AI0-001 AI Governance and Ethics Practice Question
A data scientist discovers that a model trained to predict loan defaults is denying loans at a higher rate for a particular demographic group. Which type of bias is MOST likely present?
⚠ Common exam trap
It's easy for candidates to confuse 'algorithmic bias' (a general term) with the specific root cause, failing to recognize that historical bias is the precise type when the bias originates from the training data rather than the algorithm itself.
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 inequalities, leading the model to learn and perpetuate those patterns. In this case, if historical loan data shows higher denial rates for a demographic group due to past discriminatory practices, the model will replicate that bias in its predictions. This is the most likely cause because the model is not inherently biased but inherits bias from the data it was trained on.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Confirmation bias
Why it's wrong here
Confirmation bias is a human tendency to favour information confirming existing beliefs; it is not a property of training data that produces disparate denial rates across demographic groups. It would be the answer when analysing how analysts interpret results, not when a model systematically disadvantages a protected group.
- ✗
Selection bias
Why it's wrong here
Selection bias arises from non-representative sampling during data collection, not from a deployed model producing disparate denial rates across groups. It is tempting because biased training data is a frequent root cause, yet the described outcome reflects the model's learned patterns, pointing to historical or label bias instead.
- ✗
Algorithmic bias
Why it's wrong here
Algorithmic bias arises from model design or training data producing discriminatory outcomes, but the stem describes a disparate impact on a protected group, which is specifically labelled as bias in the data or model rather than a distinct algorithmic type. It is tempting because algorithmic bias is a real concept, yet the scenario points to a different bias category.
- ✓
Historical bias
Why this is correct
Historical bias arises when training data reflects past societal or institutional prejudice, so the model reproduces those disparities. A loan model denying one demographic at higher rates mirrors biased historical lending decisions captured in the training set.
About these practice questions
This AI0-001 question is part of Courseiva's 962-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. 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.