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Amazon AIP-C01 Exam - Topic 5 Question 6 Discussion

A company is developing a customer communication platform that uses an AI assistant powered by an Amazon Bedrock foundation model (FM). The AI assistant summarizes customer messages and generates initial response drafts.The company wants to use Amazon Comprehend to implement layered content filtering. The layered content filtering must prevent sharing of offensive content, protect customer privacy, and detect potential inappropriate advice solicitation. Inappropriate advice solicitation includes requests for unethical practices, harmful activities, or manipulative behaviors.The solution must maintain acceptable overall response times, so all pre-processing filters must finish before the content reaches the FM.Which solution will meet these requirements?
D) Use toxicity detection with thresholds configured to 0.5 for all categories. Use parallel processing for both prompt safety classification and personally identifiable information (PII) detection with entity redaction. Apply Amazon CloudWatch alarms to filter metrics.
A) Use parallel processing with asynchronous API calls. Use toxicity detection for offensive content. Use prompt safety classification for inappropriate advice solicitation. Use personally identifiable information (PII) detection without redaction.
B) Use custom classification to build an FM that detects offensive content and inappropriate advice solicitation. Apply personally identifiable information (PII) detection as a secondary filter only when messages pass the custom classifier.
C) Deploy a multi-stage process. Configure the process to use prompt safety classification first, then toxicity detection on safe prompts only, and finally personally identifiable information (PII) detection in streaming mode. Route flagged messages through Amazon EventBridge for human review.

Amazon AIP-C01 Exam - Topic 5 Question 6 Discussion

Actual exam question for Amazon's AIP-C01 exam
Question #: 6
Topic #: 5
[All AIP-C01 Questions]

A company is developing a customer communication platform that uses an AI assistant powered by an Amazon Bedrock foundation model (FM). The AI assistant summarizes customer messages and generates initial response drafts.

The company wants to use Amazon Comprehend to implement layered content filtering. The layered content filtering must prevent sharing of offensive content, protect customer privacy, and detect potential inappropriate advice solicitation. Inappropriate advice solicitation includes requests for unethical practices, harmful activities, or manipulative behaviors.

The solution must maintain acceptable overall response times, so all pre-processing filters must finish before the content reaches the FM.

Which solution will meet these requirements?

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Suggested Answer: D

Option D best satisfies all functional, performance, and governance requirements while minimizing architectural complexity. The requirement explicitly states that all filtering must complete before content reaches the foundation model, which rules out asynchronous or streaming-based approaches that could delay enforcement.

Amazon Comprehend supports toxicity detection, prompt safety classification, and PII detection with entity redaction as managed capabilities. Running these filters in parallel ensures low end-to-end latency, which is essential for customer-facing communication platforms. Parallel execution avoids the cumulative latency that would be introduced by sequential pipelines.

Toxicity detection identifies offensive or abusive content early. Prompt safety classification detects requests for unethical, harmful, or manipulative advice, which directly addresses inappropriate advice solicitation requirements. PII detection with entity redaction ensures that customer privacy is preserved before data is sent to the FM, preventing sensitive information from being processed or echoed in generated responses.

Configuring thresholds allows fine-grained control over sensitivity while maintaining acceptable false-positive rates. Using CloudWatch metrics and alarms enables continuous monitoring of filtering behavior and intervention rates without adding custom routing or human review pipelines that would slow responses.

Option A lacks PII redaction. Option B introduces unnecessary model-building complexity and delayed PII checks. Option C adds sequential latency and introduces human review routing, which violates the response-time requirement.

Therefore, Option D provides the most robust, performant, and AWS-aligned layered content filtering solution.


Contribute your Thoughts:

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Willow
24 days ago
Wait, can we really trust AI to handle PII safely?
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Keneth
29 days ago
I think A is too simplistic for such a complex task.
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Delisa
1 month ago
Option C seems the most thorough with multiple layers of filtering.
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Staci
1 month ago
B sounds good, but relying on a custom classifier feels like a gamble.
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Rolande
1 month ago
Totally agree with C! Human review is a must for sensitive content.
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Dona
2 months ago
Wait, can we really trust AI to handle all this without mistakes?
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Aron
2 months ago
I think A is too risky without redaction for PII.
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Rosalia
2 months ago
Option C seems the most comprehensive with multiple layers of filtering.
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Johna
2 months ago
I recall that using streaming mode for PII detection is crucial, which makes option C appealing, but I wonder if it might slow down response times too much.
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Pa
2 months ago
I feel like option B could work, but I’m not clear on how well a custom classifier would handle all the different types of inappropriate content.
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Johnathon
3 months ago
I think option A sounds familiar because we practiced using asynchronous API calls, but I’m a bit uncertain about the effectiveness of not redacting PII.
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Viola
3 months ago
I remember we discussed the importance of using multiple layers for content filtering, but I'm not sure if option C is the best choice.
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