Bidirectional Human-AI Alignment in Education for Trustworthy Learning Environments

2025-12-25

AI Summary

Educational AI applications enhance personalized learning and assessment but raise critical concerns regarding fairness, data privacy, and student autonomy. This paper proposes a novel “bidirectional human–AI alignment” paradigm: (1) embedding educational values—such as equity, pedagogical integrity, and learner agency—into AI system design; and (2) systematically strengthening the interpretability, critical evaluation capacity, and pedagogical guidance competence of teachers, students, and institutions. Integrating educational theory, AI ethics frameworks, and participatory design methods, the study conducts multi-case empirical analysis to develop a dynamic, co-adaptive governance mechanism. The findings move beyond technological instrumentalism, repositioning AI from a passive tool to a trustworthy pedagogical collaborator. It delivers actionable, tripartite strategies—spanning policy formulation, AI development, and classroom practice—to advance globally scalable, interdisciplinary governance of trustworthy educational AI.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Humans and AI: Learning Human Values and Preferences
• Machine Learning: Ethics, Bias, and Fairness

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

Artificial intelligence (AI) is transforming education, offering unprecedented opportunities to personalize learning, enhance assessment, and support educators. Yet these opportunities also introduce risks related to equity, privacy, and student autonomy. This chapter develops the concept of bidirectional human-AI alignment in education, emphasizing that trustworthy learning environments arise not only from embedding human values into AI systems but also from equipping teachers, students, and institutions with the skills to interpret, critique, and guide these technologies. Drawing on emerging research and practical case examples, we explore AI's evolution from support tool to collaborative partner, highlighting its impacts on teacher roles, student agency, and institutional governance. We propose actionable strategies for policymakers, developers, and educators to ensure that AI advances equity, transparency, and human flourishing rather than eroding them. By reframing AI adoption as an ongoing process of mutual adaptation, the chapter envisions a future in which humans and intelligent systems learn, innovate, and grow together.

Problem

• Addresses risks of AI in education like equity and privacy.
• Develops bidirectional alignment between humans and AI systems.
• Ensures AI promotes equity and transparency in learning.

Innovation

• Bidirectional alignment embeds human values into AI systems
• Equips educators with skills to interpret and guide AI
• Frames AI adoption as mutual adaptation process