During EDUCAUSE 2021, higher education is charged with recognizing--and working to change--the biases that impact technological innovation

With innovation comes inequity


During EDUCAUSE 2021, higher education is charged with recognizing--and working to change--the biases that impact technological innovation

Who do we listen to in higher education, and how we can work against daily–but critical–behind-the-scenes patterns that perpetuate racism and inequity in schools, communities, the workplace, and technological innovation?

From a young age, we’re fed the idea that a technology-driven utopian society will make our lives more efficient, more fair, and will save us, said Ruha Benjamin, professor of African American Studies at Princeton University and author of People’s Science: Bodies and Rights on the Stem Cell Frontier, during the opening keynote of EDUCAUSE’s annual conference. But coded inequities perpetuate harmful patterns in our society.

Benjamin has studied the social dimensions of science, technology, and medicine for over fifteen years and speaks widely on issues of innovation, equity, health, and justice in the U.S. and globally.

Technology shapes us, but behind that technology are humans with their own biases, interests, assumptions, and ideas. These become encoded in our sociotechnical structures.

“As it stands today, there’s a very small sliver of humanity whose imagination is getting encoded into our digital world,” Benjamin said. “Part of the work I see us in higher education responsible for is to broaden whose imagination, values, and needs become encoded in those structures.”

Efforts must be made to democratize not just access to technology, but the design of technology. Higher education, Benjamin added, is very much ground zero when it comes to this responsibility.

Examples of limited perspectives in technology are plentiful. An image search for professional hairstyles pulls up images of white women, while an image search for unprofessional hairstyles displays Black women with natural hair. Data from an AI hiring tool that vets job applicants shows that applicants with names traditionally associated with a white person received 50 percent more callbacks.

Laura Ascione