Study finds women judged more harshly for using AI

Women are significantly penalised for using artificial intelligence to create job application materials, while men who use identical AI assistance receive forgiveness and understanding, according to research by Zehra Chatoo, a former Meta strategist and founder of the think tank Code For Good Now.

Chatoo distributed identical AI-generated résumés under two candidate names: Emily Clarke and James Clarke. Reviewers said the identical names were AI-assisted. The results revealed a stark gender double standard.

Reviewers questioned Emily's trustworthiness 22% more often than James's. Her competence was doubted twice as frequently, with feedback suggesting she "can't even write a CV herself" and questioning whether she possessed job skills.

James was subjected to a completely different approach. "He just needed a bit of help putting it together," the reviewers reported.

This reveals an underlying bias in the workforce. "When men use AI, we question their effort. When women use AI, we question their integrity. That difference changes the perceived risk of using AI," Chatoo explained.

The generational gap was evident. Men from Generation Z, who have grown up around AI, viewed Emily’s CV negatively 3.5 times more often than James’s. James’s identical CV earned a 97% approval rating, while Emily’s got a 76% approval rating for the same content.

Harvard Business School Associate Professor Rembrand Koning documented a 25% adoption gap between men and women using AI for work. Women, concerned about perception and potential accusations of cheating, remain more risk-averse.

According to the Caltech survey conducted in January involving 3,000 respondents, women were significantly less confident that the advantages of AI would outweigh the disadvantages, and their belief that AI would help advance their careers was also weaker.

The findings have helped to determine one of the significant obstacles in bridging the AI adoption gap, as Chatoo mentioned, "If people believe they will be judged more harshly for using AI, they are less likely to adopt it, regardless of their capability. Closing the AI adoption gap means addressing not just how people use AI but how that use is evaluated."