[论文解读] Beyond Tools: Generative AI as Epistemic Infrastructure in Education

Bodong Chen|ArXiv.org|Apr 9, 2025

Educational Strategies and Epistemologies被引用 3

一句话总结

本文主张将生成式AI视为教育中的认识论基础设施，重新配置认知主体性，提出包含三个分析条件的框架，并在课程设计与反馈中分析AI工具以揭示认识论替代及其伦理含义。

ABSTRACT

AI systems are increasingly embedded in practices where humans have traditionally exercised epistemic agency, the capacity to actively engage in knowledge formation and validation. This paper argues that understanding AI's impact on epistemic agency requires analyzing these systems as epistemic infrastructures rather than as neutral tools. Drawing on theories of technological mediation and distributed cognition, I advance a framework that foregrounds how AI systems reconfigure the conditions under which epistemic agency can be exercised. The framework specifies three analytical conditions: affordances for skilled epistemic actions, support for epistemic sensitivity, and implications for habit formation. I apply this framework to AI systems deployed in education, a domain where epistemic agency is both professionally essential and ethically significant. Analysis of AI lesson planning and feedback tools reveals patterns of epistemic substitution: while useful for efficiently handling teaching tasks, these systems perform cognitive operations without sustaining skilled epistemic actions, epistemic sensitivity, or virtuous habit formation, potentially preventing the cultivation of professional judgment that relies on these practices. The findings contribute to philosophical debates about AI and human agency by specifying mechanisms through which infrastructural embedding shapes epistemic possibilities, and offer design principles for AI systems that sustain rather than supplant human epistemic agency.

研究动机与目标

• 在教育中阐明认知主体性为何重要以及AI系统如何改变它。
• 提出分析框架，将AI视为知识实践的基础性中介。
• 将该框架应用于教育中的AI，聚焦于课程设计与反馈工具。
• 识别认识论替代的机制及其伦理含义。
• 提出设计原则以在AI增强的教育中维持人类认知主体性。

提出的方法

• 以技术中介理论与分布式认知理论为分析基础。
• 明确三项分析条件：熟练认识论行动的可及性、对认识论敏感性的支持、以及对习惯形成的影响。
• 将框架应用于教育中的AI使用，特别是课程设计与反馈工具。
• 诊断在AI处理认知任务而未维持熟练实践时出现的认识论替代模式。
• 提出促进持续的人类认识论主体性的设计原则。

实验结果

研究问题

• RQ1 AI系统在教育情境中如何重新配置可以行使认知主体性的条件？
• RQ2 AI工具通过什么机制替代或削弱教育中的熟练认识论行动、认识论敏感性和美德性习惯的形成？
• RQ3 哪些设计原则可以确保AI系统在教学中维持而非替代人类认知主体性？

主要发现

• AI系统能够通过执行认知运算来承担认识论劳动，但并未维持熟练的认识论行动。
• AI工具可能降低教育实践中的认识论敏感性和专业判断的机会。
• 在AI驱动的课程设计与反馈工作流中出现认识论替代的模式。
• 嵌入AI基础设施会改变教育者与学习者的认识论可能性与主体性条件。
• 设计原则可以引导AI系统支持而非取代人类认知主体性。