AI0-001 AI Security, Ethics and Governance Practice Question
A bank deploys an AI system to approve loan applications. During testing, the model denies a disproportionate number of applicants from a particular demographic group, even after controlling for credit history. Which ethical principle is being violated?
⚠ Common exam trap
The AI0-001 exam often tests the distinction between fairness and transparency, where candidates mistakenly choose transparency because they confuse 'explaining why the model denied loans' with 'the model being biased against a group.'
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
✓
Fairness
The AI system's disparate impact on a demographic group, even after controlling for credit history, directly violates the principle of fairness. Fairness in AI requires that models do not produce biased outcomes that systematically disadvantage protected groups, regardless of whether the bias stems from training data, feature selection, or algorithmic design. This scenario describes a clear case of algorithmic bias, which fairness principles aim to prevent.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Transparency
Why it's wrong here
Transparency concerns disclosure of how decisions are made, not disparate outcomes; the model's denial pattern is a fairness or non-discrimination breach. Transparency would be the correct principle if the bank concealed the model's use or could not explain its decision logic to applicants.
- ✗
Privacy
Why it's wrong here
Privacy governs handling of personal data such as collection, storage and consent, whereas the stem describes biased denial rates, which is a fairness violation. Privacy would be the correct principle if applicant data had been exposed or used without authorisation.
- ✗
Accountability
Why it's wrong here
Accountability concerns tracing decisions to responsible owners, not statistical parity across groups. The scenario describes disparate impact after controlling for credit history, which is a fairness violation. Accountability would be the answer if the bank could not identify who authorised the model's deployment or who owns remediation.
- ✓
Fairness
Why this is correct
Fairness requires that outcomes not disadvantage protected groups after legitimate factors are controlled. Denying one demographic disproportionately despite equivalent credit history breaches this principle, indicating bias embedded in training data or features rather than genuine creditworthiness differences.
About these practice questions
One of 962 original AI0-001 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.