“So what should we tell our children?
That to
stay ahead, you need to focus on your ability to
continuously adapt, engage with others in that
process, and most importantly retain your core sense
of identity and values.
For students, it’s not just about
acquiring knowledge, but about how to learn.
For
the rest of us, we should remember that intellectual
complacency is not our friend and that learning –
not just new things but new ways of thinking – is a
life-long endeavor.”
Blair Sheppard
Global Leader, Strategy and Leadership
Development, PwC
The growing capabilities of artificial intelligence and robotics have led to claims we are on the cusp of a new machine age that will dwarf previous waves of automation in terms of the scale, speed and scope of the disruption it causes
(Brynjolfsson and McAfee 2014; Ford 2015; CitiBank 2016; Susskind and Susskind2015; World Economic Forum 2015; Avent 2016; Srnicek and Williams 2015).
Whereas the technologies that drove automation in the past required clear instructions in controlled environments to substitute for human endeavor, new technologies are now increasingly able to act and problem-solve independently, inferring the appropriate solution or actions on the basis of the external inputs, and ‘learning’ as they do so. As a result, machines (whether hardware or software) are increasingly able to perform both routine and non-routine tasks, physical and cognitive work. Tasks once thought to be the sole preserve of humans can now often be performed better, and increasingly more cheaply, by machines.
If automation is unlikely to wholly displace human labor, it is likely to change the shape of the labor market, the occupations that individuals work in, and the type of work tasks humans perform. It is also likely to reshape the type of tasks we perform within those occupations. As some but not all those tasks are automated, the nature of work will change. For example, a recent analysis of more than 2000 work activities across more than 800 occupations estimated that fewer than 5 per cent of all occupations could be automated entirely with existing technologies, but that 60 per cent of occupations have at least 30 per cent of constituent activities that could be automated today. The nature of work remaining would evolve significantly.
(McKinsey 2017).
A recent OECD study reached a similar conclusion: once job-level tasks are accounted for, the study estimated that only 9 per cent of jobs in the UK are susceptible to automation in the next decade, but that 35 per cent of jobs would change radically in the next two decades
(Arntz et al 2016)
The evolving bundle of tasks performed by human labor has the potential to improve the experience of work for many. As David Autor has argued, the interplay between machine and human comparative advantage allows machines to substitute for labor in performing routine and programmable tasks, while amplifying the comparative of advantage of humans in supplying problem-solving skills, adaptability, emotional and caring labor, and creativity. For many, this will lead to improved quality of work as complex, difficult to automate tasks increase as a share of work, with labor specializing and increasing the value of the performance of tasks that people continue to perform
(Autor 2017)
Spending more time performing and specializing in tasks in which we excel and retain comparative advantages over machines should be a positive outcome. At the same time, more repetitive tasks are more likely to be automated. Paradoxically, automation could make work more ‘human’.
In the absence of policy intervention, the most likely outcome of automation is an increase in inequalities of wealth, income and power. Automation has the potential to deliver enormous productivity dividends. McKinsey estimate that widespread adoption of AI, machine learning, and robotics could raise global productivity growth by between 0.8 and 1.4 per cent annually, while the UK’s Digitalization Review estimates that industrial digitalization could realize efficiency gains of approximately five per cent of GDP per year
(McKinsey 2017; HMG 2017a).
Technology has the power to improve our lives, raising productivity, living standards and average life span, and free people to focus on personal fulfillment. But it also brings the threat of social unrest and political upheaval if economic advantages are not shared equitably. Some sectors and roles, even entire sections of the workforce will lose out, but others will be created. Automation will not only alter the types of jobs available but their number and perceived value. By replacing workers doing routine, methodical tasks, machines can amplify the comparative advantage of those workers with problem- solving, leadership, EQ (Emotional Intelligence), empathy and creativity skills. Those workers performing tasks which automation can’t yet crack, become more pivotal – and this means creativity, innovation, imagination, and design skills will be prioritized by employers.
(“Workforce of the Future” PwC, 2018)
To prevent a worst-case scenario—technological change accompanied by talent shortages, mass unemployment and growing inequality—reskilling and upskilling of today’s workers will be critical. It is critical that businesses take an active role in supporting their current workforces through re-training, that individuals take a proactive approach to their own lifelong learning and that governments create the enabling environment, rapidly and creatively, to assist these efforts.
(“The Future of Jobs” WEF, 2016)
.
The growing capabilities of artificial intelligence and robotics have led to claims we are on the cusp of a new machine age that will dwarf previous waves of automation in terms of the scale, speed and scope of the disruption it causes
(Brynjolfsson and McAfee 2014; Ford 2015; CitiBank 2016; Susskind and Susskind2015; World Economic Forum 2015; Avent 2016; Srnicek and Williams 2015).
Whereas the technologies that drove automation in the past required clear instructions in controlled environments to substitute for human endeavor, new technologies are now increasingly able to act and problem-solve independently, inferring the appropriate solution or actions on the basis of the external inputs, and ‘learning’ as they do so. As a result, machines (whether hardware or software) are increasingly able to perform both routine and non-routine tasks, physical and cognitive work. Tasks once thought to be the sole preserve of humans can now often be performed better, and increasingly more cheaply, by machines.
If automation is unlikely to wholly displace human labor, it is likely to change the shape of the labor market, the occupations that individuals work in, and the type of work tasks humans perform. It is also likely to reshape the type of tasks we perform within those occupations. As some but not all those tasks are automated, the nature of work will change. For example, a recent analysis of more than 2000 work activities across more than 800 occupations estimated that fewer than 5 per cent of all occupations could be automated entirely with existing technologies, but that 60 per cent of occupations have at least 30 per cent of constituent activities that could be automated today. The nature of work remaining would evolve significantly
(McKinsey 2017).
A recent OECD study reached a similar conclusion: once job-level tasks are accounted for, the study estimated that only 9 per cent of jobs in the UK are susceptible to automation in the next decade, but that 35 per cent of jobs would change radically in the next two decades
(Arntz et al 2016)
The evolving bundle of tasks performed by human labor has the potential to improve the experience of work for many. As David Autor has argued, the interplay between machine and human comparative advantage allows machines to substitute for labor in performing routine and programmable tasks, while amplifying the comparative of advantage of humans in supplying problem-solving skills, adaptability, emotional and caring labor, and creativity. For many, this will lead to improved quality of work as complex, difficult to automate tasks increase as a share of work, with labor specializing and increasing the value of the performance of tasks that people continue to perform
(Autor 2017).
Spending more time performing and specializing in tasks in which we excel and retain comparative advantages over machines should be a positive outcome. At the same time, more repetitive tasks are more likely to be automated. Paradoxically, automation could make work more ‘human’.
In the absence of policy intervention, the most likely outcome of automation is an increase in inequalities of wealth, income and power. Automation has the potential to deliver enormous productivity dividends. McKinsey estimate that widespread adoption of AI, machine learning, and robotics could raise global productivity growth by between 0.8 and 1.4 per cent annually, while the UK’s Digitalization Review estimates that industrial digitalization could realize efficiency gains of approximately five per cent of GDP per year
(McKinsey 2017; HMG 2017a).
Technology has the power to improve our lives, raising productivity, living standards and average life span, and free people to focus on personal fulfillment. But it also brings the threat of social unrest and political upheaval if economic advantages are not shared equitably. Some sectors and roles, even entire sections of the workforce will lose out, but others will be created. Automation will not only alter the types of jobs available but their number and perceived value. By replacing workers doing routine, methodical tasks, machines can amplify the comparative advantage of those workers with problem- solving, leadership, EQ (Emotional Intelligence), empathy and creativity skills. Those workers performing tasks which automation can’t yet crack, become more pivotal – and this means creativity, innovation, imagination, and design skills will be prioritized by employers.
(“Workforce of the Future” PwC, 2018)
To prevent a worst-case scenario—technological change accompanied by talent shortages, mass unemployment and growing inequality—reskilling and upskilling of today’s workers will be critical. It is critical that businesses take an active role in supporting their current workforces through re-training, that individuals take a proactive approach to their own lifelong learning and that governments create the enabling environment, rapidly and creatively, to assist these efforts.
(“The Future of Jobs” WEF, 2016)