ai-prompt-engineering-safety-best-practices

Mitigate bias in AI outputs by applying red-teaming, adversarial testing, and moderation APIs. This Skill guides you through detecting and preventing harmful or biased responses to ensure responsible AI usage.

Test AI safety using red-teaming and adversarial testing methodologies to identify vulnerabilities. This Skill provides testing frameworks to detect harmful outputs and validate that LLMs adhere to Microsoft, Google, and OpenAI safety principles.

Yes, you can use prompt patterns like role prompting and chain-of-thought to improve LLM safety by structuring inputs carefully. This Skill teaches how to apply these patterns to maintain context and constraints.

Prevent data leakage in AI assistants by applying prompt constraints and security measures outlined in this Skill. It covers strategies to protect user privacy and mitigate risks of sensitive information exposure.

You need moderation APIs as part of a comprehensive strategy to detect and prevent harmful outputs. This Skill explains how to integrate them with prompt engineering fundamentals for effective bias mitigation.