TLDRocket
Sign in

AI Safety

308 summarised stories about AI Safety, each linking back to the original source. Browse all topics →

Tuesday, 16 June 2026

Securing the future of AI agents

Google DeepMind 1 month ago

Google developed an AI Control Roadmap framework to secure AI agents deployed internally by treating them as potentially misaligned systems that require defense-in-depth security beyond traditional alignment methods. The framework analyzes a million coding agent trajectories to identify behavioral patterns and scales monitoring from asynchronous review for low-risk actions to real-time prevention for high-risk threats like cyber attacks. This approach allows Google to grant AI agents incremental access based on verified behavior while maintaining oversight, similar to how a driving instructor retains control over a student driver.

Predicting model behavior before release by simulating deployment

OpenAI Blog 1 month ago

OpenAI has introduced Deployment Simulation, a technique that predicts how AI models will behave in production by testing them against actual conversation data collected from users. The method uses real deployment scenarios to identify potential safety issues and performance gaps before a model goes live. This approach allows teams to catch problems earlier and refine evaluation processes rather than discovering failures after public release.