SHAI: Shared Humanistic Artificial Intelligence A Semantic Intent Projection Framework for Stewardship Intelligence Architecture (Package)

Abstract This paper presents SHAI (Shared Humanistic Artificial Intelligence), an architectural framework for building AI systems grounded in Stewardship Intelligence rather than Exploratory Intelligence. The framework centers on Semantic Intent Projection (SIP), where meaning is treated as the canonical representation and language as an optional, gated projection. We introduce a six-layer architecture comprising sensors, world model, semantic canonicalization, collaborative interface, safety gate, and safety shell. The architecture embodies three core deployment requirements: Compatible (fits human environments), Collaborative (participates and defers), and Comfort (safety through care, not liability). We draw on the "Mum Model" of safety knowledge encoding to illustrate how real-world alignment has always worked: through compressed semantic transmission of causal knowledge, evaluated before action. This blueprint is offered as an architectural reference for implementers building domestic robotics, assisted care systems, and safe automation. Keywords: Semantic Intent Projection, Stewardship Intelligence, Safety Architecture, World Models, VL-JEPA, Domestic Robotics, Human-AI Collaboration, Alignment © 2026 John Richard Smith. All rights reserved except as expressly granted under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).