A new study predicts that globally between 0.4 billion and 0.8 billion people could lose their jobs to automation between now and the year 2030. According to McKinsey & Company, a consulting firm, between 3% and 14% of workers across the globe will have to get new skills in order to land new occupations in the course of the next ten years.
“Even if there is enough work to ensure full employment by 2030, major transitions lie ahead that could match or even exceed the scale of historical shifts out of agriculture and manufacturing,” says the report by McKinsey Global Institute which was published earlier in the month.
However the impact of automation will not be uniform across the globe and will instead vary between countries. How each individual country is affected will depend on the wealth of that particular country as well as the kind of jobs which already exist in each. McKinsey estimates that in about 60% of the jobs that are currently available across the globe, about a third of their constituent activities have the capacity to be automated.
In its study, McKinsey conducted research in some 46 countries where over 800 different jobs were assessed. According to the report there will a higher number of workers requiring to acquire new skills in advanced economies than in others. In Germany and the United States for instance about one-third of the workers will require to be equipped with new skills while in Japan the figure is close to 50% of the workers. Only about 12% of workers in China will require new skills on the other hand due to the fact that human labor will still be relatively cheaper than automation for a majority of the employers there.
Repetitive and predictable tasks
The jobs that are most easily automated are those that involve repetitive and predictable tasks and this includes preparing fast food, operating machinery and data processing tasks such as accounting and paralegal work. But according to McKinsey, full automation can only happen with less than 5% of jobs.
Jobs which face the least danger of full automation are those whose wages are relatively low and those which lack predictability. Part of the reason for this is that there is no incentive for business to invest on the technology. Such jobs include child care, plumbing and gardening. Occupations which pay high wages but which involve social interactions and managing people have a lower risk of automation because of the difficulty in programming machines for such tasks.