Artificial Intelligence’s Views of Women in Science Are More Biased Than Those of Humans

Since the 1960s, researchers have engaged in “Draw a Scientist” exercises where children are asked to draw a scientist. The results were then analyzed to determine the gender of those depicted in the drawing. Of 5,000 drawings collected over the first 11 years of the study, only 28 of them depicted a woman scientist, and all of these were drawn by girls. Not a single boy in the study drew a woman scientist. By 2018, about one-third of all scientists depicted in the drawings were determined to be women.

Lisa M.P. Munoz, a science writer, president of a science communication consulting firm, and author of Women in Science Now: Stories and Strategies for Achieving Equity (Columbia University Press, October 2023), has produced a similar experiment using artificial intelligence. She asked the AI-image generation model Stable Diffusion to draw 100 images of a ”photorealistic scientist.” Only 6 of 100 depicted what appeared to be a woman scientist. Most appeared older and White. Thus, the AI version of Draw a Scientist was more in line with the depictions of children in the 1960s than is the case today.

Munoz then did a similar experiment asking the AI software to draw a ”photorealistic engineer.” Only one of the 100 drawings generated depicted a woman.

Munoz concludes that “this data exposes the deep and persistent human biases that still plague public perceptions of STEM fields. While humans have made great strides in their pictures of scientists, AI is still decades behind. Our best defense is to keep elevating the stories of successful women scientists and engineers from the last several decades. Telling the stories of these women in STEM can help shape not only human perceptions of the fields but also — eventually — AI ones. Most importantly, these stories can help inspire and empower the next generation of innovators, working to make a difference in the world.”