Workforce Transitions in a Time of Automation, McKinsey Global Institute, 2017

Erica Groshen, Susan Helper, John Paul MacDuffie, and Charles Carson “Preparing U.S. Workers and Employers for an Autonomous Vehicle Future”https:// avworkforce.secureenergy.org/wp-content/uploads/2018/06/Groshen-et-al- Report-June-2018-1.pdf, 2018

Bakhshi, H., Downing, J., Osborne, M. and Schneider, P., The Future of Skills: Employment in 2030. London: Pearson and Nesta, 2017.