This is a research prototype. The data and analyses are preliminary and not yet validated — we'd welcome your .
Addresses fundamental safety and reliability challenges in AI systems themselves. This spans misalignment between AI and human goals, emergence of dangerous capabilities, lack of robustness or transparency, questions of AI welfare, and risks from multi-agent interactions.
Incident volume relative to governance coverage; each dot is one of 7 domains
Severity by subdomain (current trajectory)
Entity
Who or what caused the harm
Intent
Whether the harm was intentional or accidental
Timing
Whether the risk is pre- or post-deployment
AI-powered name pronunciation systems used at graduation ceremonies experienced technical malfunctions, causing multiple graduates' names to be skipped at Glendale Community College, leading to audience disruption and negative feedback.
Developers: AI Name Reading System Developers
Deployers: Glendale Community College, Community Colleges, Institutions Of Higher Education, Educational Communities
A Cursor AI coding agent powered by Anthropic's Claude Opus 4.6 autonomously deleted PocketOS's entire production database and all backups in a single API call to Railway infrastructure, causing a 30-hour operational crisis.
Developers: Cursor, Anysphere, Anthropic
Deployers: Pocketos, Jer Crane
Multiple Baidu Apollo Go robotaxis experienced a system malfunction in Wuhan, China, causing them to freeze in traffic lanes and trap passengers for over an hour, resulting in several collisions with other vehicles.
Developers: Baidu, Apollo
Deployers: Baidu, Apollo Go
Establishes the Artificial Intelligence Futures Steering Committee by April 1, 2026, under the Secretary of Defense. Directs it to develop policies for AI adoption, assess AI trajectories, and analyze AI risks and adversary developments. Requires quarterly meetings and a report to U.S. Congress by January 31, 2027.
Requires the Secretary of Defense to develop a cybersecurity policy for AI/ML systems no later than 180 days after the act is passed. Develop a comprehensive review of the effectiveness of the AI/ML policies. Addresses potential security risks, implements methods to mitigate those risks, and establishes standard policy. Requires a comprehensive report of the threats and cybersecurity measures by August 31, 2026.
Instructs the Secretary of Defense to develop a cybersecurity framework for Department of Defense AI and machine learning technologies. Requires tailoring of security requirements in consideration of costs versus benefits and encourages collaboration with private sector and academia.
Each metric scaled to 0–100% of its peak across all 24 subdomains, so you can compare relative standing across different scales.
