Bidirectional Human-AI Alignment in Education for Trustworthy Learning Environments

✐ ✐ “main” — 2025/12/29 — 1:13 — page 1 — #1 ✐ ✐ ✐ ✐ ✐ ✐ Chapter 1 Bidirectional Human–AI Alignment in Education for Trustworthy Learning Environments Hua Shen, NYU Shanghai, New York University Abstract Artificial intelligence (AI) is transforming education, offering unprecedented opportunities to personalize learning, enhance assessment, and support educa- tors. 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. Keywords: AI for Education, Human-AI Alignment, Evolving AI Roles in Education 1. Introduction Artificial intelligence (AI) is rapidly becoming woven into the fabric of education [1, 2]. From adaptive learning platforms and automated assessment tools to intelligent tutoring systems and predictive analytics, AI technologies promise to reshape how students learn, how teachers teach, and how schools make decisions [3, 4]. These innovations hold the potential to address long- standing challenges—personalizing learning at scale, reducing administrative burdens, and generating timely insights to support both teaching and student progress. Yet alongside this promise lie significant risks. Without deliberate attention to ethics, inclusivity, and transparency, AI systems may amplify biases, erode student privacy, or diminish teacher autonomy. They can also disrupt the delicate social dynamics of classrooms, altering power relationships between students, 1 arXiv:2512.21552v1 [cs.CY] 25 Dec 2025 ✐ ✐ “main” — 2025/12/29 — 1:13 — page 2 — #2 ✐ ✐ ✐ ✐ ✐ ✐ Bidirectional Human–AI Alignment in Education for Trustworthy Learning Environments educators, and technology providers. In this sense, the introduction of AI into education is not merely a technical shift but a cultural and normative one [5]. Building on the “Bidirectional Human-AI Alignment” framework [6, 7], this chapter proposes a bidirectional approach to human–AI alignment in education—one that treats alignment not as a one-way imposition of human values onto machines, but as a dynamic process in which both humans and AI systems co-adapt. On one hand, AI must be designed and deployed to reflect shared educational values such as equity, trust, and student agency [8, 10]. On the other hand, educators and learners must also develop new literacies, skills, and mindsets to engage productively and critically with AI systems [9]. Only through this reciprocal relationship can AI enhance, rather than undermine, the human goals of learning. The chapter unfolds in five major parts: • What Needs to Be Aligned – We begin by unpacking the foundations of alignment in education: shared values and ethical principles, clear learning goals, and well-defined interaction norms between humans and AI systems. • Pathways to Achieving Alignment – We explore technical design strategies, ethical and legal frameworks, and mechanisms for continuous feedback and adaptation that sustain alignment over time. • Evolving Roles of AI in Education – We trace AI’s trajectory from support tool to collaborative partner, focusing on adaptive learning, personalization, and enhanced assessment. • Impacts of AI on the Educational Ecosystem – We examine how AI affects teacher roles, student agency, classroom safety, and the broader capacity to interpret and critique algorithmic decisions. • Moving Forward: Actions and Recommendations – We conclude with practical steps for policymakers, educators, and developers, and identify key areas for future research and innovation. By weaving these threads together, the chapter aims to provide a roadmap for designing trustworthy learning environments where human and artificial agents work in concert. Our goal is not simply to safeguard against harm, but to actively cultivate a culture of mutual trust, transparency, and shared responsibility—ensuring that AI enhances the human dimensions of education rather than eroding them. 2. What Needs to Be Aligned? The promise of AI in education hinges on alignment—ensuring that technolo- gies support, rather than distort, the aims of teaching and learning. Alignment is not a single dimension; it is a multi-la

This content is AI-processed based on open access ArXiv data.