Generative AI in Values Education: Affordances, Ethical Risks and Implications for Teaching
DOI:
https://doi.org/10.70088/1e1ya973Keywords:
generative artificial intelligence, values education, moral education, moral interlocutor, teacher authorityAbstract
Generative artificial intelligence (GenAI) has become ordinary in university study, and students increasingly bring to it the questions about right and wrong that they once brought to teachers. Institutional guidance still treats GenAI mainly as a threat to academic integrity, leaving unsettled what kind of moral participant a language model can be. This article offers a theoretical account of that question. It characterises values education as a relational practice and specifies three conditions that any occupant of the educator's position must satisfy: answerability, exemplarity and address. It then distinguishes five affordances of GenAI, namely the generation of moral content, the simulation of perspectives, Socratic questioning, feedback on moral reasoning, and a tacit curriculum of machine authority, and analyses the risk internal to each. These risks fall into epistemic, relational, axiological and agentic families and are connected rather than independent. The central argument is that a generative model can be a moral interlocutor but not a values educator: it cannot be answerable for what it says, cannot exemplify a life, and cannot address a particular student. Four implications for teaching and institutional design follow.References
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Copyright (c) 2026 Ying Chen (Author)
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