- Jul 24, 2021
In 2013, Oxford University academics Carl Benedikt Frey and Michael A. Osborne – drawing upon recent advances in machine-learning and mobile robotics – created an innovative methodology that allowed them to classify more than 700 occupations using AI-based job search, according to their susceptibility to computerization over the next two decades.
They also implemented this methodology to estimate the probability of computerization for these occupations, utilizing a Gaussian process classifier.
Probing the resulting estimates, they further examined the possible impacts of future computerization on US labor market outcomes. Their foremost goal was to investigate the number of jobs at risk, in addition to understanding how an occupation’s probability of computerization is related to individual wages and educational attainment.
While the study did not attempt to identify the occupations that will actually be supplanted by automation and artificial intelligence, it did highlight which ones are most vulnerable compared with the rest.
This infographic from Misumi Corporation takes a closer look at the 12 occupations identified in the study as most at risk while also providing additional data from O*NET OnLine and the U.S. Bureau of Labor Statistics. O*NET OnLine is a computer application that was developed in order to grant the public easy access to the O*NET database.
This database of over 900 occupations in the United States’ primary online resource for occupational information, containing data on hundreds of standardized descriptors, as well as those that are occupation-specific in nature.
The U.S. Bureau of Labor Statistics, on the other hand, is an agency that assesses various aspects of the U.S. labor sector, including labor market activity, price changes, working conditions, and productivity in the American economy. They are responsible for creating the Occupational Employment Statistics (OES) program, which provides yearly employment and wage figures about almost 800 occupations nationwide.
Let’s take a closer look at what the data from these various sources reveal.