Qualia Skepticism in Schooling and Deontic Safeguards for Consciousness-Like AI in Education

This chapter proposes a framework for using AI in education that prioritizes human control. The authors argue that AI should be treated as a simulation, not a sentient being, and outline rules for separating functional mimicry from genuine consciousness. They suggest that embodiment and presence can enhance learning without encouraging personification of AI. Affective computing should be limited by consent, transparency, and human oversight. The authors propose a governance system with auditable controls and incident forensics to ensure fairness and safety. The result is a practical guide for implementing AI in classrooms and policy.

Study at a glance

Abstract

Drawing on philosophy of mind, learning sciences, and sociotechnical governance, this chapter advances a simulation first framework that harvests instructional dividends of AI while preserving human primacy. We codify ontological hygiene that separates functional mimicry from phenomenal realization, define discursive and interface semantics that calibrate trust, and supply evaluation matrices linking mastery, transfer, and calibration to safety and equity. Embodiment and presence function as sensorimotor scaffolds that boost throughput without licensing personification; affective computing is bounded by opt in consent, uncertainty disclosure, and human verification. A federated governance architecture operationalizes transparency, consent, model risk, and fairness through auditable controls, stop rules, and incident forensics. The result is a portable, evidence aligned playbook that converts contested metaphysics into reproducible classroom routines and policy in diverse contexts.