Stanford historian and feminist scholar Rachel Jean-Baptiste argues that as artificial intelligence becomes increasingly embedded in everyday systems, it also inherits the blind spots of the data used to train it—particularly around gender, race, and lived experience. Drawing on her work in global history and feminist theory, she warns that many AI datasets still flatten or exclude the complexities of identity, which risks reproducing bias at scale. In collaboration with computer science faculty, she is advancing “gender literacy” as a core competency for students across disciplines, including engineering, so future technologies can better reflect social realities rather than distort them. Her broader goal is to position institutions like Stanford at the forefront of interdisciplinary research that ensures AI systems are not only technically advanced but also historically and ethically informed.
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https://humsci.stanford.edu/feature/bringing-global-histories-gender-race-and-citizenship-ai-age
