AI Associate AI Fundamentals Practice Question
A financial services firm uses an AI model to approve loan applications. They discover the model denies loans at a higher rate for a protected demographic. What is the most likely root cause?
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
✓
The training data contains historical bias
Historical bias in training data can cause models to learn and perpetuate discrimination.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The model is overfitted
Why it's wrong here
Overfitting does not necessarily cause demographic bias.
- ✓
The training data contains historical bias
Why this is correct
If historical loan decisions were biased, the model will learn that bias.
- ✗
The model uses too few features
Why it's wrong here
Too few features can cause underfitting but not specifically demographic bias.
- ✗
The model has low precision
Why it's wrong here
Low precision is a performance metric, not a cause of bias.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI Associate practice question is part of Courseiva's free Salesforce 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 AI Associate exam.