OECD estimates 14% of jobs at high risk of automation | MIT J-WEL

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OECD estimates 14% of jobs at high risk of automation

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Nearly all experts agree that machine learning, AI, and workplace automation following developments in these fields will replace many jobs worldwide. But estimates of the risk posed by automation have varied considerably. Some studies estimate that only 9% of jobs in the United States are at risk from automation, while others argue that nearly 50% of jobs in the United States are at risk; however, even the much-lower 9% figure equates to 13 million jobs in the US alone.

In March, the Organisation for Economic Co-operation and Development (OECD) published a working paper, “Automation, skills use and training,” that interprets work-related data from 32 OECD countries. The paper improves upon earlier automation estimates “by using a more disaggregated occupational classification…and identifying the same automation bottlenecks emerging from the experts’ discussion.” Automation bottlenecks are job tasks that experts believe will be difficult to automate, which include those requiring social intelligence, cognitive intelligence, and perception and manipulation, defined as the “ability to carry out physical tasks in an unstructured work environment.”

The study rated individual jobs along an automation probability scale; the study classified a job at high risk of automation if the estimated probability of automation was greater than 70%, medium risk (50-70%), or low risk (<30%).

 

Significant findings from the study include:

  • Nearly 50% of jobs included in the study are expected to be “significantly affected by automation,” but the risk is variable.
  • 14% of jobs are at high risk of automation; 32% are at medium risk; and 26% are at low risk of being automated.
  • The risk for automation is highest for workers at the youngest working age for all countries, with the exception of Russia.
  • Automation risk is also highly variable across countries; the study rates only 6% of jobs in Norway as highly automatable, in contrast to 33% of jobs in Slovakia.
  • Jobs that require minimal/low levels of education are the most susceptible to automation, while those that call for professional training or tertiary education are less likely to be automated. Jobs in agriculture and the manufacturing sector are particularly vulnerable.
  • Worryingly, “Workers in fully automatable jobs are more than three times less likely to have participated in on-the-job training, over a 12-month period, than workers in non-automatable jobs.”

 

The stated mission of OECD, which has 35 member countries, is to advance policies that will improve the economic and social well-being of people globally. One of its key goals is to “Ensure that people of all ages can develop the skills to work productively and satisfyingly in the jobs of tomorrow.” This aligns with the aims of J-WEL’s Workplace Learning Collaborative, which include identifying the skills that will be required in the workforce of the future as a result of new developments in AI, demographic trends, globalization, and other factors. The Workplace Learning Collaborative also aims to reassess the role and function of the learning organization in enterprises of all sizes.

Download the OECD study.