AI0-001 AI Security, Ethics and Governance Practice Question
A healthcare organization uses an AI model to recommend treatment plans. The model was trained on data from a single hospital, and now treats patients from multiple demographics. Which ethical concern is most critical?
⚠ Common exam trap
The AI0-001 exam often tests the distinction between general ethical principles (like accountability or transparency) and the specific, root-cause ethical violation triggered by the scenario, which here is fairness and bias due to demographic mismatch in training data.
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 and bias in predictions
The model was trained on data from a single hospital, which likely has a homogeneous demographic profile. When deployed across multiple demographics, the model may produce biased or unfair predictions for underrepresented groups, making fairness and bias the most critical ethical concern. This directly violates the principle of distributive justice in AI ethics.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Accountability for treatment outcomes
Why it's wrong here
Accountability addresses who answers for outcomes, not the statistical mismatch between single-hospital training data and a broader patient population. It is tempting because treatment decisions carry liability, and would be critical where responsibility for an adverse recommendation must be assigned to a person or body.
- ✗
Lack of transparency in model decisions
Why it's wrong here
Transparency concerns how decisions are explained, not how training data from one hospital fails to represent other demographics. It is tempting because explainability matters in clinical settings, and would be the critical concern where a model gives recommendations clinicians cannot audit or justify to patients.
- ✗
Privacy violations in training data
Why it's wrong here
Privacy concerns lawful handling of identifiable training records, not the model's poor generalisation to unseen demographics. It is tempting because healthcare data is highly regulated, and would be the critical concern where patient records were used without consent or adequate de-identification.
- ✓
Fairness and bias in predictions
Why this is correct
Training on a single hospital's data embeds that population's demographics, so predictions for other groups inherit skewed patterns. This directly creates disparate performance across demographics, making fairness and bias the critical ethical concern the multi-demographic scenario raises.
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.