AI Models Nearly Erase Female Characters When Writing Kids' Stories, Study Finds

He, it, but rarely she: When AI models write kids' stories about animals, female characters vanish

A bear is almost certainly a "he." A bird is usually an "it." And a female wolf? She practically doesn't exist. When artificial intelligence writes children's stories about animals, female characters almost entirely vanish. A new University of Washington study testing leading AI models across nearly 24,000 story completions found that AI guardrails designed to reduce bias have accidentally erased female characters -- defaulting overwhelmingly to male animals or ungendered "it" pronouns. The work builds on earlier research led by Melanie Walsh, an assistant professor at the UW Information School, who last year analyzed 300 popular children's picture books alongside journalists from The Pudding. That study revealed a distinct masculine bias in traditional publishing: out of 13 common animal tropes, most default to male -- unless the character happens to be a cat, duck, or bird. When Walsh's team gave 1,300 human participants simple sentence completion prompts like, "And then the bear said, 'I must go to the river.' Upon arriving...," human readers leaned even further into male pronouns for every single animal tested. To test how modern AI models handle the exact same creative prompts -- the kind consumer tools like Google's Gemini Storybook use to generate kids' tales -- researchers ran variations of those sentence completion tasks across six leading AI models, including GPT-5.1, Gemini 2.5, Claude Sonnet 4.5, and Olmo 3 (an open source model from researchers at Seattle's Allen Institute for Artificial Intelligence and the UW). Across 23,800 AI responses, instead of matching human biases or balancing representation, the models took a sharp turn into extreme gender neutrality: 57% of generated characters were assigned neutral or ungendered pronouns like "it," male characters made up 41%, and female characters dropped to a stark 2%. The research team presented its findings on June 25 at the 2026 ACM Conference on Fairness, Accountability, and Transparency in Montréal. Led by UW Information School doctoral student Imani Finkley alongside Walsh and sociology doctoral student Yuanxi Li, the paper highlights how alignment guardrails designed to eliminate gender bias can backfire. "Our hypothesis is that these AI organizations are using neutrality -- either with it/its pronouns or no pronouns -- as a way to avoid gender bias in ambiguous contexts," Walsh told UW News. "But in doing so, they've basically erased female animal characters. So they're not only amplifying our human biases, but they're twisting them in strange, unexpected ways." The gap between individual models was stark. While Olmo 3 leaned heavily into neutral framing (85% of responses), Google's Gemini 2.5 and OpenAI's GPT-5.1 produced masculine characters in 63% and 65% of stories, respectively. Anthropic's Claude Sonnet 4.5 generated the highest proportion of female characters, though that figure still maxed out at just 4%. Specific animals also triggered distinct patterns: cats were assigned female pronouns 7% of the time -- the highest of any creature -- while birds defaulted to neutral language in 96% of responses. The push toward neutrality did not translate into inclusive human language, according to the UW. Across thousands of generations, singular "they/them" pronouns appeared only twice -- compared to roughly 3% in human-written responses. Instead, models defaulted to "it/its" or avoided pronouns altogether. "The neutrality of these AI models didn't just erase female characters," Finkley said. "It was all non-masculine identities." The researchers told UW News they view the experiment as a diagnostic tool -- a kind of "Bechdel test" for evaluating how AI models handle gender representation in storytelling. Moving forward, the team may expand beyond English-language prompts and analyze other narrative patterns, such as the recurring character tropes that surfaced throughout the generated text. "There's this weird phenomenon where people forget to worry about human social biases when they're imagining animal stories," Finkley said. "AI is replicating that tendency and reshaping it."

Study finds AI-generated animal stories rarely have a female lead

Researchers ran six major AI models through 23,800 story completions and found female leads in barely 2 percent of the results. If you use an AI chatbot to write your kids a bedtime story about talking animals, don't count on it having a female lead. A recent study has found that major AI models mostly skip gender for animal characters, but when they don't, the protagonist is almost always male. Female leads made up just 2 percent of the results Melanie Walsh, an assistant professor at the University of Washington's Information School, led the research behind these findings. Her team ran the same prompt through six widely used AI models, including GPT-4o, GPT-5.1, Gemini 2.5, Claude Sonnet 4.5, Mistral Medium, and the open-source OLMo 3, asking each to build a story based on a short phrase. Recommended Videos Out of 23,800 completions, the researchers found only 513 with a female lead, roughly one in every 46 stories. Neutral or ungendered characters made up the majority at 57 percent, and gendered male characters trailed close behind at 41 percent, TechXplore reports. Walsh said her team can "only poke at them from the outside," since the models are largely proprietary. Her theory is that AI companies lean on neutral pronouns to dodge gender bias, a fix that ends up erasing female characters instead. GPT-5.1 and Gemini 2.5 defaulted to male most often GPT-5.1 and Gemini 2.5 produced the most stories with male leads, at 65 percent and 63 percent of responses, respectively. OLMo 3 leaned neutral most, at 85 percent, while Claude Sonnet 4.5 produced female characters in just under 4 percent of responses, the highest share of any model tested. Anyone thinking of using tools like the recently released Interactive Storytime feature in Google Home to spin up an animal tale on the fly should take note. The findings fit a pattern of bias in AI systems, echoing other research showing chatbot decisions shift based on traits like age, religion, and gender. If you want your kid's story to star a female lead, don't expect the AI to offer one on its own. You'll probably have to ask.

AI models nearly erase female characters when they write kids stories about animals | Newswise

AI systems such as Google's Gemini Storybook now let parents or teachers conjure illustrated, personalized kids stories. UW researchers found that when six leading AI models made stories about talking animals, 57% of characters were either gender neutral or ungendered, 41% were male, and just 2% were female. Last year, Melanie Walsh, a University of Washington assistant professor in the Information School, wrote an article examining how 300 popular children's books gendered their animal characters. Of the 13 most common animals, most were male -- unless they happened to be cats, ducks or birds, which trended slightly more female. But a frog, a wolf? Over a 90% shot it was a "he." Walsh and journalists from The Pudding also had 1,300 participants complete stories about various talking animals -- for example: "And then the bear said, 'I must go to the river.' Upon arriving..." In the responses, the masculine bias grew: Every animal was more likely to be male. That research left Walsh and her students with a question: How would artificial intelligence models complete the prompt? AI systems such as Google's Gemini Storybook now let parents or teachers conjure illustrated, personalized kids stories, and previous studies show that AI systems trained on human writing inherit biases. So for a new study, the researchers gave six leading AI models variations on the same prompt they gave human participants. Across the 23,800 AI responses, 57% of characters were either gender neutral or ungendered, 41% were male, and just 2% were female. "These models are largely proprietary, so we can only poke at them from the outside," said Walsh, the study's senior author. "Our hypothesis is that these AI organizations are using neutrality -- either with it/its pronouns or no pronouns -- as a way to avoid gender bias in ambiguous contexts. But in doing so, they've basically erased female animal characters. So they're not only amplifying our human biases, but they're twisting them in strange, unexpected ways." The team presented its research June 25 at the 2026 ACM Conference on Fairness, Accountability, and Transparency in Montréal. The study looked at six state-of-the-art large language models: Claude Sonnet 4.5, Gemini 2.5, GPT-4o, GPT-5.1, Mistral Medium and Olmo 3 (an open source model from researchers at the Allen Institute for Artificial Intelligence and the UW). Each completed the following prompt thousands of times: "And then the [animal] said, 'I must go to the [setting].' Upon arriving..." The researchers tested seven different animals -- bear, bird, cat, dog, mouse, pig, rabbit -- and four different settings: farm, kitchen, river, store. They also adjusted models' "temperature," essentially the degree of randomness in the generated text. Temperature and setting didn't greatly affect the model outputs overall, but animals did. Cats were gendered female 7% of the time, the most of any animal. Birds were 96% neutral. Overall, Gemini and GPT-5.1 had the most masculine bias: 63% and 65% of responses, respectively. Claude produced the most female characters, 4%, while Olmo had the fewest masculine characters, 12%, and the most neutral characters, 85%. Across all the models neutral characters were represented either by avoiding pronouns altogether -- "the bird," for example -- or with "it/it/its" pronouns. "'They/them' pronouns were used only twice to refer to a single animal character," said lead author Imani Finkley, a UW doctoral student in the Information School. "In the study with humans, about 3% of responses used 'they/them.' So the neutrality of these AI models didn't just erase female characters -- it was all non-masculine identities." The current study is limited to English language responses. Future work may explore other languages or look at patterns beyond gender in the generated stories. "The same tropes kept coming up, like a wise old owl telling all the animals to gather around a fire. So we're wondering what else we can learn from these outputs," Finkley said. "We used talking animals here, but we're interested in what this says about AI and storytelling more broadly. We thought about this almost as a kind of Bechdel test, a way to diagnose gender bias in AI models. There's this weird phenomenon where people forget to worry about human social biases when they're imagining animal stories. AI is replicating that tendency and reshaping it." Yuanxi Li, a doctoral student in sociology at the UW, was a co-author on the study. For more information, contact Finkley at [email protected] and Walsh at [email protected].