- A
Avoid creating or reinforcing unfair bias
This is the exact principle that directly addresses unfair bias.
- B
Uphold high standards of scientific excellence
Why wrong: This principle focuses on scientific rigor, not bias.
- C
Be socially beneficial
Why wrong: This principle focuses on overall benefit, not specifically on bias.
- D
Be accountable to people
Why wrong: This principle is about accountability, not bias specifically.
Question 623 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.
Which of the following is a key principle in Google's AI Principles that directly addresses the need to avoid creating or reinforcing unfair bias?
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
✓
Avoid creating or reinforcing unfair bias
Option A is correct because Google's AI Principles explicitly state 'Avoid creating or reinforcing unfair bias' as a standalone principle. This principle directly mandates that AI systems must be designed and tested to mitigate biases in training data, model outputs, and deployment contexts, ensuring fairness across demographic groups. It is the most direct response to the question's focus on avoiding unfair bias.
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.
- ✓
Avoid creating or reinforcing unfair bias
Why this is correct
This is the exact principle that directly addresses unfair bias.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Uphold high standards of scientific excellence
Why it's wrong here
This principle focuses on scientific rigor, not bias.
- ✗
Be socially beneficial
Why it's wrong here
This principle focuses on overall benefit, not specifically on bias.
- ✗
Be accountable to people
Why it's wrong here
This principle is about accountability, not bias specifically.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between principles that directly address bias versus those that are related but broader, so candidates may confuse 'Be socially beneficial' or 'Be accountable to people' as the correct answer because they seem to cover fairness, but they lack the explicit focus on avoiding unfair bias.
Detailed technical explanation
How to think about this question
Under the hood, avoiding unfair bias requires techniques such as dataset auditing for representation skew, fairness metrics like demographic parity or equalized odds, and post-hoc bias mitigation algorithms like reweighting or adversarial debiasing. A real-world scenario is a hiring model trained on historical data that underrepresents women; without explicit bias checks, it would reinforce gender discrimination, violating this principle even if the model has high accuracy.
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: Avoid creating or reinforcing unfair bias — Option A is correct because Google's AI Principles explicitly state 'Avoid creating or reinforcing unfair bias' as a standalone principle. This principle directly mandates that AI systems must be designed and tested to mitigate biases in training data, model outputs, and deployment contexts, ensuring fairness across demographic groups. It is the most direct response to the question's focus on avoiding unfair bias.
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.
About these practice questions
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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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