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Generative AI Leader Practice Question: Is a key principle in Google's AI Principles that…
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?
⚠ Common exam trap
The Generative AI Leader exam 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.
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
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.
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
Google's AI Principles explicitly list avoiding creation or reinforcement of unfair bias as a core objective, addressing fairness directly. The principle commits Google to preventing unjust impacts on people, particularly those relating to sensitive characteristics such as race, gender, and similar protected attributes.
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Uphold high standards of scientific excellence
Why it's wrong here
Scientific excellence governs rigour, reproducibility and peer review of AI research, not fairness outcomes, so it does not address avoiding unfair bias. It is tempting because rigorous evaluation supports trustworthy systems, and it would be the correct principle when the concern is research quality or methodological validity.
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Be socially beneficial
Why it's wrong here
Being socially beneficial covers broad societal impact, not the specific mandate to avoid unfair bias, which sits under the separate principle of avoiding creating or reinforcing unfair bias. It is tempting because social benefit sounds related to fairness, and it would be the correct principle when assessing whether an AI application advances the common good overall.
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Be accountable to people
Why it's wrong here
Accountability concerns human oversight, redress and responsibility for AI outcomes, not the avoidance of unfair bias itself. It is tempting because biased systems harm people and demand accountability, and it would be the correct principle when the question concerns governance, auditability or remedy mechanisms.
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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.