Automation and job displacement will be one of the most significant challenges for the global economy of the coming decades. A 2017 McKinsey report estimated that 375 million workers – 14 per cent of the global workforce – will need to switch occupational categories by 2030. This is comparable to the shift from agricultural economic models to industrial ones in the late nineteenth and early twentieth centuries.
In one of the most cited papers on the subject, The Future of Employment: How Susceptible Are Jobs to Computerisation?, Carl Frey and Michael Osborne from the University of Oxford estimated 47 per cent of total US employment to be at risk. The impact of technologies such as artificial intelligence and robotics is a hot research subject: a paper published in July this year by German and Danish academics concluded that “firms that adopted robots between 1990 and 1998 increased the number of jobs by more than 50 per cent between 1998 and 2016, while firms that did not adopt robots reduced the number of jobs by more than 20 per cent over the same period.”
The World Economic Forum suggests that by 2022, automation will displace 75 million jobs globally – but create 133 million new ones. However, in his bracing new book The Technology Trap, Carl Frey extrapolates from the history of the industrial revolution to offer a vision of the future in which Amazon Go, AI assistants and autonomous vehicles are “worker replacement” technologies.
Research into the likelihood that a job will be impacted by digitisation has largely focused on the “automatability” of the role and the subsequent economic, regional and political implications of this.
What this research doesn’t take into account is something more important for the millions of taxi drivers and retail workers across the globe: their likelihood of being able to transition to another job that (for now) isn’t automatable. Recent research suggests that the answer to this may be that the skills that enable workers to move up the ladder to more sophisticated roles within their current areas might be less important than broader skills that will enable workers to transition across sectors.
In July, Amazon announced that it would spend $700m retraining around 30 per cent of its 300,000 US workforce. While laudable, it will be interesting to see the outcome. In the UK, the National Retraining Scheme has largely been led by employers, meaning that those on zero-hours contracts and part-time workers – often low-skilled – will miss out. Governance will be a crucial element of ensuring that such schemes focus on individuals and life-long learning, rather than upskilling workers into roles that will soon also face automation.
According to the McKinsey report, “growing awareness of the scale of the task ahead has yet to translate into action. Public spending on labour-force training and support has fallen steadily for years in most member countries of the Organisation for Economic CoOperation and Development.”
This impacts not only the low-skilled and poorly compensated. Goldman Sachs once had 500 people on its equities trading desk; it now has three. The global impact of automation is also put into relief by research demonstrating that, if China and India are taken out of the picture, between 1988 and 2015, income inequality increased throughout the world, particularly in the west. Elsewhere, billions of people do not have the essentials of life as defined by the UN Sustainable Development goals.
Globalisation has brought enormous benefits to the world, but it has taught us that complacency towards the impacts of change can lead to social unrest and political instability. We need to ask ourselves, what does prosperity look like in the 21st century? Alongside climate change, automation is arguably tech’s biggest challenge. As with globalisation, governments and employers – and us workers – ignore its potential consequences at our peril.
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