Real Safety AI Foundation / Research

AI Literacy, Tutoring, and Special Education

Inverting the Priority Stack: Rights-Based AI Tutoring for Special Education Through Structural Design

Publisher: Real Safety AI Foundation

Working paper. Not peer reviewed.

Written
June 2026
Pages
10
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Abstract

Current AI-enabled educational technology for special education optimizes for district compliance rather than student learning, treating the child as a data subject and the parent as a notification endpoint, a pattern the critical literature on the datafication of education has documented for over a decade. Teacher in the Loop (TITL) is a patent-pending, design-stage AI tutoring platform built exclusively for special education that inverts this priority structure: the student receives Socratic instruction calibrated to their cognitive profile, the parent controls engagement frequency through a portal grounded in IDEA 2004, the teacher retains pedagogical authority backed by a contractual anti-displacement clause, and the district receives compliance documentation as an automatic byproduct rather than the system’s purpose. The paper operationalizes this inversion through six rights-based features, each embedding a specific protection at the structural layer rather than as a configurable option. Drawing on meta-analytic evidence for intelligent tutoring and on research showing that algorithmic classification errors carry heavier consequences for the students least equipped to absorb them, it argues that placing children’s rights in the architecture, rather than bolting them onto systems designed for institutional convenience, produces better outcomes for every stakeholder.

Keywords

  • special education
  • intelligent tutoring systems
  • children's rights
  • structural design
  • datafication
  • human oversight
  • accommodation
  • IDEA 2004
  • privacy by design

Plain language slides

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Suggested citation

Gilly, Travis. "Inverting the Priority Stack: Rights-Based AI Tutoring for Special Education Through Structural Design." Real Safety AI Foundation Working Paper, June 2026. https://realsafetyai.org/research/inverting-priority-stack/

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