Designing technology around the human body can be tricky. For years, researchers have relied on gold standards to implement safety measures and accurate representations of humans. 

But what happens when the algorithms behind artificial intelligence are off, built on cadavers, or only represent the body of traditionally male figures? 

New research by University of Michigan assistant professor Abigail Jacobs discusses the dangers of these “flawed” assumptions, what the AI systems are built on and how to prevent future mistakes. 

Jacobs’ research, “The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology” was featured on IEEE Spectrum, a technology magazine. 

“We dug into these so-called gold standards being used for all kinds of studies and designs, and many of them had errors or were focused on a very particular type of body,” she says. “We want engineers to be aware of how these social aspects become coded into the technical—hidden in mathematical models that seem objective or infrastructural.”

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Read “AI Is Being Built on Dated, Flawed Motion-Capture Data” on IEEE Spectrum. 

See Jacobs’ study, “The Cadaver in the Machine: The Social Practices of Measurement and Validation in Motion Capture Technology” on arXiv.  

Learn more about Abigail Jacobs by visiting her UMSI faculty profile. 

— Noor Hindi, UMSI public relations specialist