- A
Algorithmic bias
The model's algorithm or training process causes systematic errors against certain groups.
- B
Historical bias
Why wrong: Historical bias would stem from past discriminatory data, not necessarily from model design.
- C
Selection bias
Why wrong: Selection bias occurs if the training data is not representative of the population.
- D
Confirmation bias
Why wrong: Confirmation bias is a human cognitive bias, not a model bias.
Question 509 of 1,000
AI0-001 AI Governance and Ethics Practice Question
This AI0-001 practice question tests your understanding of ai governance and ethics. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A social media platform uses an AI system to moderate content. The system incorrectly flags legitimate posts as hate speech, disproportionately affecting minority groups. Which type of bias is 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
✓
Algorithmic bias
The AI system's output (incorrectly flagging legitimate posts as hate speech) is a direct result of the model's design, training data, or deployment choices, which is the definition of algorithmic bias. This bias disproportionately affects minority groups because the algorithm's decision-making process systematically produces unfair outcomes for those groups, even if the training data itself was not historically biased.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 this is correct
The model's algorithm or training process causes systematic errors against certain groups.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Historical bias
Why it's wrong here
Historical bias would stem from past discriminatory data, not necessarily from model design.
- ✗
Selection bias
Why it's wrong here
Selection bias occurs if the training data is not representative of the population.
- ✗
Confirmation bias
Why it's wrong here
Confirmation bias is a human cognitive bias, not a model bias.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between 'algorithmic bias' (bias introduced by the model's design or deployment) and 'historical bias' (bias present in the training data), so candidates mistakenly choose historical bias when the question describes a system that actively produces unfair outcomes due to its own logic.
Detailed technical explanation
How to think about this question
Algorithmic bias can arise from imbalanced training data, flawed feature engineering, or inappropriate optimization objectives. For example, if the model was trained on a dataset where hate speech labels were disproportionately applied to posts from minority groups, the algorithm may learn to associate linguistic features common in those groups with hate speech, leading to false positives. In real-world scenarios, this has been observed in content moderation systems where African American Vernacular English (AAVE) is incorrectly flagged as toxic at higher rates than other dialects.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the AI0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this AI0-001 question test?
AI Governance and Ethics — This question tests AI Governance and Ethics — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Algorithmic bias — The AI system's output (incorrectly flagging legitimate posts as hate speech) is a direct result of the model's design, training data, or deployment choices, which is the definition of algorithmic bias. This bias disproportionately affects minority groups because the algorithm's decision-making process systematically produces unfair outcomes for those groups, even if the training data itself was not historically biased.
What should I do if I get this AI0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
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.
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