AI0-001 AI Security, Ethics and Governance Practice Question
After deploying a model for fraud detection, the data scientist observes a steady decline in precision over two months. Which issue is most likely occurring?
⚠ Common exam trap
The AI0-001 exam often tests the distinction between data drift and concept drift by describing a scenario where the model's predictions become less accurate over time due to a change in the underlying relationship, not just the input data distribution.
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
✓
Concept drift
Concept drift occurs when the statistical properties of the target variable change over time, causing the model's decision boundary to become outdated. In fraud detection, fraudsters continuously adapt their methods, so the relationship between input features and the fraud label shifts, leading to a steady decline in precision as false positives increase.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Data drift
Why it's wrong here
Data drift refers to changes in input distribution; here precision is dropping, suggesting the relationship is changing.
- ✓
Concept drift
Why this is correct
Precision decline indicates that the model's decision boundary is no longer optimal, a sign of concept drift.
- ✗
Model overfitting
Why it's wrong here
Overfitting would likely cause high variance from the start, not gradual decline.
- ✗
Adversarial attack
Why it's wrong here
Adversarial attacks may cause sudden drops, not steady decline.
About these practice questions
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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.