A new study using AI-generated identical resumes found reviewers were more likely to question the credibility and competence of a female applicant when both candidates used AI assistance. The experiment created matched résumés with a single naming difference—Emily Clarke versus James Clarke—and circulated them to reviewer groups with an AI-use disclosure. Results reported that Emily’s résumé was associated with higher rates of trust doubt and more frequent concerns about competence, while James’s AI usage was more readily framed as legitimate help. The study’s authors connect the findings to wider concerns about an AI gender gap and risk-interpretation differences. The work also cites related research on adoption behavior and how perceived expertise penalties can shape whether users—especially women—avoid AI tools in professional contexts.