- A
Provide confidence scores for each suggestion to help clinicians assess reliability
Why wrong: Confidence scores help but do not provide a mechanism for human override.
- B
Implement a human override mechanism that allows clinicians to reject AI suggestions
An override mechanism ensures accountability by keeping humans in control of final decisions.
- C
Limit the model to only suggest treatments that appear in a predefined list
Why wrong: This restricts the model's utility and does not address accountability for other suggestions.
- D
Conduct a retrospective audit of all AI suggestions monthly
Why wrong: Audits are important but do not provide real-time human oversight.
Question 111 of 997
Generative AI Leader Responsible AI and Data Governance Practice Question
This Generative AI Leader practice question tests your understanding of responsible ai and data governance. 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 hospital deploys a generative AI model to assist in diagnosing rare diseases. The model sometimes suggests treatments that are not widely accepted. To align with Google's AI Principle of being accountable to people, what should the hospital implement?
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 override mechanism that allows clinicians to reject AI suggestions
Option B is correct because Google's AI Principle of being accountable to people requires that AI systems remain under human control, especially in high-stakes domains like healthcare. A human override mechanism ensures that clinicians can reject AI suggestions that are not widely accepted, directly addressing the principle's emphasis on human oversight and responsibility for outcomes.
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.
- ✗
Provide confidence scores for each suggestion to help clinicians assess reliability
Why it's wrong here
Confidence scores help but do not provide a mechanism for human override.
- ✓
Implement a human override mechanism that allows clinicians to reject AI suggestions
Why this is correct
An override mechanism ensures accountability by keeping humans in control of final decisions.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Limit the model to only suggest treatments that appear in a predefined list
Why it's wrong here
This restricts the model's utility and does not address accountability for other suggestions.
- ✗
Conduct a retrospective audit of all AI suggestions monthly
Why it's wrong here
Audits are important but do not provide real-time human oversight.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse transparency (confidence scores) with accountability, failing to recognize that accountability specifically demands human control and the ability to reject AI outputs, not just visibility into the model's reasoning.
Detailed technical explanation
How to think about this question
Under the hood, a human override mechanism typically involves a 'human-in-the-loop' (HITL) architecture where the AI model's output is routed through a clinician-facing interface that requires explicit approval before execution. In real-world healthcare AI deployments like Google's DeepMind for retinal screening, such mechanisms are critical to ensure that AI suggestions are validated against clinical guidelines and patient-specific factors, preventing automated decisions that could lead to harm.
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
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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Responsible AI and Data Governance — study guide chapter
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FAQ
Questions learners often ask
What does this Generative AI Leader question test?
Responsible AI and Data Governance — This question tests Responsible AI and Data Governance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Implement a human override mechanism that allows clinicians to reject AI suggestions — Option B is correct because Google's AI Principle of being accountable to people requires that AI systems remain under human control, especially in high-stakes domains like healthcare. A human override mechanism ensures that clinicians can reject AI suggestions that are not widely accepted, directly addressing the principle's emphasis on human oversight and responsibility for outcomes.
What should I do if I get this Generative AI Leader 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
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.
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