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