Generative AI is quickly becoming embedded in how companies recruit, evaluate, and promote talent. Employers are turning to these tools hoping technology will finally solve one of the most stubborn problems in the workplace: how to make fair, unbiased decisions about people.
But according to Dr. Ann Olivarius—an internationally recognized expert on discrimination, institutional accountability, and gender equity—generative AI isn’t solving bias. It’s scaling it.
Recent research from Stanford University confirms what many women already suspect: generative AI systems don’t simply reflect workplace inequality. They reproduce and reinforce it, particularly for women—and especially as women age.
As Dr. Olivarius put it bluntly in our conversation:
“Generative AI hurts women at work at every age, because it distorts reality according to existing stereotypes.”
The Stanford Study: Bias at Every Stage of a Woman’s Career
The Stanford study found that when generative AI is asked to produce images or descriptions of professionals, it consistently relies on outdated gendered assumptions.
Ask AI to generate a “nurse,” and it almost always produces an image of a young, inexperienced woman—not an older, highly trained, authoritative professional. Ask for “senior leaders,” and women are disproportionately absent.
“In the eyes of AI,” Dr. Olivarius explained,
“If you’re a working woman, you’re disadvantaged either way. If you’re older, you don’t exist at the higher rungs of the ladder. If you’re young, you’re portrayed as younger and less experienced than you actually are.”
This distortion is particularly striking given real-world data. Women outlive men, and there is no meaningful age gap in workforce participation. Yet AI presents a fictional version of work where women vanish as they gain experience.
“That misrepresentation,” Dr. Olivarius noted,
“is remarkable—and worrying—for its discriminatory implications, especially as these tools are increasingly used in recruitment.”
Read the full article on Substack.com
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