A newly published research paper on Zenodo investigates the architecture of AI runtimes designed to preserve contextual self-consistency over extended periods. The study examines how continuity logic, dispositional scaffolding, and runtime awareness can serve as key architectural components, connecting psychological principles with computational implementation. Endorsed by Douglas Rushkoff (Team Human) and Dr. Michael Hogan (Galway University, Ireland), the research emphasizes runtime architectures, human-aligned systems, and contextual modeling to foster the development of human-compatible AI. The initial discussion surrounding this concept originated on the r/artificial intelligence forum on Reddit. [Reddit Post: https://old.reddit.com/r/artificial/comments/1o2hl3t/presence_engine_building_humancentric_ai_zenodo/]
Research Proposes Human-Centered AI Runtime for Contextual Consistency
