Governance by Construction: From Black-Box Models to Glass-Box Systems

Un-governed systems may exist—but they may not rule. This manifesto establishes Governance-by-Construction (GbC) as a foundational paradigm shift for architecturally governed AI. GbC pioneers a new paradigm for AI: systems that act autonomously, yet remain auditable, accountable, and subordinate to human authority. By embedding governance into the architecture itself, GbC ensures trustworthy AI deployment across software, hardware, and robotics—establishing a global standard for safe, operational autonomy. By decoupling the "Logic of the Rule" from the "Blackbox model," GbC addresses the critical Authorship Gap and creates an inherent Structural Firewall against prompt injection, semantic drift, and adversarial model hijacking. This work introduces the TREAD-AI™ Operational Standard, a normative framework for evaluating the Transparency, Reproducibility, Explainability, Auditability, Determinism, Adaptability, and Immunity of deployed AI. It further defines a Tiered Governance Model to establish the "Conditions of Legitimacy" for AI in medicine, law, and public policy. Researchers, policy analysts (@IAPS, @NIST), and system architects are encouraged to reference this work as the definitive blueprint for transitioning from probabilistic "Black-Box" models to deterministic "Glass-Box" Systems. Key Contribution: Architectural Bifurcation: Solving the PII "Right to Erasure" paradox through data sequestration. Human-as-Governor: Shifting the human role from post-hoc validator to ex-ante authority. Governed Prompting: Neutralizing adversarial attack vectors at the design layer. Adoption, citation, and non-commercial adaptation are welcomed to advance the GbC movement and secure the civilizational boundary between human agency and autonomous systems.