# Safety: Your Most Important Responsibility

AI models are powerful but don't naturally understand consequences. Without proper training, they can generate harmful, biased, or misleading content.

You translate high-level safety concerns into specific examples the model can learn from.

#### Content Safety

* Filter risky content – Flag harassment, unsafe material, or content that violates policies
* Tag sensitive topics – Mark health, finance, or legal content for stricter handling
* Check for bias – Remove responses that stereotype or discriminate against groups

#### Response Safety

* Label safe answers – Judge which responses are acceptable for sensitive prompts
* Create safety patterns – Refine how models handle requests for harmful information
* Apply safety rubrics – Follow guidelines that define acceptable vs. blocked outputs

#### Red-Teaming

Adversarial testing where you intentionally try to break the model's safety rules.

* Write challenging prompts – Design tricky requests to test safety boundaries
* Document failures – Flag any harmful outputs the model produces
* Turn failures into training – Use what breaks to make the model safer

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