AI Safety & Responsible AI
Red teaming
Actively trying to break or misuse an AI system to uncover weaknesses before attackers do.
Example
Specialists deliberately try to make a chatbot reveal secrets or produce harmful instructions.
Why it matters
It helps expose weaknesses that ordinary demonstrations are unlikely to reveal.
You'll hear it
“The test found a way around the approval step.”
Can you control it?
Sometimes
Sometimes. Some products or workflows let you influence red teaming, while others keep it fixed or manage it automatically. Check the settings and documentation for the tool you are using.
Common questions
- Does failing to break a system prove it is secure?
- No. The tested approaches cover only part of what could go wrong.
- Is this the same as attacking a service without permission?
- No. Legitimate testing needs an agreed scope and authority.
- Can the team overlook familiar assumptions?
- Yes. Different perspectives can reveal problems that one group repeatedly misses.