John Chi-Kin Lee;Chris Dede;Minjuan Wang;Xuefan Li
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Building Trust in AI Through Dialogues With Eastern Ethics: Toward Ethical Partnerships in Education
This article proposes a novel framework for ethical human–artificial intelligence (AI) partnerships in education by integrating Eastern ethics (with Chinese ethics as an example), intelligence augmentation, and agentic AI design. Moving beyond the dominant Western paradigm, the study draws from Confucian and Daoist principles—such as relational trust, coagency, and moral cultivation—to envision AI as an ethical partner, not just a tool. It addresses two key questions: How can trust in AI be cultivated in education? and when can AI be ethically considered a collaborator? The authors introduce a triadic model combining normative grounding, cognitive scaffolding, and system-level design, operationalized through culturally sensitive platforms, pedagogy, and ethical interaction. They also propose a three-tiered evaluation system: learner trust metrics, educator audits, and AI reflexivity protocols. This interdisciplinary synthesis provides a scalable culturally rooted pathway for designing AI systems that are pedagogically meaningful, ethically adaptive, and co-constructive—contributing to more equitable and morally resonant educational futures.
期刊介绍:
The IEEE Transactions on Learning Technologies covers all advances in learning technologies and their applications, including but not limited to the following topics: innovative online learning systems; intelligent tutors; educational games; simulation systems for education and training; collaborative learning tools; learning with mobile devices; wearable devices and interfaces for learning; personalized and adaptive learning systems; tools for formative and summative assessment; tools for learning analytics and educational data mining; ontologies for learning systems; standards and web services that support learning; authoring tools for learning materials; computer support for peer tutoring; learning via computer-mediated inquiry, field, and lab work; social learning techniques; social networks and infrastructures for learning and knowledge sharing; and creation and management of learning objects.