AI0-001 AI Governance and Ethics Practice Question
A company is deploying an AI system that screens job applications. According to the EU AI Act, this system is likely classified as high-risk because it affects employment opportunities. Which requirement must the company implement for high-risk AI systems?
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
✓
A human-in-the-loop mechanism that enables override of the AI's decisions
The EU AI Act requires human oversight for high-risk AI systems to allow operators to override or stop the system's decisions when necessary. The other options are not mandated by the Act for high-risk systems.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
A human-in-the-loop mechanism that enables override of the AI's decisions
Why this is correct
High-risk systems must allow human oversight, including the ability to override or halt automated decisions.
- ✗
Full transparency by publishing the model's source code and training data
Why it's wrong here
The Act does not require full source code disclosure; it mandates transparency documentation such as model cards.
- ✗
Annual third-party audits of the model's energy consumption
Why it's wrong here
Energy consumption reporting is recommended but not a mandatory requirement for high-risk systems.
- ✗
Obtaining explicit consent from each applicant to process their data
Why it's wrong here
While consent may be needed for data processing, it is not the specific human oversight requirement for high-risk AI systems.
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.