Self-supervised Meta-Heuristic Mapping - a Framework for Adaptive Human-AI Governance

As artificial intelligence ecosystems become increasingly sophisticated and ubiquitous, there is a need to align their decisions and behavior with human values and objectives. We introduce a novel framework that maps behavioral and cultural "blueprints" to bridge personal and institutional realms. Enabling co-evolving human-AI understanding by integrating individual empowerment and organizational guidance through privacy-first dynamic meta-modeling. We demonstrate preservation of human agency via consent-driven analytics and systemic harmonization via an architecture personalizing human-AI interaction, by mapping a perception and societal’s multi-dimensional culture. We hope to generate individual and collective beneficial spark throughout our conclusions.