The mission of the Lab is to identify a new generation of biases and “stereotype threat” in AI and help provide context and nuance to the conversation to mitigate those biases. Unmasking Coded Bias highlights AI and stereotype threat in a new generation of Black students and professionals. It questions how AI can reify and reconstruct bias based on our gender, age, race, and class and creates a new toolbox to be shared with industry leaders and policymakers.
“What we find in Amani’s field work is that even when the respondents may not yet have direct experience of bias in AI, the threat itself or what the social psychologist Claude Steele has named “stereotype threat” can profoundly affect our use of AI, threatening to undermine performance and participation, causing both emotional and intellectual reactions affecting our career choices,” says law professor Rangita de Silva de Alwis. “Amani’s work helps us recognize these algorithmic threats shared among a new generation of professionals and points us in the direction of new mitigation tools needed to address these threats.”
To assess Black professionals’ and students’ perceptions, Carter surveyed eighty-seven Black professionals and students coupled with an analysis of three-hundred and sixty online professional profiles with the goal of understanding how AI-powered platforms reflect, recreate, and reinforce anti-Black bias.
Read more at Penn Law News.