Study finds women judged more harshly for using AI

Research by Zehra Chatoo, a former Meta strategist and founder of the think tank Code For Good Now, reveals a significant gender bias in how AI-assisted job applications are perceived. Chatoo distributed identical AI-generated résumés under male and female names—James Clarke and Emily Clarke—and found reviewers judged Emily far more harshly. Reviewers questioned Emily’s trustworthiness 22% more often than James’s, doubting her competence with comments like ‘can’t even write a CV herself.’ The study also exposed generational differences: men from Generation Z, who grew up with AI, criticized Emily’s CV 3.5 times more than James’s. James received a 97% approval rating for his identical CV, while Emily’s approval stood at 76%. Chatoo noted that men using AI face scrutiny over effort, whereas women face accusations of lacking integrity, creating a perceived risk that discourages adoption. Harvard Business School Associate Professor Rembrand Koning documented a 25% gap in AI adoption between men and women, with women avoiding AI tools due to fear of backlash. A Caltech survey of 3,000 respondents in January found women were less confident AI would benefit their careers, further widening the adoption divide. Chatoo emphasized that perceived judgment is a major barrier, stating that addressing evaluation biases is key to closing the AI adoption gap. The findings suggest that societal perceptions of AI use differ sharply by gender, with women penalized more severely despite identical performance. This bias may contribute to slower AI integration among women, reinforcing existing workplace disparities. The study underscores the need for greater awareness of unconscious biases in AI-assisted professional settings.