AI0-001 AI Governance and Ethics Practice Question
An AI system trained on historical medical records shows that certain racial groups have higher predicted risk for a disease. The data reflects real-world differences in diagnosis rates due to unequal access to healthcare. Which type of bias is this?
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
✓
Historical bias
Historical bias occurs when the training data reflects past societal inequities. Selection bias would occur if the sample is not representative; confirmation bias stems from the model's own predictions; algorithmic bias arises from the model design.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Algorithmic bias
Why it's wrong here
Algorithmic bias arises from model design choices; here the bias originates from the data.
- ✗
Selection bias
Why it's wrong here
Selection bias involves non-random sampling; the scenario describes systemic historical inequities, not sampling issues.
- ✓
Historical bias
Why this is correct
The data reflects historical disparities in healthcare access, which is a classic example of historical bias.
- ✗
Confirmation bias
Why it's wrong here
Confirmation bias is about interpreting evidence to confirm pre-existing beliefs, not about data reflecting history.
About these practice questions
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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.