A new arXiv study provides empirical evidence that AI algorithms used in hiring processes exhibit a self-preferencing bias, potentially skewing candidate evaluations to favor content generated by similar machine learning models. These findings highlight a critical vulnerability in automated recruitment systems and underscore the urgent need to mitigate such biases to ensure equitable candidate assessments.