AIAI – AI-Enabled Academic Integrity

<p dir="ltr">This author’s note introduces and documents the conceptual origin of <b>AIAI – AI-Enabled Academic Integrity</b>, a new theoretical framework proposed by <b>Giacomo Visin</b> 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.</p><p dir="ltr">The framework is grounded in four pedagogical pillars:</p><ol><li><b>Ethical Access</b> – knowing when and why AI can be used responsibly;</li><li><b>Critical Competence</b> – evaluating and adapting AI output through reflection;</li><li><b>Reflexive Transparency</b> – disclosing and justifying AI use in academic work;</li><li><b>Educational Value</b> – integrating AI use as a skill aligned with learning outcomes.</li></ol><p dir="ltr">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.</p>