The deployment of AI technologies in information retrieval systems brings significant opportunities for enhancing information retrieval and user experience. However, it also raises critical ethical considerations, including issues of transparency, data privacy, algorithmic bias, and accessibility. This study examines these ethical challenges, exploring their implications for both users and library systems. By analyzing case studies and existing frameworks, it identifies best practices for ensuring ethical AI implementation, such as promoting transparency in algorithmic decision-making, safeguarding user data, and designing inclusive systems for diverse user groups. The findings provide actionable recommendations for developers, librarians, and policymakers to balance technological advancement with ethical responsibility, fostering trust and equity in AI-driven library systems.
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