Digital Empathy in AI for Social Good: A Systematic Review of Applications in Education and Libraries

Abstract

Artificial intelligence (AI) is increasingly shaping educational and library environments, promising efficiency, personalization, and accessibility. However, questions remain about whether these systems align with the values of equity, fairness, and care. Digital empathy the ability of technology to recognize, interpret, and respond appropriately to human emotions offers a way to humanize AI and ensure it functions as a tool for social good. This review synthesizes research on how empathy is conceptualized, operationalized, and integrated into AI systems designed for education and libraries. A systematic search across multiple databases identified 28 studies published between 2010 and 2024. These were analyzed to uncover common theories, design principles, and applications. The findings highlight that empathetic AI fosters inclusive learning environments, supports accessibility for marginalized groups, and improves user trust in digital systems. However, challenges persist, including algorithmic bias, limited ethical frameworks, and superficial applications of empathy. The review concludes that embedding empathy in AI requires interdisciplinary collaboration and consistent methodological tools. Future research should focus on long-term outcomes of empathetic AI and the development of guidelines for equitable, ethical design.