In her article on “AI’s Diversity Problem,” (Boston Globe, February 8, 2019), Swathi Meenakshi Sadagopan interviewed CS graduate student and recent inductee into the next class of Junior Fellows at Harvard’s Society of Fellows, REDIET ABEBE, to ask about the way AI may be insufficiently developed to handle assessments of race and gender: “there are limits to what AI can do. If it’s going to be truly effective, not to mention fair, it’s got to have a steady human hand—a programmer who can spot problems and make the necessary adjustments.”As Sadagopan writes: “Much of the criticism leveled at artificial intelligence focuses on the bias that’s too often baked into its data […].” However, another pressing issue is “a lack of diversity in the AI teams building and overseeing systems. Anyone watching the field closely can see it has a diversity problem.”

Sadagopan continues: “Rediet Abebe, a Cornell University PhD student who has been active in the push to diversify AI, says broader representation could head off unintended bias in AI.” As Abebe told Sadagopan:“[In AI applications] discrimination rarely happens through malice. A lot of the time it happens through neglect.”

Sadagopan emphasizes a shift in the culture addressing diversity in Computer Science: “Several grassroots groups fostering inclusivity have emerged, too, including Black in AI, co-founded by Abebe and Timnit Gebru, a Google AI research scientist. From its beginnings as an email list, Black in AI has grown to more than 1,000 members in under two years and serves to amplify the research conducted by black researchers […] Abebe recounts asking the admissions committee at Cornell University why there was only one other black student in her computer science graduate program. ‘We don’t get enough applications from black students,’ was the response she got […].”

As Sadagopan reports: “In 2017, Abebe mentored 15 graduate school applicants and co-launched a program within the Black in AI community to match more than 200 students with over 80 mentors. In 2018, the computer science department at Cornell tripled the number of black applicants over the previous year, thanks in part to this effort.”

Despite these points of significant progress, Sadagopan says “still, some activists say there are some AI systems that even the most diverse machine learning team can’t fix. […] ‘Technology impacts reality,’ notes Os Keyes, University of Washington PhD student and transgender researcher, ‘Inclusive and diverse hiring is necessary, but it is also insufficient.’"

Read the entire article here.