AWS Certified AI Practitioner AIF-C01 Practice Question
A team is building a customer credit-approval model. To follow the human-centered design principle of unbiased decision-making, which action best supports this goal?
Withhold all model details from end users to reduce the risk of adversarial attacks.
Limit explanations to one sentence so users are not overloaded with information.
Provide feature-attribution explanations that show how much each sensitive attribute affected an individual prediction.
Choose the most complex ensemble model available to maximize predictive accuracy.
Unbiased decision-making requires designers to surface information that helps users detect and correct unfair outcomes. Providing feature-attribution explanations that disclose whether sensitive attributes (for example, gender or race) influenced each prediction lets reviewers evaluate and challenge any discriminatory impact. Keeping explanations short, maximizing raw accuracy with complex models, or hiding all model details does not empower users to identify or address potential bias, so those actions do not satisfy the principle.
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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