easyMultiple Choice
Generative AI Leader Practice Question: Is a key Google AI Principle that directly…
Which of the following is a key Google AI Principle that directly addresses the need to avoid creating or reinforcing unfair bias?
⚠ Common exam trap
Google often tests the ability to distinguish between the specific wording of Google's AI Principles, where candidates may confuse 'avoid creating or reinforcing unfair bias' with the broader principle of 'be accountable to people' because both involve ethical considerations, but only the former directly names bias as the core issue.
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
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Avoid creating or reinforcing unfair bias
It is the exact wording of one of Google's seven AI Principles, which explicitly states the commitment to 'avoid creating or reinforcing unfair bias.' This principle directly addresses the need to mitigate bias in AI systems, such as ensuring training datasets are representative and algorithms do not perpetuate historical inequities. It is a foundational directive for responsible AI development, distinct from broader accountability, safety, or privacy concerns.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Avoid creating or reinforcing unfair bias
Why this is correct
Avoid creating or reinforcing unfair bias is one of Google's published AI Principles, committing teams to design systems that do not amplify discrimination against protected groups. It directly addresses the stem's requirement, sitting alongside principles such as being socially beneficial and accountable to people.
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Be accountable to people
Why it's wrong here
Accountability to people covers oversight, appeal and human redress for AI decisions, not the technical mitigation of biased training data or outputs. It is tempting because accountability underpins responsible AI generally, and it would be correct when the requirement concerns governance and answerability rather than fairness itself.
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Be built and tested for safety
Why it's wrong here
Safety testing addresses harmful, dangerous or misused outputs, not discriminatory or unfair treatment of groups. It is tempting because safety and fairness are both responsible-AI objectives, and this principle would be correct when the requirement concerns preventing physical, financial or societal harm rather than bias.
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Incorporate privacy design principles
Why it's wrong here
Privacy design principles govern data handling, consent and minimisation, not fairness in model outputs. It is tempting because privacy and bias both fall under responsible AI, and this principle would be correct when the requirement concerns personal data protection rather than avoiding discriminatory outcomes.
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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.