The Artificial Intelligence Field Is Too White and Too Male, Researchers Say

The artificial intelligence industry is facing a “diversity crisis,” researchers from the AI Now Institute said in a report released today, raising key questions about the direction of the field.

Women and people of color are deeply underrepresented, the report found, noting studies finding that about 80 percent of AI professors are men, while just 15 percent of AI research staff at Facebook and 10 percent at Google are women. People of color are also sidelined, making up only a fraction of staff at major tech companies. The result is a workforce frequently driven by white and male perspectives, building tools that often affect other groups of people. “This is not the diversity of people that are being affected by these systems,” AI Now Institute co-director Meredith Whittaker says.

Worse, plans to improve the problem by fixing the “pipeline” of potential job candidates has largely failed. “Despite many decades of ‘pipeline studies’ that assess the flow of diverse job candidates from school to industry, there has been no substantial progress in diversity in the AI industry,” the researchers write.

{snip}

The researchers make some suggestions for improving the problem. Companies, they say, could improve transparency by publishing more data on compensation, broken down by race and gender, and by publishing harassment and discrimination transparency reports.

{snip} Tools like a program that scans faces to determine sexuality, introduced in 2017, echo injustices of the past, the researchers write. {snip} s“We need to know that these systems are safe as well as fair,” AI Now Institute co-director Kate Crawford says.

Tech industry employees have taken a stand on some major AI issues, pressing their companies to drop or review the use of sensitive tools that could hurt vulnerable groups. {snip}

“The diversity crisis in AI is well-documented and wide-reaching,” the researchers conclude. “It can be seen in unequal workplaces throughout industry and in academia, in the disparities in hiring and promotion, in the AI technologies that reflect and amplify biased stereotypes, and in the resurfacing of biological determinism in automated systems.”

[Editor’s Note: The report Discriminating Systems: Gender, Race, and Power in AI, by Sarah Myers West, Meredith Whittaker, and Kate Crawford, is available as a free PDF here.]