What the Literature says about the Future of Work
This literature review provides an overview of the changes about to revolutionise workplaces, the skills that are growing in demand (and those that are not) and how work is likely to change in the future.
Change drivers for the world of work
The three key forces that will shape the future of work are: automation: ever-smarter machines performing ever-more human tasks; globalisation: our workforce going global and the global workforce coming to us; and collaboration: many jobs, with many employers, often at the same time.
How we work is being impacted by mega-trends including “globalisation, technological progress and demographic change” (OECD, 2017, p.2). The key sites for technological progress are in “Big Data, artificial intelligence (AI), the Internet of Things and ever-increasing computing power” (p.4). For the International Monetary Fund (2018), the major factors driving labour market trends are “automation and cheaper capital goods” and “global integration” (p.12) making a global marketplace. Research by Pearson and Nesta (Bakhski et al., 2017) adds environmental sustainability, urbanisation, increasing inequality, and political uncertainty (p.12) to this list. Australian research has come to similar conclusions.
The Commonwealth Scientific and Industrial Research Organisation (CSIRO) point to the “growth in computing power, device connectivity, data volumes and artificial intelligence” ((Hajkowicz et al., 2016, p.7) as trends to watch in coming years. While stressing these are yet to be fully felt in the Australian economy, each of them have been growing exponentially, so that their impacts are likely to be both sudden and significant. Each of these individual drivers of change are linked to all the others impacting Australia — so that we are seeing the growth of the peer-to-peer marketplace, significant demographic change, the end of the mining boom, and regional economic changes impacting our Asian trading partners coming together at the same time. We will consider these change drivers in more detail throughout this report.
A history of panic
While it is impossible to predict the future solely on what happened in the past, it is important to remember that people have been very concerned about the devastating impact of technology for hundreds of years, and yet many (if not most) of their worst predictions never occurred. Robert Malthus’ (1798, np) famous prediction of societal misery related to the inevitability of population increase has not come to pass. The Luddites destruction of machines in the first industrial revolution, which they blamed for destroying their jobs and trades, proved ill-informed (Frey & Osborne, 2013). In 1930 Keynes, the leading economist of his day, warned the world needed to prepare for “technological unemployment” (IMF, 2018, p. 6) where large numbers of people would be replaced by machines and would never work again.
Yet, although the technological changes introduced over the last 200 years have brought large scale economic shifts, eventually they have led to ever more jobs. It is true that this has often involved significant dislocation, and that this frequently took many decades to settle, however, ultimately more jobs were created than destroyed (Quigley & Chalmers, 2017).
In 2014, the Pew Research Centre (Rainie & Anderson, 2017, p.2) asked 1,408 experts if this time, machines would create more jobs than they would take. The experts were split almost 50:50 on whether there would be more or fewer jobs in the future due to technological change. Some predicted a ‘jobs apocalypse’ (where virtually every job currently being performed by humans would eventually be taken over by robots) — some have presented this as a future we should strive towards (Srnicek & Williams, 2015). The other extreme predicted the main problem in the future will be a chronic shortage of workers for all the jobs about to be created.
Despite these disagreements about the short to midterm employment prospect resulting from technology and other change drivers, everyone agreed that we are living through significant and world changing times and that if people are to remain employable, they will need to acquire and develop new skills. These do not only refer to technological knowledge and skills, but also to ‘soft’ skills such as collaborative capability, empathy and entrepreneurial skills.
It is also argued that if we want to avoid the significant social dislocation caused by the pace and scope of technological change we will need governments, policy makers and businesses to work together to address these threats and how to alleviate them (Bakhshi et al., 2017).
Uneven Impacts of Change
Whether experts predict the mass elimination of jobs (Frey & Osborne, 2013), or more new jobs being created than lost (AlphaBeta, 2017), overwhelmingly everyone agrees the changes occurring in the labour market will be significant, substantial and likely to require a large proportion of the workforce to engage in retraining, reskilling and lifelong learning (Riad, 2017). This will require businesses, governments and education facilities finding new ways to reach a growing number of people needing access to the skills essential for the new economy (CEDA, 2015). In such a fast-changing world, even those leaving school today may not have the skills they needed for jobs they will be applying for.
For the foreseeable future, the challenge of ‘cybernation’ is not mass unemployment, but the need to educate many more young people for the jobs computers cannot do.
While there are too many people qualified for many current jobs that are disappearing, there are also skills shortages where companies struggle to find those with the right skills to fill their vacancies (Commonwealth Bank, 2017; OECD, 2013). A “2017 talent shortage survey found that 40 per cent of employers reported difficulties in finding skilled talent, while the number of employers filling these gaps by retraining and developing people internally has more than doubled since 2015” (WEF, 2018, p.3).
Many predict a hollowing or polarising of workplaces (IMF, 2018; OECD, 2017) producing winners and losers, with the highly-skilled rewarded by high-paying jobs while the low-skilled find themselves in low paid jobs that are increasingly monitored, managed and working under automated surveillance technologies (West, 2108).
The polarisation of jobs within workplaces has been a recognised trend in industrial relations for a long time (Deery & Welsh, 2001) and the disparate treatment of workers in such polarised workplaces has been extensively documented (Brown, Ashton & Lauder, 2012; Brown, Hesketh & Williams, 2004; Ehrenreich, 2006, 2011; Kusnet, 2008; Wynhausen, 2005). A common theme in this literature is that those with hard to obtain skills are offered full time employment on good wages, while those with easy to replace skills are often not fully integrated into their workplace, work as part-time or casual employees only when they are needed by their employer, and are paid significantly less (Davies et al., 2011). And while new jobs are certainly being created, these are often ‘better … but also fewer’ (West, 2018), and require much higher skills to obtain (CEDA, 2015). Figure 1 shows that the trend in new jobs has moved towards professionals and skilled workers.
However, others take a much more positive perspective on the future. As technology replaces jobs that are “dull, dirty, dangerous and demanding” (Hajkowicz et al., 2016, p.78), the future of employment will involve jobs that are more rewarding and creative (CEDA, 2015; Commonwealth Bank, 2017; FYA, 2017a; Hajkowicz, 2016; Sundararajan, 2017) — some authors stress that future jobs will allow employees to be more fully ‘human’ (AlphaBeta, 2017, p.8; CEDA, 2015; Frey & Osborne, 2013; FYA, 2017a).
A further complication here is that those caught in low-paid and low-skilled jobs, or who have been pushed out of the job market entirely, are more likely to see their career as a relatively fixed part of their identity (Dolby, Dimitriadis & Willis, 2013; Kenway, Kraack & Hickey-Moody, 2006; Weis, 1990, 2005) — that is, to see themselves as being their job title rather than understanding the full breadth of skills they possess that could be adapted to changing work possibilities. The rapidly changing nature of work will mean people will be unlikely to remain ‘one thing’ throughout their whole career, with some estimating that “a 15-yearold today will experience a portfolio career, potentially having 17 different jobs over five careers in their lifetime” (FYA, 2017b, p.3).
A trend towards the ‘hollowing’ of workplaces is likely to accelerate as jobs replaced by technology increasingly come from the middle of the employment hierarchy. And as those in the middle see their jobs being replaced, they in turn take the jobs of less skilled employees (Bakhshi et al., 2017; FYA, 2017a; IMF, 2018). Increasingly, gaining employment depends on first having various credentials and qualifications (FYA, 2017b) with educational qualifications being used as a way to sort and eliminate applicants (Brown et al., 2004).
This means that competition for jobs at the bottom of the jobs hierarchy will become increasingly fierce (Australian Government, 2018) with “graduates ‘pushing down’ into lower skill level occupations where they are competing with people with fewer or no qualification” (p.3). Those currently without credentials may struggle to gain the skills needed to obtain jobs with more rewarding remuneration due to the expense and social distance they have always faced in gaining a university qualification (Kenway et al., 2006; Weis, 1990, 2005) — university being easier to successfully complete if someone in your family has previously attended. Also, the expense of a university education, in terms of time, fees, forgone earnings, and the uncertainty of a likely career post-qualification, weigh more heavily on young people who do not know anyone with such a qualification (Teese & Polesel, 2003).
Unskilled people tend to have left school early. Given that future employment is predicted to require lifelong learning (FYA, 2017), this will make life difficult for those who struggled at school the first time.
Policy solutions mostly stress education and retraining as needing to become even more central to government policy concerns (IMF, 2018; OECD, 2013). Such solutions, however, stress that governments require the cooperation of education providers and businesses, especially since the training needed to acquire the skills for particular businesses are often very specific to those businesses and are often only fully understood by those businesses too. Further, ongoing and lifelong learning is often presented as being the responsibility of the individual worker. However, workers have difficulty in meeting the expense of retraining (both in terms of time without a wage, as well as the cost of the training itself) and difficulty knowing what training will best prepare them for future jobs (Sundararajan, 2017).
There are a number of clear messages in this plot. First, potential job losses are polarised: Jobs in administration and sales (and many service areas) will disappear, while jobs in the technical professions and personal services will remain. Second, many of those jobs remaining are characterised by nonroutine thinking and especially high levels of originality and creativity.
Many believe that STEM (Science, Technology, Engineering and Mathematics) qualifications will be increasingly in demand (Commonwealth Bank, 2017), stressing that too few Australian students are gaining such qualifications (FYA, 2017b). However, a degree in STEM by itself will not guarantee a job in the future, and will certainly not bypass the need to continue on with lifelong learning (FYA, 2017).
Automation, Computerisation, New Technologies
Until recently, technological progress has involved the automation of highly routine physical tasks (Hajkowicz et al., 2016). This has meant that the burden of technological progress has been felt mostly in manufacturing, mining and related industries. Today, many believe that automation will occur in any task able to be specified by an algorithm and performed by a robot or computer system (Frey & Osborne, 2013). Often the jobs facing this new wave of automation are associated with those in the middle of the job market, that is, jobs such as bookkeepers or paralegals, jobs which until recently seemed both safe and relatively well-paid. Robots have much more difficulty replacing work that involves fine motor skills — such as making beds or folding towels – or in locating items in unstructured space — such as tidying magazines on a coffee table (Brynjolfsson & McAfee, 2012) at the lower end of the labour market. This is the cause of the hollowing out of workplaces referred to above, where jobs remain at the top and bottom, but those in the middle increasingly disappear.
We will see training for the jobs of the past, and for service jobs. The jobs of the future will not need large numbers of workers with a fixed set of skills – most things that we can train large numbers of workers for, we will also be able to train computers to do better.
Moore’s Law states that ‘the number of transistors on computer processors will double’ every two years (Hajkowicz et al., 2016, p.31). This leads to exponential growth in computing power over time and this in turn means that computers and robots become increasingly more effective and efficient. This opens up more jobs to being taken over by machines. However, rather than necessarily destroying jobs, new technologies are likely to replace the dull aspects of jobs and thereby make the job as a whole more rewarding, interesting and enjoyable (Hajkowicz, 2016). As Hajkowicz says, “Spreadsheets didn’t kill accountancy jobs, it just changed them”.
A frequent piece of advice given to young people regarding automation and the future job skills they will need, is for them to augment their abilities to work with technology (Davenport & Kirby, 2016; Quigley & Chalmers, 2017). That is, they are more likely to be successful if they ‘race on the machine rather than with it’ (Hughes, 2017, p.132).
The future of work will be primarily about how people can collaborate effectively with machines to do what neither can do alone.
The fact that jobs can be replaced by machines does not automatically mean that they will be. “(T)here are legal as well as ethical obstacles that may prevent such a substitution or at least substantially slow down its pace” (Arntz et al., 2016, p.7). For instance, while bookkeeping, accounting and auditing are generally seen as job categories highly likely to be automated, few of these jobs can be performed without some level of “group work or face-to-face interactions” (Arntz et al., 2016, p.14). Humans still prefer to have complex interpersonal interactions with other humans, rather than with machines.
And while the work of bookkeepers and some lawyers can be automated in theory, those of “gardener, hairdresser, or home health aide” (Brynjolfsson & McAfee, 2012) remain beyond technology’s reach. It is estimated that rather than technology replacing all jobs that it in principle can, that “Over two-thirds of the shift away from automatable tasks will be driven by people changing the way they work, not changing jobs” (AlphaBeta, 2017, p.13).
The Skills of the Future
58% of students aged under 25 years in Australia (are) enrolled in fields of study that will be radically affected by automation in the next 10-15 years. If we focus just on VET students, the proportion of students being trained in the at-risk occupations rises to a significant 71%. … Such jobs include woods trades, horticulture, and printing.
Predicting the skills necessary for future jobs begins with the obvious problem of specifying skills for jobs that do not currently exist. The World Economic Forum estimates that ‘up to 65 per cent of children entering primary school today are likely to work in jobs that do not yet exist’ (Raid, 2017, p.17). In fact, ‘it is much easier to accurately identify the jobs that will be destroyed by technological change than it is to predict those that will be created in the future’ (CEDA, 2015, p.21). For instance, one report says that ‘modelling … suggests almost five million jobs (in Australia) face a high probability of being replaced in the next decade or two while a further 18.4 per cent of the workforce has a medium probability of having their roles eliminated’ (CEDA, 2015, p.8).
Some economists have shown that while this structural change has been occurring in the types of skills needed in the workplace, this has not reduced levels of employment, so that ‘the new labour saving technologies did not reduce the demand for labour’ (Arntz et al., 2016, p.23). The nature of labour is, however, changing.
The shift from routine to non-routine skills
The shift in skills needed due to automation and computer technology is nicely illustrated in the Figure 2 which shows the relative changes in employment by skill type over the 30-year period in Australia from 1986 to 2016. Routine cognitive jobs decreased slightly and routine manual jobs decreased by a quarter, but nonroutine cognitive jobs increased by almost a quarter as well, while non-routine manual jobs almost doubled from one-in-every-twenty to slightly more than one-inevery- ten jobs.
Technology is increasingly eliminating jobs that young people (FYA, 2017b) and the poor (West, 2018) have traditionally used to enter the labour force. A recent Australian report stressed we need to rethink our education policies given that the overwhelming majority of young people are ‘enrolled in fields of study that will be radically affected by automation over the next 10-15 years’ (FYA, 2017a, p.36).
Australian Government (2018) analysis of trends in current high employment industries shows that most of the industries with the largest proportions of people with no post-school qualifications are predicted to decline as a share of total employment. These are industries that traditionally have employed large numbers of working class people, such as agriculture, manufacturing and electricity, gas, water and waste. One concern is that few of the new 21st century industries employ large numbers of people.
Not all jobs that can be automated will be automated, and jobs that cannot be automated today may be tomorrow. While it is not possible to predict with certainty which jobs will continue into the future, it is clear that certain skills are much less likely to be automated than others. This difference relates to how routine the work is. “Routine tasks are defined as tasks that follow explicit rules that can be accomplished by machines, while non-routine tasks are not sufficiently well understood to be specified in computer code” (Frey & Osborne, 2013, p.17).
Whether in manual or cognitive work (see Figure 3) the major growth in jobs has been in the non-routine sectors. The skills that have had increasing demand include “creative intelligence, social intelligence and problem solving” and these are what are sometimes referred to as “21st Century skills, enterprise skills and employability skills” (FYA, 2017a, p.32). These skill sets include ‘”confidence, communication, creativity, project management, enthusiasm for learning, critical thinking, teamwork, digital literacy, financial literacy and global citizenship”. In fact, “the categories of interpersonal, creative and information synthesis are projected to increase from just under half of all work activity to almost 70 per cent over the thirty years from 2000 to 2030” (Charmers & Quigley, 2017, p.65).
The industries that came into existence in the US after 2000 were only employing half of one per cent of all US jobs (Quigley & Chalmers, 2017, p.21). When Facebook purchased Instagram for a billion dollars, it employed only 13 people (Quigley & Chalmers, 2017, p.83).
Routine tasks are harder to define, and often relate to a single part of a job, rather than the job in its entirety (Hughes, 2017). This is not limited to low-paying jobs, but rather it is said to be the case that “a large part of what professions learn in their long educations can be automated” (p.135). However, UK research has found that “Jobs with salaries of less than £30,000 a year are almost five times more likely to be lost to automation than jobs with salaries of more than £100,000 a year” (Charmers & Quigley 2017, p.60).
This raises a question concerning how well we are able to predict the skills that will remain essentially human and those that will be taken by machines. An interesting example is that of the driverless car. While these are yet to take over any jobs, it must be remembered that driving was, until very recently, often presented as a good example of the kind of job that computers would be unlikely to be able to achieve in the near term, and yet “today Google’s driverless cars have driven over 2 million miles” (Bakhshi et al., 2017, p.22). One estimate in the US is that “driverless deliveries would put at least 2.5 million drivers out of work” (West 2018).
In tomorrow’s job market adaptability, resilience, buoyancy and entrepreneurial capabilities are of growing importance. This is because of the increased pace of change fuelled by technological innovation and globalisation increases the need for workers to handle minor and major transitions. Workers will need the capability to handle a career dead-end (or job loss) and create their own job in another space.
A common thread to the predicted jobs of the future is that they will require entrepreneurial skills. Although entrepreneur can mean very different things to different people, it is often taken to mean that “the future workforce will need to be more autonomous and self-directed, working on tasks independently with less supervision and support from managers or supervisors. Many more people will work externally, from home or a remote office. Young people of today will need to manage their own time more, make more decisions about priority and importance of tasks and be more personally motivated and driven” (FYA, 2017b, p.18).
Entrepreneurs are also seen as risk-takers, those who start their own businesses. The barriers to starting a business are decreasing due to the easy availability of computing power and connectivity, the low-cost of these, the availability of financing (including crowdfunding), the fact many businesses are now much less capital intensive, and because marketing and gaining customer feedback are easier today in an interconnected world. The reduction in these entry costs are reflected in the results of a global survey of over 12,000 Millennials that “found 68% of respondents (believed) they have the opportunity to become an entrepreneur” (FYA, 2017a, p.18).
There are strong reasons to believe the freelancer and portfolio worker will become a much more common model in tomorrow’s labour market’ (Hajkowicz, 2016, p.19).
Sometimes becoming an entrepreneur is promoted as a way to avoid the increasing inequality in society, where we should “aim for a future of crowd-based capitalism in which most of the workforce shifts from a full-time job as a talent or labour provider to running a business of one — in effect a microentrepreneur who owns a tiny slice of society’s capital” (Sundararajan, 2017, p.7). However, while such a shift is seen as providing workers with a larger stake in the economy than they previously may have had, it also comes at a cost where “young entrepreneurs face increasing financial uncertainty” (Lagarde, 2017, p13).
The notion of the growing importance of entrepreneurial skills is a central piece of advice being given to young people, and so schools and universities are being encouraged to teach these skills (Brynjolfsson & McAfee, 2012) so that entrepreneurialism “becomes a lifestyle” (UKCES 2014b, p.14). It is generally predicted that entrepreneurial skills will become essential as more people move to working in ways that are less fixed to a single employer so that their jobs become more like ‘portfolio workers’ — that is, freelance, one-person businesses.
While such work is often seen as highly precarious, that is, where “platform workers may have multiple jobs, work long hours and under high stress” (OECD, 2017, p.14) and while it may mean “all jobs will be less secure and an ever-greater portion of the workforce will become part-time, on-demand, independent contractors without benefits” (Hughes 2017, p.139) “one survey found 88 per cent would continue freelancing even if they were offered a traditional full-time career” (Hajkowicz et al., 2016, p.37).
These new jobs allow for much more flexibility and as such “provide greater opportunities for underrepresented groups to participate in the labour market” (OECD, 2017, p.2). The age of lifelong employment is effectively over, with workers “now staying in jobs, on average, for about 3.3 years” (Charmers & Quigley, 2017, p.133).
STEM, STEAM and digital skills
So ubiquitous will ICT be in the future that it will be added to reading, writing and arithmetic as basic competencies expected of all Australians.
In The Global Auction (Brown et al., 2012) the authors point to seemingly contradictory facts. The first is that as the world becomes more driven by technology, the expectation is that more people will need STEM qualifications to obtain well-paying jobs, and yet fewer students appear to be studying STEM subjects at tertiary level. Despite this, the authors point out that “the STEM workforce in the United States totals about 4.8 million, which amounts to less than a third of the 15.7 million workers who hold at least one STEM degree” (Brown et al., 2012, p.38). Nonetheless, despite this apparent over-supply of STEM professionals, the call to encourage more young people into the field is “reinforced by a strong steer from government based on the view that you could make a manager out of an engineer but you couldn’t make an engineer out of a manager” (Brown et al., 2012, p.38).
While this could be understood as diminishing the importance of holding a STEM qualification, it is very much a minority opinion. In fact, the growing importance of holding such qualifications is a strong theme in the literature, such that many are concerned there will be a looming skills shortage in Australia due to our growing need for these skills (Office of the Chief Scientist, 2016).
The Commonwealth Bank (2017) refers to a forecast “that 45 per cent of employers are seeking to increase their STEM-qualified staff over the next 5-10 years” (p.11). Others predict that workers will need to use the thinking skills acquired in STEM education in virtually all future job roles — “Workers will use the foundational skills of mathematics and science for 9 hours a week (up 80 per cent from today) and advanced technology skills for 7 hours a week (also up 75 per cent from today)” (FYA, 2017a, p.7).
STEM skills are often aligned with calls for digital competence.
Digital competency will be a basic competency for all workers in the future. It needs to be included as a core component of school education, both in terms of content and delivery, as distinct from the teaching of specialised ICT, technology and computer science subjects.
While most commentators believe that STEM skills will be the most secure pathway to the jobs of the future, not everyone agrees. For instance, Sundararajan (2017) believes “As the cognitive capabilities of digital machines expand, students may need less education in science, technology, engineering, and math and may benefit from a greater emphasis on design thinking, entrepreneurship, and creativity to prepare them for a micro-entrepreneurial career” (p.11).
This emphasis on creativity and design thinking is taken up in increasing interest in combining STEM education with arts and design, to provide the A in ‘STEAM’ education. Further, STEM is also linked to digital literacy: “The jobs of the future require problem solving and digital skills, and innovative and creative thinking, all taught through STEM” (Commonwealth Bank, 2017, p.11). Another report argues that “over 50% of jobs will require significant digital skills and yet our young people are not learning them in schools” (FYA, 2017a, p.2). Figure 4 provides estimates of the proportions of future jobs that will need various levels of digital literacy, with more than half of future occupations needing much more than the skills learnt in merely operating computers.
Problem solving skills are unlikely to be taken over by computers in the near term and are predicted to become increasingly important at work, including taking more work time as the average job will see them increase by 90 per cent to require 12 hours per week by 2030 (FYA, 2017b, p.7). The same report stresses “The skills that will matter most in the workplace of the future are, by a wide margin, problem solving, judgment and critical thinking” (p.16).
Problem solving skills in demand will include: “Originality and Fluency of Ideas. Learning Strategies and Active Learning — the ability of students to set goals, ask relevant questions, get feedback as they learn and apply that knowledge meaningfully in a variety of contexts” (Bakhshi et al., 2017, p.66).
By looking at the skills required in job advertisements, research has shown that “the proportion of jobs that demand critical thinking has increased by 158%, creativity by 65%, presentation skills by 25% and team work by 19%” (FYA, 2017, p.7).
The issue with many of the skills needed for future jobs is that they often require extensive experience in the workplace to acquire and this can put young workers at a disadvantage where jobs are only available to those with experience, and acquired on the job. Some have warned that the jobs used by youth to enter the workforce are also the jobs technology is displacing (Brynjolfsson & McAfee, 2012; Ross, 2016).
Interpersonal skills remain a clear advantage humans hold over machines. Frey and Osborne’s (2013) research stressed that many jobs will potentially be able to be done by machines, however, whether they will be done by machines is not simply a question of the machine’s ability to do a particular task, but also of our willingness to choose a robot over a human. As Schwab (2016) asks, “would we consult an AI-driven robot doctor with a perfect or near-perfect diagnostic success rate — or stick with the human physician with the assuring bedside manner who has known us for years?” (np)
Frey and Osborne (2013) stress that computers struggle with what they call ‘social intelligence’ and as such “real-time recognition of natural human emotion remains a challenging problem” (p.29). Whereas: “socially intelligent employees are able to quickly assess the emotions of those around them and adapt their words, tone and gestures accordingly” (Davies et al., 2011, p.8).
It is also true, however, that humans have predictable cognitive biases and that these often undermine our ability to see the fairest or best solution to many problems (Kahneman 2011). It is in such tasks that a programmed algorithm may well perform better than a human and that ‘Such algorithmic improvements over human judgement are likely to become increasingly common’ (Frey & Osborne, 2013, p.21).
Computers will outcompete human labour “when a problem can be speciﬁed — in the sense that the criteria for success are quantiﬁable and can readily be evaluated’ (Frey & Osborne, 2013, p.16). “People get bored, people get headaches. Computers don’t” (Brynjolfsson & McAfee, 2012). More complex skills that require novel thinking and adaptability given the needs of the context “will be at a premium in the next decade, particularly as automation and offshoring continue” (Davies et al., 2011, p.9).
This shift in jobs of the future towards the kinds of skills that humans can do and that machines cannot is presented as a trend towards making employment not only more enjoyable, but also fundamentally more human (see, AlphaBeta, 2017). For instance, it is estimated that “automating routine tasks will improve job satisfaction by 62% of low-skilled workers” (p.23).
Interpersonal, human skills will also be important as demographics change. An ageing population is causing a shift in the profile of Australia’s workforce. For instance, a quarter of all new jobs created in the five years to 2017 were in Health Care and Social Assistance (Australian Government, 2018, p.11). However, an ageing population does not only impact healthcare, but also means that workplaces will need to be more accommodating of difference, since many will become 4G workplaces — where four generations of employees will be working together in close proximity (UKCES, 2014b).
Similarly, all forms of cultural differences will need to be accommodated in the workplaces of the future (Hajkowicz et al., 2016) and this is likely to become increasingly the case due to migration and globalisation (Davies, 2011; FYA, 2017a; Horton et al., 2018), particularly for Australia in the ‘Asian Century’ (Australian Government, 2012).
Team work has always been a feature of employment. However, a number of trends are making the need for collaboration and networking centrally important skills in the new economy. As people become more entrepreneurial and potentially work for more than one employer at a time, they will also need to have strong networks of people who know their skill set and who will recommend them for new work.
In the future, human skills such as creativity, imagination, emotional intelligence and empathy (Commonwealth Bank, 2017, p.16) will become increasingly important to augment our interactions with computer systems. The OECD (2017) points out that “the labour market is increasingly rewarding soft skills such as the ability to communicate, work in teams, lead, solve problems and self-organise” (p.19).
Creativity is also particularly difficult to program a computer to achieve. This is because creativity, by definition, produces something that is new, novel and therefore something that cannot be fully predetermined in code beforehand. In that sense, a truly creative outcome is one that can only be recognised at the end of the process when looking back — computers are rules based and creativity could be virtually defined as the very opposite of that.
Creativity: Value will not come from the old ways, only the new, making imagination and creativity central to tomorrow’s capabilities.
However, creativity is not just about producing something that is novel or unexpected. A creative solution to a problem also needs to be ‘right’ in the sense that it needs to provide a positive solution to the problem at hand. Creativity skills are growing in demand. “A 2016 World Economic Forum report estimates that five years from now, more than a third of skills considered important today will no longer be relevant. Creativity and emotional intelligence will be among the top three needed” (Riad, 2017, p.18).
Allied with this, commentators predict a “low susceptibility of engineering and science occupations to computerisation’ since they require a ‘high degree of creative intelligence” (Frey & Osborne, 2013, p.44).
Ford’s moving assembly line is dominated by machines. However, there are many humans shown in the clip, performing complex spatial tasks that it is difficult for robots to achieve. These workers work alongside the machines. Such jobs have a long future.
Other jobs that are unlikely to be replaced by robots include many trades such as plumbing and carpentry. However, even here it is important to remember that disruptive technological change is likely to occur, even if it may not require a robot to operate in the same way as a human. Tasks may be changed to meet the needs of the robot (Frey & Osborne, 2013). Both “predictable physical and unpredictable physical” occupations “are expected to experience workplace change driven by automation in the near future” (AlphaBeta, 2017, p.9).
Davenport and Kirby (2016) turn the standard argument about automation and computerisation on its head and ask, “if you were a machine, what shortcomings would you readily admit to, and want to have a human making up for?” (np). They suggest that your best career path is to become what the machine would need.
Skills in Lifelong Learning
The monumental changes underway make it nearly impossible to predict with certainty the skills that will be needed and rewarded in the future labour market. However, what is clear is that people will need to retrain and to build on their skills throughout their working lives. This capacity for adaptability and retraining is likely to become a key skill that employers will look for in their employees (FYA, 2017a; Rainie & Anderson, 2017; UKCES, 2014a).
Reskilling and retraining will become increasingly necessary if people are to remain employed. In fact, individuals will be expected to ‘take greater personal responsibility for acquiring and continuously updating skills for progression and success in the face of limited investment from employers and government and increasing division between low and high-skill jobs’ (UKCES, 2014b p.26). Research suggests that businesses that invest in “workforce reskilling and human capital development” find that it is a “noregret action” (WEF, 2018, p.17), in that the benefits are positive to the business regardless of patterns in skill availability.
Today’s young people will need to spend more hours learning on the job than ever before … In fact, Australian workers will spend one-third of their hours at work learning, a 30 per cent increase from today.
There have been few times in history when the future of work has been less like the past. In the past people spent most of their time making things, however, in the future relationships are likely to be as important as what is produced. In the past people worked in one job for most of their working lives, in the future a large section of the workforce will likely work for themselves. In the past people were defined by their job title, in the future they will be defined and redefined by the skills they have and how they go about marketing those skills. In the past, when you became something you were known as that type of worker, in the future people are likely to go on becoming new versions of themselves as they continuously learn new skills. The jobs of the future look to be much more dynamic, interesting and rewarding. And today, for those who engage with this project of lifelong learning, that future is within reach.