Automation is one of those emotive issues that can conjure up a range of different images in our minds. A vision of people signing on the dole queue, having been turfed out their jobs by machines. A picture of people living the life of Riley, served from dawn to dusk by robots. Or even sci-fi scenes, where humans are subjugated by machines until they finally revolt and overthrow their mechanised masters.
Actually, the reality is likely to be far more mundane, and it is interesting to see that in the UK, where automation has become increasingly common, latest figures show higher-than-ever employment rates, and the lowest unemployment since the early 1970s. Automation, it seems, does not necessarily equal fewer jobs; rather, it can create the conditions for new types of employment.
One of the common misconceptions around the automation issue is that machines take jobs on a like-for-like basis. That is, this machine replaces that job. However, while there are some jobs that can potentially be fully automated, for the most part it is much more a case of there being certain elements of a job that are at substantial risk of disruption because of technology, including things like job design changes and workplace reorganisation.
But what does the issue of automation mean for a university that is trying to ensure its provision maintains relevance in a rapidly changing economy? (Note: we are talking solely about automation, which is technology that can be programmed to do things automatically, rather than Artificial Intelligence, which is the science of making intelligent machines that can mimic human behaviour).
On the one hand, because automation tends to affect routine and repetitive work, the major automation risks are generally at the lower end of the skills spectrum in non-graduate jobs. For instance, according to our UK Occupations Automation Index, which identifies the time spent in each occupation on tasks that are considered high and low risk from automation, the jobs with most at risk tasks are window cleaners, painters and decorators, and plasterers. This doesn’t mean that these jobs necessarily will be automated; but that, according to academic research, a high proportion of each job involves tasks that could be under threat from automation. Nor does it mean that these jobs will be performed by robots. In the case of painters and plasterers, for instance, things like modular construction are likely to lessen the demand for on-site painters and plasters, while window cleaning is becoming much more capital-intensive than it used to be, meaning that it is taking fewer window cleaners to clean the same amount of windows.
On the other hand, the fact that the majority of high-risk tasks tend to be in low skilled occupations doesn’t mean that there aren’t threats to jobs that require degree-level qualifications. There are, and again we can identify them. For example, according to our index the three graduate-level occupations that contain the most high-risk tasks are taxation experts, town planning officers, and archivists and curators, while at the other end of the spectrum health service and public health managers, natural and social science professionals, and senior professors in educational establishments are deemed to have the lowest risk.
The more a university can identify which tasks and associated skills are under threat from automation, which ones are not under threat, and which ones could be a complement to automation in a given labour market, the better placed it will be to factor this into its course and skills module planning to encourage better long-term employment outcomes.
In many ways, automation is bound to be something of an unknown quantity, since we cannot know with any certainty what technological advances are on their way. However, by better understanding where the main risks are likely to be, and then applying this to thinking around course provision, universities can help to mitigate the risk of sending their students out into the world of work with skills that could soon be obsolete.
For more information, visit: economicmodelling.co.uk/higher-education