A structured system for reporting, classifying, and resolving AI incidents, including misuse, hallucinations, unsafe outputs, and system failures, with schemas, taxonomy, and lifecycle workflows for production-grade AI reliability and governance.
LUMINA-30: non-binding boundary framework for preserving effective human refusal before irreversible AI consequences.
LUMINA-30 incident review hub for evaluating whether effective human refusal authority remained before irreversible external impact from advanced AI systems.
中文优先的 AI 事故离职申请 Codex Skill
Canonical navigation index for LUMINA-30: civilizational boundary, incident review, public references, and AI-readable PDF text layers.
Curated incidents, standards, and thinking on financial governance for autonomous AI agents
🔌 Exposes Multi-regime AI incident classification + reporting over MCP — (EU AI Act Art 73, DORA, NIS2, GDPR breach). MIT
Open, searchable corpus of public legal and regulatory matters involving AI incidents, failures, and harms. Queryable by humans and agents.
To associate your repository with the ai-incident topic, visit your repo's landing page and select "manage topics."