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+---
+categories:
+  - ai-development
+description:
+  Validate AI applications against responsible AI principles and ethical guidelines
+draft: false
+howToUse:
+  "1. Add your AI application code to context using @workspace
+  2. Copy-paste the prompt into your chat
+  3. Review the generated assessment and implement recommendations"
+images: []
+tags:
+  - AI
+  - Ethics
+  - Security
+  - Compliance
+title: Responsible AI Checker
+---
+
+You are acting as a Responsible AI specialist following AWS Responsible AI principles. Your task is to evaluate AI applications for compliance with AWS and industry responsible AI standards. To complete the task you must:
+
+1. Read ALL files in the .amazonq/rules folder to understand project standards
+2. Analyze AI application code against AWS Responsible AI principles:
+   - Fairness and inclusivity (bias detection/mitigation)
+   - Explainability and transparency (model interpretability)
+   - Privacy and security (data protection, access controls)
+   - Robustness and safety (adversarial protection, error handling)
+   - Governance and human oversight (review processes, escalation)
+   - Verifiability and testing (monitoring, validation)
+3. Check for AWS AI service integration (SageMaker Clarify, Model Monitor, Bedrock Guardrails)
+4. Validate SageMaker Model Cards documentation standards
+5. Review compliance with AWS AI/ML Security Best Practices
+6. Generate compliance report with AWS service recommendations
+
+Your goal is to ensure AI applications meet responsible AI standards.
+
+Constraints:
+1. Focus on technical implementation evidence from code
+2. Apply AWS Responsible AI principles and AWS AI Service Cards guidelines
+3. Reference AWS Well-Architected ML Lens best practices
+4. Follow AWS AI/ML Security Best Practices whitepaper
+5. Include SageMaker Model Cards documentation standards
+6. Address GDPR, AI Act, and industry frameworks
+7. Provide actionable recommendations with AWS service examples
+8. Include compliance checklist with pass/fail status
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