AWS aws-certification documentation change
Summary
Updated terminology from 'GenAI' to 'generative AI (GenAI)', expanded examples of explainable AI tools, and added examples for human-centered AI design principles.
Security assessment
Changes involve terminology clarification and expanded examples of responsible AI practices, but no security-specific vulnerabilities, features, or mitigations are mentioned.
Diff
diff --git a/aws-certification/latest/ai-practitioner-01/ai-practitioner-01-domain4.md b/aws-certification/latest/ai-practitioner-01/ai-practitioner-01-domain4.md index 3fecf2676..ba4d20bb5 100644 --- a//aws-certification/latest/ai-practitioner-01/ai-practitioner-01-domain4.md +++ b//aws-certification/latest/ai-practitioner-01/ai-practitioner-01-domain4.md @@ -32 +32 @@ Objectives: - * Identify legal risks of working with GenAI (for example, intellectual property infringement claims, biased model outputs, loss of customer trust, end user risk, hallucinations). + * Identify legal risks of working with generative AI (GenAI) (for example, intellectual property infringement claims, biased model outputs, loss of customer trust, end user risk, hallucinations). @@ -49 +49 @@ Objectives: - * Describe tools to identify transparent and explainable models (for example, SageMaker Model Cards, open source models, data, licensing). + * Describe tools to identify transparent and explainable models (for example, Amazon SageMaker Model Cards, SageMaker Clarify, Amazon Bedrock Model Evaluations, open source models, data, licensing). @@ -53 +53 @@ Objectives: - * Describe principles of human-centered design for explainable AI. + * Describe principles of human-centered design for explainable AI (for example, user-feedback mechanisms, AI decision transparency).