Open Autonomous intelligence initiative
Conceptual update:
- Simplified PMF incorporated in the Structural Intelligence Framework
- Entity is the common managed-object base class.
- Host, Sensor, Signal, Event, Knowledge, Agent, Interface, and Log are Entity subclasses..
Open Autonomous Intelligence Initiative
Open object-oriented models for accountable AuI
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Open SGI MVP — Aging-in-Place Event Recognition Use Case
This document defines the primary use case for the Open SGI Minimum Viable Product (MVP). This document exists to: ground Open SGI development in human reality prevent scope creep into surveillance or diagnosis guide subclassing of OAII Base Model objects support transparent review by collaborators
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OAII Base Model v0.1 — Index
This index provides a consolidated view of the OAII Base Model v0.1 object set, their roles, and their relationships. The Base Model defines an open, object‑oriented, edge‑primary architecture for autonomous intelligence systems, with aging‑in‑place event recognition used as a reference domain. The Base Model is normative at the object level and non‑normative at the implementation…
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OAII Base Model — Interface v0.1
The Interface object represents a controlled interaction surface through which Agents and systems communicate with humans or other systems within a World. Interfaces enable assistance, notifications, consent, and configuration while enforcing Policy constraints and privacy boundaries. Interfaces are where autonomy meets human oversight.
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OAII Base Model — Log v0.1
The Log object provides an explicit, structured, and privacy-aware record of system activity within a World. Logs enable auditability, accountability, debugging, and review without requiring continuous data retention or surveillance. In the OAII Base Model, Logs are first-class objects designed to support trust, not monitoring.
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World-Scoped Intelligence: Why Context Boundaries Are Essential for Ethical AI
One of the most common sources of harm in AI systems is not malicious intent, poor data, or even flawed models. It is context leakage. When AI systems fail, they often fail because observations, interpretations, or rules escape the context in which they were valid. Meaning is treated as portable when it is not. This…
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Edge Autonomy and Human Dignity: Why Local Intelligence Matters in the Home
When discussions about AI architecture turn to the edge, they often focus on latency, bandwidth, or reliability. Those considerations matter — but in the home, they are secondary. In domestic settings, where intelligence runs is a question of dignity. Aging‑in‑place systems are not abstract infrastructure. They inhabit private spaces, observe intimate routines, and influence moments…
Open Autonomous Intelligence Initiative 