Explainable AI in education: Fostering human oversight and shared responsibility

European Digital Education Hub (EDEH)
28/04/2025
This report by the European Digital Education Hub explores explainable artificial intelligence (XAI) in education, emphasizing its role in ensuring transparency, trust, and human oversight. It analyzes its impact, legal compliance, practical applications, and the necessary competencies for educators.
Explainable AI in education: Fostering human oversight and shared responsibility

The document "Explainable AI in education: Fostering human oversight and shared responsibility", published by the European Digital Education Hub (EDEH) in 2025, addresses explainable artificial intelligence (XAI) in education. XAI aims to ensure that AI systems explain their decisions clearly, fostering trust and accountability. Authored by experts, the report details how XAI enhances education by aligning with European ethical and legal values.

Divided into five chapters, the first introduces XAI, explaining concepts such as transparency, interpretability, explainability, and comprehensibility. It highlights that XAI sets AI apart from other programs due to its autonomy and complex results, requiring clear explanations. In education, XAI supports personalized learning and complies with EU ethical guidelines, such as the AI Act.

The second chapter examines XAI's compliance with the AI Act and GDPR, which demand transparency and data protection. Through fictional cases (automated grading, intelligent tutoring), it explores challenges in providing tailored explanations to students, educators, and developers, ensuring legal and educational compliance.

The third chapter examines XAI from the perspective of educational stakeholders, focusing on intelligent tutoring systems and lesson plan generators. These tools personalize learning but require clear explanations to build trust. It emphasizes collaboration among teachers, students, and authorities to ensure ethical explanations.

The fourth chapter proposes competencies for educators based on the UNESCO framework, covering primary to higher education. It includes understanding AI explanations, evaluating biases, and promoting critical thinking. Practical examples, such as offline activities for primary students or bias analysis projects, encourage AI literacy.

The final chapter concludes that XAI aligns AI with educational values, recommending training, transparent tools, and funding for open resources. It advocates for collaboration to combine technological innovation with human judgment, ensuring ethical and effective education.

In summary, this document provides a comprehensive guide on how XAI can transform education, ensuring that AI systems are transparent, ethical, and useful. It is a valuable tool for educators, developers, and policymakers seeking to responsibly implement AI in educational settings.

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