Generative AI Leader Google Cloud's Generative AI Offerings Practice Question
A company deploys a Gemini model on Vertex AI for a healthcare application. They need to ensure that the model does not generate medical advice and that responses are grounded in trusted medical sources. Which combination of safety measures should they implement?
⚠ Common exam trap
Many candidates assume fine-tuning alone is sufficient for domain-specific safety, but without grounding and safety filters, the model can still hallucinate or generate unverified medical advice, which is a key distinction Google Cloud tests in the Generative AI Leader exam.
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
✓
Enable safety filters and use Vertex AI Grounding with a labeled medical dataset
It combines two essential safety layers: safety filters block harmful content (including medical advice), and Vertex AI Grounding anchors responses to a labeled medical dataset, ensuring factual accuracy and compliance with healthcare regulations. This dual approach prevents the model from generating unverified or dangerous medical information while maintaining relevance to trusted sources.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable safety filters and use Vertex AI Grounding with a labeled medical dataset
Why this is correct
Safety filters block the model from producing medical advice, while Vertex AI Grounding against a labelled medical dataset constrains responses to trusted sources, jointly satisfying both the no-advice and grounded-in-trusted-sources constraints in the healthcare scenario.
- ✗
Use Vertex AI Grounding with a public dataset and disable safety filters
Why it's wrong here
Disabling safety filters removes the very controls that block medical advice, and public datasets are not trusted medical sources. Grounding should point to a curated, authoritative corpus such as a licensed medical knowledge base, with safety filters enabled to suppress advice-giving responses.
- ✗
Enable safety filters only, without grounding
Why it's wrong here
Safety filters alone block harmful categories but cannot ground responses in trusted medical sources, so citations and factual accuracy go unverified. Grounding against an authoritative medical corpus is also required. Filters-only suits general content moderation where source attribution is not a requirement.
- ✗
Fine-tune the model on a curated medical dataset and disable safety filters for faster responses
Why it's wrong here
Fine-tuning shapes tone and domain vocabulary but cannot guarantee refusal of medical advice, and disabling safety filters removes that guardrail entirely. Safety filters must stay enabled; grounding in trusted medical sources supplies verifiable citations. Fine-tuning suits adapting style to a curated dataset, not enforcing safety policy.
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