Question

A company launches a customer-facing chatbot built on Amazon Bedrock. During testing, the team notices the model occasionally produces hateful and profane language when users provoke it. The team wants a managed way to detect and block toxic and offensive content in both user inputs and model outputs without retraining the model. Which approach best addresses this responsible-AI safety concern?

Accepted Answer

Configure Guardrails for Amazon Bedrock with content filters to block toxic and offensive language in prompts and responses

Answer

Use Amazon SageMaker Clarify to generate feature attribution reports for each chatbot response

Answer

Lower the temperature parameter so the model produces more deterministic and less varied output

Answer

Fine-tune the foundation model on a larger general-purpose text corpus to improve fluency