Ethical Immunity for a Living Knowledge Graph: Proactive Threat Mitigation through AI Red Teaming and Decentralized Governance

Abstract

The transition from static articles to a living Scientific Knowledge Graph, as proposed in our previous work, promises to accelerate discovery and restore feedback loops in science. However, a fully open, semantically linked graph of all scientific knowledge also presents an unprecedented dual-use risk: it could become a roadmap for malicious actors to identify and exploit hidden vulnerabilities. This paper addresses that paradox by introducing a comprehensive framework for "Ethical Immunity" — a set of proactive, architecture-level mechanisms designed to make the Knowledge Graph resilient to misuse without resorting to censorship or secrecy. We detail a three-pillar system: (1) AI-powered Red and Blue Teams that continuously simulate misuse scenarios and generate countermeasures; (2) Decentralized Autonomous Organizations (DAOs) for transparent, expert-driven oversight and risk assessment; and (3) "Ethical Quarantine" protocols that allow for the temporary isolation of high-risk knowledge while ensuring the parallel development of defenses. We argue that such a framework transforms the Knowledge Graph from a passive repository into an active immune system for civilization, capable of identifying and neutralizing threats at the speed of discovery. This paper provides a technical and organizational blueprint for building safety into the very fabric of 21st-century science.