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AIF-C01 Practice Question: An AI practitioner is training a resume screening…
An AI practitioner is training a resume screening model and discovers that the model has a significantly lower recall for female candidates compared to male candidates. Which type of bias is MOST likely present?
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 training data reflects past societal biases, such as fewer women in certain job roles. This leads to the model learning those biases and producing unfair outcomes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Representation bias
Why it's wrong here
Representation bias occurs when certain groups are underrepresented in the training data, but here the model has lower recall, suggesting it learned biased patterns from historical data.
- ✓
Historical bias
Why this is correct
Historical bias stems from past prejudices in the data; the model learns that female candidates are less likely to be hired, resulting in lower recall.
- ✗
Aggregation bias
Why it's wrong here
Aggregation bias occurs when a model fails to account for differences among subgroups, but here the issue is specifically about historical hiring patterns.
- ✗
Measurement bias
Why it's wrong here
Measurement bias arises from how features are measured or labeled, not from historical outcomes.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services 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 AIF-C01 exam.