Around the world and within every industry, machines are disrupting occupational structures and bringing into question the nature of human labour at an alarming rate. Previous limitations surrounding robotics and automation have been overcome, with investment into such technologies on an exponential upward trajectory.
Changying Precision Technology Company in China focuses on the production of mobile phones and increasingly uses automated production lines. A few years ago the factory was run by 650 employees, but now just 60 people are required to complete the job, with robot co-workers responsible for the rest.
In 2015 Nike completed pilot testing on automated stitching, reducing production on a typical size run of its iconic Air Force 1 shoe from over 500 components across multiple factories to just a single machine and operator.
Elsewhere, automated harvesting equipment is revolutionising traditional agricultural practices, reducing the need for labour-intensive tasks normally performed by dozens of farm-workers.
Whether one should be optimistic or not about these emergent trends, one thing is clear; there is no getting off the train of technological progress anytime soon. Regardless of which side of the debate one is on, within current debates over AI and automation two injustices are repeatedly committed by both parties.
The first is a tendency to dramatically understate the scale of impending skill set disruption on the near horizon.
Understanding the Changing Nature of Work
It is important to note that where it has done well to serve as the plot-line for countless sci-fi movies and stoke dystopian fears, the complete substitution of human with robot labour is not what is now happening. Indeed, a 2017 Mckinsey & Company report found that the proportion of occupations that can be fully automated by adapting currently demonstrated technology is less than five per cent.
Undoubtedly there are still vital cognitive, social, emotional, and critical thinking abilities innate within human biology that are currently, and perhaps will remain so for a long-time, unattainable to AI.
But these skills compose only a tiny fraction of the work activities that most people are actually engaged in within their chosen occupation. The other components, whether they be physical tasks within a predictable environment, data processing, or administration can now be done quicker, more efficiently and at a lower-cost by a machine.
Therefore, playing out in front of our eyes is not the utter replacement of human with robot labour, but rather the increased rate at which technology is assuming a larger share of people’s work activities. The same Mckinsey & Company report estimates that half of all the activities people are paid to do in the world’s workforce, the equivalent of $15trn in wages, could potentially be automated by adapting currently demonstrated technologies.
Undoubtedly, if the history of progress has taught us anything, it is that new jobs in industries that do not presently exist will be created off the back of these advances in AI and automation. Up until now, the labour market has managed to adapt to the replacement of jobs with capital, with price effects tending to balance the forces of automation and creating new complex tasks for people to be paid to do.
But two emergent issues threaten to disrupt this trend. Firstly, in a world where machines can teach themselves, there is a distinct chance that machines will assume new forms of paid work created in the industries that we cannot now envisage.
A key difference between current and past episodes of technological advancement is that some forms of automation, for example, those that are based on machine learning techniques such as deep learning, improve performance over time when these AI have access to more data. Given the above, there is reason to assume that humans will be competing against more capable and increasingly sophisticated machines for the jobs of the future.
Human Labour in a Robot World
The second issue is that future employment growth is expected to derive disproportionately from smaller, generally high-skilled sectors and industries that will be unable to absorb job losses coming from other parts of the labour market. According to the World Economic Forum’s 2016 ‘The Future of Jobs Report’, by 2020, more than a third of the desired core skill sets of most occupations will be comprised of technical skills that are not yet considered crucial to the job today.
Emerging job categories such as data analysts, engineering specialists and information systems experts all require a high-degree of STEM (Science, technology, engineering and mathematics) related skills. There is already a fast-growing need for consummate technicians and specialists to create and manage advanced automated systems. For example, manufacturing and production sectors are rapidly being transformed into highly sophisticated industries where high-skilled engineers are in strong demand, and cheap human labour is rendered increasingly obsolete.
Labour in Developing Countries
This leads to the other injustice that plagues mainstream discourse over technological progress which is that neither techno-optimists nor alarmists have anything to say about the impact that technological advancement will have on the significant share of the global workforce that remains employed in agriculture, manufacturing and production industries, primarily in developing countries.
Too often are the opportunities and challenges posed by technological progress viewed solely through the lens of advanced economies. It must be raised that the vast majority of people in the developing world do not have the skills, or access to the resources to develop the skills, necessary to prosper in the digital era. The training required to become a data scientist, for example, entails an advanced degree in mathematics and statistics, computer science or engineering. Acquiring such qualifications is no simple task, and requires an investment in education and training for some years as well as access to adequate higher learning institutes.
Advanced economies with the capabilities to develop these skills already have a distinct advantage over their developing counterparts. Ultimately, these trends will upend traditional models of economic development and jeopardise the future of those people unable to gain the skills necessary to prosper in the digital age.
The Traditional Road to Prosperity
For the past hundred and fifty years countries have pursued a very particular model of economic development.
As far back as Japan in the late 1800s, a combination of low-wage agriculture and manufacturing, backed by protectionist policies to encourage import substitution and boost exports, was proven to create jobs and build household income. As workers and systems become more productive and households more prosperous, manufacturing moves up the value chain, producing higher quality products. With the construction of transport infrastructure including roads and railways, rural populations move to cities to join this industrialisation wave, creating urban concentrations of consumers with disposable income that helps generate greater prosperity.
It has been this developmental model that has driven a huge influx of 1.2 billion people joining the global labour market between 1980 and 2010, and that has brought millions out of poverty. It is hard to imagine how some of today’s most influential countries, Japan, Germany, or China, for example, would have achieved the level of their success if not for some application of this strategy.
In 2018 many developing countries aspire to advance their economies by employing a similar developmental model. Where emerging countries with young populations and high birth-rates tend to suffer from skills shortages due to their lack of educated citizens, their advantage lies in access to cheap and abundant labour. Traditionally both the agriculture and manufacturing sectors, the two industries needed to get the ball rolling towards industrialisation, have accommodated this advantage. The majority of work activities in these roles require limited training and professional oversight, making it possible for developing countries to leverage their labour advantage and grow these industries.
Globalisation added a new dimension to this model by making it easier for foreign companies to tap into cheaper labour markets and establish business operations far from home. This, in turn, brought more opportunities for wealth to be generated within developing economies through the construction of vital infrastructure and employment of significant numbers of the population by foreign companies.
This Time It Is Different
The rapid rate at which new technologies are being integrated into contemporary work environments is rapidly tearing down this bridge to prosperity. Uptake in the use of robotics has meant that industries are becoming less labour intensive while the need for highly skilled workers who are closer to where products and services are used is growing.
A 2017 Mckinsey & Company study looked at the automation potential for specific types of activities and jobs within the manufacturing sector. The report estimates that 68 per cent of total working hours spent on manufacturing-related activities in the developing world could potentially be automated using currently available technologies.
There is little incentive for companies from advanced economies to continue business operations abroad if they can fund the capital expenditure that is needed to build highly automated manufacturing plants. If a machine can operate as cheaply in Denver USA as in Chennai India, why pay to ship materials and finished goods around the world?
The drive to automate may ultimately reverse the outflow of manufacturing jobs from rich to poor countries. Such a hypothesis is supported by a survey of business leaders conducted by the Oxford Martin School with 70 per cent of respondents believing that developments in automation and 3D printing will encourage companies to move their manufacturing process closer to home. This new dynamic means that low-cost labour can be expected to lose its edge as an essential developmental tool for emerging economies, as automation drives down the cost of manufacturing globally.
Burning Down the Bridge to Prosperity
The opportunities generated by the Fourth Industrial Revolution are matched, if not surpassed by, its challenges. On the one hand, the widespread implementation of AI and automated systems might mean that advanced economies experiencing population declines or stagnation will be able to maintain living standards even as their labour force shrinks. On the other, this leaves low-income countries with high birth-rates stranded at the developmental midway point, unable to foster the skills necessary to prosper in the digital era. In the context of global development, the bridge to prosperity is being inadvertently burned down by those who have already made the crossing.
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