Analysis: In The Next 20-Years, 47% Of All Jobs In The U.S. Could Be Automated

Screengrab/GetConnected TV Show/YouTube

The majority of jobs to be spared from automation's impact continue to be those requiring tertiary education.

Back in 2013, a study by Carl Benedikt Frey and Michael Osborne from Oxford University found that nearly half -- 47 percent -- of American jobs were susceptible to automation in the next ten to twenty years.

Now, a working paper from the Organisation for Economic Co-operation and Development (OECD) builds on that study to offer a more nuanced view of automation's expected effect on jobs heading into the next couple of decades.

Its technique differs from Mr Frey and Mr Osborne’s study by assessing the automatability of each task within a given job, based on a survey of skills in 2015. Overall, the study finds that 14% of jobs across 32 countries are highly vulnerable, defined as having at least a 70% chance of automation. A further 32% were slightly less imperilled, with a probability between 50% and 70%. At current employment rates, that puts 210m jobs at risk across the 32 countries in the study.

But those numbers look different depending on which country is being examined and, for various reasons, do not apply equally across borders:

The study finds large variation across countries: jobs in Slovakia are twice as vulnerable as those in Norway. In general, workers in rich countries appear less at risk than those in middle-income ones. But wide gaps exist even between countries of similar wealth.

Differences in organisational structure and industry mix both play a role, but the former matters more. In South Korea, for example, 30% of jobs are in manufacturing, compared with 22% in Canada. Nonetheless, on average, Korean jobs are harder to automate than Canadian ones are. This may be because Korean employers have found better ways to combine, in the same job, and without reducing productivity, both routine tasks and social and creative ones, which computers or robots cannot do. A gloomier explanation would be “survivor bias”: the jobs that remain in Korea appear harder to automate only because Korean firms have already handed most of the easily automatable jobs to machines.

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