Supported by Dr. Michael Hogan (Galway University, Ireland)
The Presence Engine™
Thesis introduces Human-Centric AIX™ (AI Experience), a new category of emotional AI infrastructure that prioritizes presence, trust, and dignity over productivity and data extraction. This white paper outlines the core problem of depersonalized AI systems, presents the theory of change for AX, and integrates insights from critical thinking dispositions research. By framing emotional presence as foundational infrastructure, Presence Engine™ establishes a pathway for ethical, scalable, and human-aligned AI systems.
Abstract
Prevailing AI systems optimize for retention and engagement. They flatten context, mimic affect, and treat people as data flows rather than subjects with dignity.
This monograph advances Presence Engine™ as a framework for AIX (AI Experience): privacy-first, tone-aware, and oriented toward scaffolding enduring human dispositions—reflection, perseverance, attentiveness, and open-mindedness. We articulate design axioms, a non-commercial conceptual architecture, an integrated review of relevant scholarship, concrete empirical methods, and five field cases that illustrate presence versus extraction in practice. The framework is instantiated in Neve™, a living runtime that demonstrates how presence can be operationalized, measured, and governed.