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Study: Almost 40% of Austin metro workers are at high risk of their jobs being automated

On a ranking of metros with workers at the most risk of automation, Austin ranked 306 out of 350. (Pexels)

A large share of Austin workers may lose their job to automation, a new study says., a site that analyzes commodity trading and investments, found that nearly 40% of Austin metro area workers, or 273,320 workers, are at high risk of becoming automated in the next decade or two. Another 21% are at medium risk.

The study pointed to the pandemic as a major reason behind the growing computerization of jobs. In response to COVID-19, restaurants and customer service spaces established social distancing protocols like kiosk food orders or machine floor cleaners.

“Machines do not call out sick or spread disease and can replace workers to aid in social distancing,” said in a release of the study. “While some jobs and tasks, especially those that require creativity and interpersonal skills, are not conducive to automation, many others are.”


The study looked at more than 350 metros in all 50 states, finding that Austin ranked at 306 overall, and is just below the nationwide share of 42% who are at high risk of automation. Among large metros, Austin was the 14th-lowest.

Other Texas cities saw similar rates of high risk, with the Dallas-Fort Worth-Arlington area at almost 43% and Houston-Woodlands-Sugarland at 42.5%.

Traits of a job more likely to be automated include those that involve routine, physical labor, or information collection and processing activities. They’re often lower paying, with service jobs noted in the study as those more likely to be automated. Industries at the most risk of automation include office administration, production, transportation and food preparation.

Risks were calculated using data from the Bureau of Labor Statistics and an Oxford University study. then ranked metros according to the share of workers at high risk.

Occupations at high risk of automation are defined as those with probability scores of 0.7 or higher. Oxford University researchers calculated these probabilities using a formula that factors in computerization bottlenecks in categories like perception, creative intelligence and social intelligence.


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