AI World 4 · ML Pipeline · Stage 4

Check the Bias

Count the under-25s, compare their labels, compare the model's rejections, explain one decline, and write the card the regulator reads.

Domain: AI and machine learning
World: AI World 4: ML Pipeline (Associate)
Game type: Solution board: Drop services into each row's slots, then run records through them.
Time: About 25 minutes on a first attempt (estimated)
Exam guides: AIF-C01Task 4.1: Explain the development of AI systems that are responsible; Task 4.2: Recognize the importance of transparent and explainable models; Task 5.1: Explain methods to secure AI systems
MLA-C02Skill 1.3.3: Identify and mitigate sources of bias in data by using AWS tools and techniques (for example, dataset splitting, shuffling, augmentation); Skill 1.3.5: Resolve class imbalance in numeric, text, and image datasets; Skill 2.3.4: Explain model outputs
AIP-C01Skill 3.3.1: Develop compliance frameworks to ensure regulatory compliance for FM deployments (for example, by using SageMaker AI to develop programmatic model cards, AWS Glue to automatically track data lineage, metadata tagging for systematic data source attribution, CloudWatch Logs to collect comprehensive decision logs); Skill 3.4.2: Apply fairness evaluations to ensure unbiased FM outputs (for example, by using pre-defined fairness metrics in CloudWatch, Amazon Bedrock Prompt Management and Amazon Bedrock Prompt Flows to perform systematic A/B testing, Amazon Bedrock with LLM-as-a-judge solutions to perform automated model evaluations)