[Paper Review] Beyond Tools: Generative AI as Epistemic Infrastructure in Education

Bodong Chen|ArXiv.org|Apr 9, 2025

Educational Strategies and Epistemologies3 citations

TL;DR

The paper argues for viewing generative AI as epistemic infrastructure that reconfigures epistemic agency in education, proposes a framework with three analytical conditions, and analyzes AI tools in lesson planning and feedback to reveal epistemic substitution and its ethical implications.

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.

Motivation & Objective

• Motivate why epistemic agency matters in education and how AI systems alter it.
• Propose an analytical framework to study AI as infrastructural mediators of knowledge practices.
• Apply the framework to AI in education, focusing on lesson planning and feedback tools.
• Identify mechanisms of epistemic substitution and their ethical implications.
• Offer design principles to sustain human epistemic agency in AI-enhanced education.

Proposed method

• Ground the analysis in theories of technological mediation and distributed cognition.
• Specify three analytical conditions: affordances for skilled epistemic actions, support for epistemic sensitivity, and implications for habit formation.
• Apply the framework to AI use in education, particularly lesson planning and feedback tools.
• Diagnose patterns of epistemic substitution where AI handles cognitive tasks without sustaining skilled practices.
• Suggest design principles that promote sustained human epistemic agency.

Experimental results

Research questions

• RQ1 How do AI systems reconfigure the conditions under which epistemic agency can be exercised in educational settings?
• RQ2 What are the mechanisms by which AI tools substitute for or undermine skilled epistemic actions, epistemic sensitivity, and virtuous habit formation in education?
• RQ3 What design principles can ensure AI systems sustain rather than substitute human epistemic agency in teaching and learning contexts.

Key findings

• AI systems can subsume epistemic labor by performing cognitive operations without sustaining skilled epistemic actions.
• AI tools may reduce opportunities for epistemic sensitivity and professional judgment in educational practice.
• Patterns of epistemic substitution emerge in AI-enabled lesson planning and feedback workflows.
• Embedding AI infrastructure changes the conditions for epistemic possibility and agency for educators and learners.
• Design principles can guide AI systems to support rather than supplant human epistemic agency.