Safety + Red Team Testing

Safety + Red Team Testing is the practice of checking an AI agent for harmful or risky behavior before and after release. Safety work sets rules, guardrails, and alarms so the agent follows laws, keeps data private, and treats people fairly. Red team testing sends skilled testers to act like attackers or troublemakers. They type tricky prompts, try to leak private data, force biased outputs, or cause the agent to give dangerous advice. Every weakness they find is logged and fixed by adding filters, better training data, stronger limits, or live monitoring. Running these tests often lowers the chance of real-world harm and builds trust with users and regulators.

Visit the following resources to learn more:

• @roadmap@Visit Dedicated AI Red Teaming Roadmap
• @article@Enhancing AI safety: Insights and lessons from red teaming
• @article@AI Safety Testing in the Absence of Regulations
• @article@A Guide to AI Red Teaming - HiddenLayer