3AI Safety, Security, and Governance

• 3.1Input and Output Safety Controls

  Learn defense-in-depth against harmful inputs/outputs: input/output filtering with Bedrock Guardrails, toxicity/moderation, hallucination reduction (Knowledge Base grounding, JSON Schema), and prompt injection/jailbreak detection.

• 3.2Data Security and Privacy Controls

  Learn data protection for FM deployments: isolation/access with VPC endpoints/IAM/Lake Formation, PII detection with Comprehend/Macie, data masking/anonymization, and retention with S3 Lifecycle.

• 3.3AI Governance and Compliance Mechanisms

  Learn governance for compliance and traceability: SageMaker model cards, data lineage/catalog with Glue, CloudTrail auditing, and continuous monitoring (misuse, drift, policy violations, bias drift).

• 3.4Implementing Responsible AI Principles

  Learn to implement transparency, fairness, and accountability: reasoning display and source attribution, Bedrock agent tracing, fairness evaluation (CloudWatch metrics, A/B testing, LLM-as-a-judge), and stating limitations via model cards.