AI Governance in Education: Justice, Power, Accountability, Epistemic Equity, Institutional Responsibility, and Collective Well-Being

Artificial intelligence (AI) is rapidly reshaping education across diverse educational settings. AI systems now support teaching, learning, assessment, research, decision-making, and institutional operations. These developments are often discussed in terms of efficiency, innovation, and improved access. However, AI is not socially or economically neutral. Its design and use can reflect existing power structures, institutional interests, dominant knowledge systems, and social inequalities. The growing use of AI in academic tasks also raises questions about human agency, intellectual ownership, academic integrity, and meaningful learning. These concerns call for AI governance that goes beyond technical performance and regulatory compliance to advance restorative, distributive, procedural, and collective justice across educational communities. A justice-centered approach can examine who benefits from AI, whose knowledge is represented, who participates in decisions, what ethical boundaries should guide its use, and how transparency, disclosure, explainability, consent where relevant, and human oversight can support responsible AI use.This Research Topic aims to advance a justice-centered understanding of AI governance across diverse educational settings. It moves beyond questions of whether AI is effective or efficient to examine the values, power relations, responsibilities, and ethical boundaries that shape its development and use. Particular attention will be given to power, accountability, epistemic equity, human agency, and collective well-being.The Research Topic seeks scholarship that examines how AI governance can promote meaningful participation and address unequal access to AI and its benefits. It also encourages attention to whose knowledge, languages, cultures, and ways of knowing are represented or marginalized by AI systems. As AI becomes a pedagogical tool, governance must also consider how students and instructors can use it while maintaining intellectual agency, academic integrity, and meaningful engagement in learning. This includes questions of AI-use disclosure, explainability, human oversight, and consent where relevant. Contributions may also examine how responsibilities should be shared among students, instructors, institutions, developers, and policymakers. The broader goal is to support AI governance approaches that place justice, responsibility, human flourishing, and educational well-being alongside technological advancement.This Research Topic welcomes critical, empirical, theoretical, and interdisciplinary research on justice-centered AI governance across diverse educational settings. The focus is not on AI adoption, classroom effectiveness, technological readiness, or curriculum integration alone. Instead, contributions should examine how the design, governance, and use of AI relate to one or more of the following areas:1. Power and accountability: How power is created, distributed, and challenged through AI in education. Contributions may examine algorithmic power, transparency, AI-use disclosure, explainability, human oversight, responsibility, institutional governance, participation in AI-related decisions, and ways of holding institutions, developers, and other actors accountable.2. Epistemic and social equity: How AI systems represent, privilege, or marginalize knowledge, languages, cultures, and ways of knowing. Contributions may address knowledge hierarchies, linguistic and cultural diversity, accessibility, inclusion, unequal access to AI, and the fair distribution of opportunities and benefits across educational communities.3. Justice and institutional responsibility: How educational institutions can develop and implement AI policies grounded in fairness, responsibility, and meaningful participation. Contributions may examine institutional policy, consent where relevant, commercialization, resource distribution, labor implications, democratic governance, stakeholder participation, and responsibilities for addressing unequal benefits, risks, and harms.4. Collective well-being: How AI governance can consider the well-being of individuals and educational communities rather than efficiency or individual benefit alone. Contributions may explore human flourishing, educational relationships, trust, belonging, shared responsibility, community interests, and the broader social consequences of AI use in education.5. AI as a pedagogical tool: How AI use in academic tasks can be governed while protecting human agency, academic integrity, and meaningful learning. Contributions may examine intellectual ownership, active engagement, appropriate disclosure of AI use, ethical boundaries between AI assistance and inappropriate substitution of human work, and the responsibilities of students, instructors, institutions, and policymakers in establishing and implementing these boundaries.We welcome original research, reviews, conceptual and theoretical papers, policy analyses, perspectives, and comparative studies. Topic editors: Richard Peter Bailey, Toktam Khatibi, Miguel Casar, Olimpius Istrate Source: https://www.frontiersin.org/research-topics/86665/ai-governance-in-education-justice-power-accountability-epistemic-equity-institutional-responsibility-and-collective-well-being