AI Associate Ethical Considerations of AI Practice Question
An AI system for hiring is deployed. After six months, the HR team notices that the model's recommendations closely mimic past human hires, which were biased. The team wants to correct this. What should be their first step?
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
✓
Implement continuous monitoring and a feedback loop to detect and mitigate bias
Continuous monitoring and feedback loops can detect and correct drift or bias. Option A is wrong because removing the model does not solve underlying bias. Option C is wrong because past data already contains bias. Option D is wrong because complete transparency does not automatically correct bias.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Shut down the AI system entirely
Why it's wrong here
Shutdown may be drastic; a better approach is correction.
- ✓
Implement continuous monitoring and a feedback loop to detect and mitigate bias
Why this is correct
Monitoring allows ongoing adjustment to ensure fairness.
- ✗
Retrain the model with the same historical data but with more features
Why it's wrong here
Using the same biased data will likely reproduce bias.
- ✗
Make the model's decision process fully transparent to all candidates
Why it's wrong here
Transparency alone does not correct bias.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI Associate practice question is part of Courseiva's free Salesforce 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 AI Associate exam.