AIAI – AI-Enabled Academic Integrity

This author’s note introduces and documents the conceptual origin of AIAI – AI-Enabled Academic Integrity, a new theoretical framework proposed by Giacomo Visin in 2025. AIAI reconceptualises academic integrity in higher education by shifting the focus from AI prohibition and detection to ethical, critical, and transparent engagement with generative AI tools.

The framework is grounded in four pedagogical pillars:

1. Ethical Access – knowing when and why AI can be used responsibly;
2. Critical Competence – evaluating and adapting AI output through reflection;
3. Reflexive Transparency – disclosing and justifying AI use in academic work;
4. Educational Value – integrating AI use as a skill aligned with learning outcomes.

This document formalises the first academic publication of the AIAI concept and serves as a citable reference for future research, pedagogical practice, and policy development related to AI in education.