<![CDATA[The development of artificial intelligence (AI) has significantly transformed human resource management, particularly in recruitment and employee selection processes. AI-based recruitment systems utilize algorithms to enhance efficiency, speed, and objectivity in evaluating candidates. These systems allow organizations to process large volumes of applications more quickly and identify suitable candidates based on data-driven criteria. However, despite these advantages, the use of AI also presents challenges, especially concerning algorithm transparency and the potential for bias, which may compromise fairness in decision-making. Therefore, the role of human resource (HR) leaders becomes crucial in ensuring that AI systems are implemented in a transparent, accountable, and ethical manner. This study aims to analyze the application of algorithm transparency in AI-based recruitment and examine the role of HR leaders in overseeing and auditing these technologies to minimize algorithmic bias. The research adopts a Systematic Literature Review (SLR) approach by analyzing various scholarly articles related to AI in recruitment, algorithmic bias, and AI governance. The review process includes stages of identification, selection, evaluation, and synthesis of relevant literature from multiple scientific databases. The findings indicate that algorithm transparency is a key factor in developing fair and accountable recruitment systems. HR leaders play a strategic role through oversight mechanisms, algorithm audits, and the establishment of governance policies. Without proper supervision, AI systems risk perpetuating historical biases embedded in training data. Therefore, integrating AI with responsible HR leadership is essential to achieving transparent, fair, and sustainable recruitment practices.]]>
