- A
Implement a human-in-the-loop review for sensitive replies
Human reviewers can catch subtle biases that automated filters miss.
- B
Train the model exclusively on historical customer conversations
Why wrong: Historical data may contain biases; training exclusively on it could amplify them.
- C
Use guardrails to filter content
Guardrails can detect and block biased or harmful content automatically.
- D
Set the temperature parameter to 1.5
Why wrong: High temperature increases randomness and the likelihood of generating harmful content.
- E
Disable logging to improve performance
Why wrong: Logging is essential for monitoring and improving safety; disabling it hinders governance.
Question 227 of 1,000
Two Measures to Reduce Biased Responses in Amazon Bedrock
This AIF-C01 practice question tests your understanding of fundamentals of generative ai. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is deploying a customer-facing chatbot using Amazon Bedrock. They want to reduce the risk of generating biased or harmful responses. Which TWO measures should they implement? (Choose 2.)
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
✓
Implement a human-in-the-loop review for sensitive replies
Option A is correct because implementing a human-in-the-loop review for sensitive replies allows human reviewers to assess and approve or reject model outputs before they reach the customer. This directly mitigates the risk of biased or harmful responses by adding a layer of human judgment, especially for edge cases or high-stakes interactions where the model's guardrails might not be sufficient.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Implement a human-in-the-loop review for sensitive replies
Why this is correct
Human reviewers can catch subtle biases that automated filters miss.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Train the model exclusively on historical customer conversations
Why it's wrong here
Historical data may contain biases; training exclusively on it could amplify them.
- ✓
Use guardrails to filter content
Why this is correct
Guardrails can detect and block biased or harmful content automatically.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Set the temperature parameter to 1.5
Why it's wrong here
High temperature increases randomness and the likelihood of generating harmful content.
- ✗
Disable logging to improve performance
Why it's wrong here
Logging is essential for monitoring and improving safety; disabling it hinders governance.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common misconception when using Amazon Bedrock is that increasing the temperature parameter or training on raw historical data alone can improve safety, when in fact these actions increase risk or reduce oversight.
Detailed technical explanation
How to think about this question
Guardrails in Amazon Bedrock use configurable policies (e.g., content filters, topic policies) that intercept model inputs and outputs at inference time, applying rules based on predefined thresholds (e.g., toxicity scores from classifiers like AWS Comprehend). Human-in-the-loop workflows can be integrated via AWS Step Functions or Amazon A2I (Augmented AI) to route flagged responses for manual review, ensuring compliance with responsible AI principles. The temperature parameter controls the probability distribution of the next token; values above 1 flatten the distribution, increasing the likelihood of low-probability tokens and thus more creative but less safe outputs.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Questions learners often ask
What does this AIF-C01 question test?
Fundamentals of Generative AI — This question tests Fundamentals of Generative AI — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Implement a human-in-the-loop review for sensitive replies — Option A is correct because implementing a human-in-the-loop review for sensitive replies allows human reviewers to assess and approve or reject model outputs before they reach the customer. This directly mitigates the risk of biased or harmful responses by adding a layer of human judgment, especially for edge cases or high-stakes interactions where the model's guardrails might not be sufficient.
What should I do if I get this AIF-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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