Fair4AIED 2026: Second International Workshop on Fairness in AI-assisted Decision-Making for Education

Education is being reshaped by AI: intelligent tutoring, risk detection, personalization, and unstructured learning with large language models are now commonplace. Ensuring fairness in educational AI remains difficult. Researchers already pursue auditing, mitigation, fairness-aware modeling, bias detection in datasets, and fairness metrics for learning settings—yet this work is often fragmented across subcommunities and only loosely connected to broader fairness ideas from the machine learning community. This workshop aims to bridge those gaps through interdisciplinary dialogue and exchange among researchers, practitioners, and policymakers. Through presentations and a panel, we share practical experience, surface open questions, and connect fairness ideas to actionable strategies for real educational systems—especially as generative AI evolves—advancing socio-technical approaches that go beyond purely technical fixes.