Ethical implications of AI-driven educational management systems on equity and social justice in sustainability education: A comprehensive review

This review paper focuses on the ethical aspects of artificial intelligence (AI)-powered EMSs in teaching sustainability, paying special attention to equity and social justice. As educational institutions adopt AI technologies to improve individualization, the efficiency of school administration, and resource allocation, the ethical implications of these uses, especially concerning algorithmic bias, privacy, transparency, and inequitable access, merit attention. This review integrates over 600 scholarly works published between 2010 and 2024 to demonstrate the evolution of the discourse in AI from predominantly assessing technological innovations to grappling with the ethical implications of inequity and injustice. The findings indicate that although AI technologies can lead to more individualized learning and resource efficiency, the ethical concerns are considerable, especially the concept of algorithmic bias and unequal access that can help increase the existing social disparities. As an illustration, the use of biased data can exclude vulnerable groups, which can ruin the goal of inclusivity of sustainability education. On the other hand, the review also identifies situations in which AI can provide inclusivity by serving the marginalized groups and making quality education more democratic. These results indicate that there is an obvious necessity to adopt AI practices that are more socially just, such as participatory design, transparent algorithms, and cohesive policy frameworks to address the problems of ethical risk. It is concluded that incorporating ethical concerns into the implementation of AI is necessary to establish equal, open, and socially fair and just educational systems that facilitate sustainable development objectives. Suggested future work includes addressing ethical AI frameworks in specific school contexts, longitudinal research, stakeholder strategies for closing the digital divide, and participatory design in high-risk AI applications to promote equitable and sustainable educational possibilities for AI. The review supports the idea of including ethical concerns in AI deployment to make sustainability education systems that are fair, open to everyone, and socially just.