Governed Decision Intelligence (GDI)
Copyright © 2026 Mark Julius Banasihan

This repository contains the Governed Decision Intelligence (GDI) open specification
and reference implementation for decision-layer governance of AI systems.

GDI evolved from the RGDS (Regulated Gate Decision Support) framework,
a biopharma reference implementation developed for IND and BLA submission governance.

Prior art repositories:
- github.com/mj3b/rgds (biopharma reference implementation, 170+ commits)
- github.com/mj3b/rgds-ai-governance (AI governance covenants)

GDI is provided as an open specification for research, implementation,
and extension by the AI governance community.

It does not constitute regulatory advice, compliance guidance, or legal opinion.
Organizations implementing GDI are solely responsible for ensuring compliance
with all applicable regulatory requirements in their jurisdictions.

THIRD-PARTY REFERENCES:

This work references published research, regulatory guidance, and governance
frameworks. All such references remain the property of their respective
copyright holders and are cited for educational and analytical purposes.

Referenced works include:
- Herbert Simon: bounded rationality, procedural vs. substantive rationality
- Gary Klein: Recognition-Primed Decision model
- Daniel Kahneman: dual-process theory (System 1 / System 2)
- Gershman, Horvitz, Tenenbaum: computational rationality (Science, 2015)
- Thomas Icard: Resource Rationality (2023)
- Andreas Matthias: the responsibility gap (2004)
- Santoni de Sio and van den Hoven: meaningful human control (2018)
- Parasuraman and Manzey: automation bias (2010)
- Dietvorst, Simmons, Massey: algorithm aversion (2015)
- Oxford Martin School (Simpson, Ortega, Trager): AI governance lessons from aviation and nuclear (2025)
- NIST AI RMF, ISO/IEC 42001, EU AI Act, AIGN OS, ARAF v3.0, OECD AI Principles

Licensed under the Apache License, Version 2.0.
See the LICENSE file for details: http://www.apache.org/licenses/LICENSE-2.0