Advancements in fields like robotics and artificial intelligence are making it possible to automate many types of jobs, bringing about significant changes in how work is done. Fresh research from Emerson College reveals that the impact of job automation isn’t the same for everyone and, if not addressed specifically, could lead to increased inequality.

This study delves into the potential risk of job displacement due to automation for over 1.4 million Americans across 385 different jobs. The results highlight that the intersection of race and gender plays a crucial role in determining the likelihood of automation affecting jobs.

Societal differences

For instance, when compared to white males, Black, Hispanic, and Native American males face higher risks of job automation by 5.8%, 3.9%, and 2.8%, respectively, when other factors are kept constant. On the other hand, Asian males have a slightly lower risk by 0.9%. White females have a 1.6% lower risk compared to white males, while Black females have a 1.1% lower risk.

When it comes to females, Hispanic females face a 0.5% higher risk, and Asian females have a 0.8% higher risk. Native American females, however, didn’t show a clear correlation with either higher or lower automation risk compared to white males. The study also identified age, disability, and country of birth as significant factors affecting job automation risk.

Education emerges as a key factor in minimizing the risks of automation, and addressing existing disparities in educational attainment is crucial. For instance, even though Black females initially show a 1.1% lower risk than white males, this changes significantly when education is considered.

Lower risk

A white male with a Bachelor’s degree, for example, has a 21.3% lower risk of job automation compared to a Black female with only a high school degree. This underscores the importance of addressing both automation risks and educational disparities to ensure a fair and equitable future of work.

“This study offers valuable insights into the complex interplay of race, gender, education, and other factors with automation risks in the American workforce. It highlights the importance of tackling discrimination and educational gaps based on race and gender,” the researchers conclude.

“It also emphasizes the need to adopt policies that ensure equitable opportunities and outcomes for all workers, especially those facing greater economic vulnerability and social exclusion due to this technological transformation.”