AIF-C01 Guidelines for Responsible AI Practice Question
An e-commerce company uses an Amazon Lex chatbot to handle customer inquiries. They want to implement human oversight for sensitive interactions, such as when the chatbot cannot provide a confident response. Which AWS service should they integrate?
⚠ Common exam trap
In AWS exams, candidates often confuse data processing services (like Comprehend or Rekognition) with the human review service (A2I). They mistakenly choose a service that analyzes text or images rather than the one that orchestrates human oversight.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Amazon Augmented AI (A2I)
Amazon Augmented AI (A2I) is the correct service because it provides built-in human review workflows for ML predictions, allowing you to route low-confidence responses from Amazon Lex to human reviewers for oversight. This directly addresses the requirement for human oversight on sensitive interactions where the chatbot cannot provide a confident response.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon Rekognition
Why it's wrong here
Rekognition performs image and video analysis, so it cannot route a low-confidence Lex conversation to a human agent. It is tempting because it is an AI service that could classify sentiment from customer images, but human oversight of chatbot escalations requires a workflow and contact-centre service, not computer vision.
- ✗
Amazon Comprehend
Why it's wrong here
Comprehend extracts entities, key phrases and sentiment from text; it returns analysis, not a mechanism to hand a conversation to a human agent. It is tempting because it could detect an uncertain or negative customer message, but the requirement is live escalation routing, which Comprehend does not perform.
- ✓
Amazon Augmented AI (A2I)
Why this is correct
Amazon Augmented AI (A2I) adds a human review workflow directly into the inference path, triggering reviewers when confidence scores fall below a threshold. This satisfies the stem's requirement for human oversight of low-confidence chatbot responses, unlike services that only monitor metrics or route notifications after the fact.
- ✗
Amazon SageMaker Ground Truth
Why it's wrong here
Ground Truth builds labelled training datasets for machine learning models; it does not provide live routing of low-confidence Lex conversations to human agents. It is tempting because it involves humans reviewing data, but that review is offline annotation for model training, not real-time escalation during a customer interaction.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.