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Generative AI Leader Practice Question: A tech company wants to ensure that their…
A tech company wants to ensure that their generative AI model does not produce harmful content. They plan to use Google Cloud's content safety features. Which two methods can they use to customize content safety? (Choose two.)
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
✓
Adjust safety thresholds for different categories like hate speech and violence
Option C is correct because Google Cloud's generative AI safety features (such as those in Vertex AI) let you configure per-category safety thresholds, so you can raise or lower sensitivity for categories like hate speech, harassment, sexually explicit content, and violence to match your tolerance policy. Option D is correct because you can supply a custom blocklist of prohibited terms or phrases, which the service checks in addition to the built-in safety filters, giving you organization-specific control over banned content. Option A is not a customization method—using default filters unchanged is the absence of customization. Option B is wrong because disabling all safety filters removes protection rather than customizing it, and it is not a supported way to ensure harmful content is blocked. Option E is not part of Google Cloud's content safety customization features; training a separate detection model is a different, external approach rather than configuring the built-in safety controls.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use the default safety filters without any modifications
Why it's wrong here
Leaving defaults unchanged is not customisation; the question asks how to customise safety. It is tempting because defaults already block harmful content, but the requirement is to tailor filters, which needs adjustable thresholds or blocklists.
- ✗
Disable all safety filters for maximum model creativity
Why it's wrong here
Disabling filters removes the very moderation the company wants, so harmful output would pass through unchecked. It is tempting because unrestricted generation suits creative brainstorming or red-teaming, where deliberately probing a model's unfiltered behaviour is the goal. Here, though, the requirement is customising safety thresholds, not eliminating them.
- ✓
Adjust safety thresholds for different categories like hate speech and violence
Why this is correct
Per-category safety thresholds let the company tune sensitivity independently for hate speech, violence and other harm types, raising or lowering blocking strictness to match its risk appetite. This satisfies the stem's customisation requirement without retraining the underlying model.
- ✓
Define a custom blocklist of prohibited words or phrases
Why this is correct
A custom blocklist adds organisation-specific prohibited terms and phrases that the default safety classifiers may not cover, such as internal codenames or domain jargon. This satisfies the stem's customisation requirement by supplementing built-in category filters with explicit, deterministic blocking rules.
- ✗
Train a separate model to detect harmful content
Why it's wrong here
Training a separate detector sits outside Google Cloud's content safety configuration; customisation happens through adjustable safety thresholds and blocklists within the service. Building your own classifier is tempting when filters seem insufficient, but it is not a supported customisation method.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This Generative AI Leader practice question is part of Courseiva's free Google Cloud 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 Generative AI Leader exam.