Code-review tools increasingly display whether an author used AI when preparing pull requests. Recent studies report that AI disclosure makes reviewers rate otherwise identical work as less competent, with the penalty falling hardest on already-marginalized authors. In a within-subjects experiment in an AI-normalized organization, 447 software engineers each reviewed the same four code snippets under an AI-use disclosure embedded in the commit message and author-seniority labels. AI disclosure did not bias perceptions of code effectiveness or author competence, whereas a seniority label significantly biased both. Together, these findings show no detected penalty for disclosed AI use in this setting, while confirming that the author information shown in code review can still bias evaluations.<\/p>\n","protected":false},"excerpt":{"rendered":"
Code-review tools increasingly display whether an author used AI when preparing pull requests. Recent studies report that AI disclosure makes reviewers rate otherwise identical work as less competent, with the penalty falling hardest on already-marginalized authors. 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