Explainable AI in education: A multi-stakeholder approach to transparency and ethical practice

Abstract

Integrating AI into education makes explainability an ethical imperative. This analysis examines competency requirements for 5 stakeholder groups – learners, educators, parents, system leaders, and developers – while evaluating capacity-building interventions, participatory design, and multi-stakeholder governance frameworks. Technical disclosure proves insufficient; sustainable implementation demands distributed responsibility through professional development, human-centered design, and collaborative governance. Three critical challenges persist: cognitive overload from complex explanations, equity gaps in interpretive capabilities, and automation bias fostering over-reliance. Effective educational AI adoption requires integrating participatory design with institutional governance to establish shared accountability across the educational ecosystem.

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