Responsible AI Practices for RAG
Explore ethical guidelines and best practices for developing and deploying RAG systems responsibly and transparently.
Why Responsible AI in RAG Matters
Beyond just technical capabilities, Retrieval Augmented Generation (RAG) systems have a real-world impact. Responsible AI (RAI) ensures these powerful systems are developed and deployed ethically, prioritizing human well-being and societal benefit.
It's about building trust, mitigating risks, and ensuring your RAG application contributes positively.
Showing Your Work: Transparency
Transparency in RAG means making it clear how the system works. Users should be able to understand what data sources were used to generate an answer and, ideally, the confidence level of the information.
- Builds user trust.
- Allows for independent verification.
- Helps identify potential issues.
All lessons in this course
- Data Privacy and PII Handling
- Mitigating Hallucinations and Bias
- Responsible AI Practices for RAG
- Defending Against Prompt Injection