While artificial intelligence (AI) and automation are poised to shake up the workforce by becoming skilled at performing human tasks, it has not been clear exactly how many–and which–human workers will be affected by the changes. And although AI is expected to master a variety of human tasks–351 scientists just offered a timeline for when human tasks will be completed by machines–the vast majority of US workers still do not fear that their entire job will be replaced by robots, according to the 2017 Randstad Employer Brand Research.

A new report, however, sheds light on which human workers will be most impacted by advances in automation and AI, by geographic region. Ball State University in Muncie, Indiana, recently released a report from its Center for Business and Economic Research making a bold prediction: Half of low-skilled US jobs are at risk of being replaced by automation.

The report examined how AI and automation will impact the workforce in America by mapping out two variables: Risk of automation, and offshore job losses. It found a “very strong regional concentration of potential automation and trade job losses facing American communities.”

According to the report, job losses will not be spread evenly across income– lower-wage, low-skilled workers are most at risk of losing work due to automation. In both cases–losses due to offshoring as well as losses due to AI and automation–rural communities are more at risk, with the report stating that “urban places tend to offer more resilience due to existing forces of agglomeration.”

It’s clear that AI and automation will force both employers and employees to change the way we think about work. TechRepublic’s Alison DeNisco has also reported on the effects of automation, from a geographical standpoint, looking at how US cities will be most impacted. “Low-wage cities such as Las Vegas, Orlando, and El Paso will be hit the hardest by job automation, according to a recent report from the Institute for Spatial Economic Analysis (ISEA),” DeNisco wrote. She went on to add that job losses are likely to be more drastic than previously predicted, and that the jobs that may take the greatest hits–due to advances in machine learning–are in truck driving, healthcare diagnostics, and education.

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