An Architectural Blueprint for Automated Intelligence (github.com)

Michael Barnes has released a comprehensive four-segment research series on AI architecture, now available as open-access preprints on Zenodo. Each segment includes an accessible Explanatory Companion and a formal Definition, addressing critical concepts in AI architecture, including "entity," "authority," and "continuity," which are currently underrepresented in AI vocabulary. The series consists of a Preamble outlining the foundational questions, followed by detailed architectural contributions: Automated Intelligence, Authorization Topology, and Identity Continuity. This research is significant for the AI/ML community as it establishes a formal framework for understanding automated systems through structural invariants and separation of authority from capability, rather than merely performance metrics. The proposed architectural definitions aim to foster more robust, reliable AI systems by standardizing essential concepts. By filing these definitions with the U.S. Copyright Office and making them publicly accessible, Barnes encourages transparency and further exploration within the field, paving the way for more insightful discussions on automated intelligence's future and governance.