- A
Continue using the model but monitor the denial rates monthly.
Why wrong: Monitoring without action is insufficient.
- B
Add an explanation to applicants in affected areas about why they were denied.
Why wrong: Explanation is good but does not eliminate the unfair impact.
- C
Remove postal code from the model and retrain using only non-biased features.
Removing the biased proxy variable helps reduce discrimination.
- D
Publish a report on the model's disparate impact and accept it as a business risk.
Why wrong: Accepting discrimination is unethical.
AI Associate Ethical Considerations of AI Practice Question
This AI Associate practice question tests your understanding of ethical considerations of ai. 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 financial institution deploys an AI model to approve loan applications. The model uses features like income, credit score, and postal code. An audit reveals that the model denies loans at a higher rate for applicants in certain postal codes, which correlate with minority neighborhoods. What should the institution do to align with ethical AI principles?
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
Remove postal code from the model and retrain using only non-biased features.
Option D is correct because removing the biased feature and using alternative features is a direct way to mitigate bias. Option A is wrong as it does not address the root cause. Option B is wrong because it only adds transparency, not fairness. Option C is wrong because disclosure does not fix the bias.
Key principle: OSPF neighbour adjacency depends on matching area, hello/dead timers, network type, and authentication — IP reachability alone is not enough.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Continue using the model but monitor the denial rates monthly.
Why it's wrong here
Monitoring without action is insufficient.
- ✗
Add an explanation to applicants in affected areas about why they were denied.
Why it's wrong here
Explanation is good but does not eliminate the unfair impact.
- ✓
Remove postal code from the model and retrain using only non-biased features.
Why this is correct
Removing the biased proxy variable helps reduce discrimination.
Related concept
OSPF neighbours must agree on key parameters.
- ✗
Publish a report on the model's disparate impact and accept it as a business risk.
Why it's wrong here
Accepting discrimination is unethical.
Common exam traps
Common exam trap: OSPF can fail even when IP connectivity looks correct
OSPF neighbour formation depends on matching areas, timers, network type, authentication and passive-interface behaviour. Do not choose an answer only because the devices can ping.
Detailed technical explanation
How to think about this question
OSPF questions usually test the details that control adjacency and route selection. Read the neighbour state, area, router ID and interface configuration before deciding what is wrong.
KKey Concepts to Remember
- OSPF neighbours must agree on key parameters.
- Router ID selection can affect neighbour relationships and LSDB output.
- OSPF cost influences the preferred path.
- A route can appear in OSPF information but not become the installed route.
TExam Day Tips
- Check area mismatch first when OSPF adjacency fails.
- Review passive interfaces when a network is advertised but no neighbour forms.
- Use show ip ospf neighbor and show ip route clues carefully.
Key takeaway
OSPF neighbour adjacency depends on matching area, hello/dead timers, network type, and authentication — IP reachability alone is not enough.
Real-world example
How this comes up in practice
A network engineer at a university connects two campus buildings via a fibre link. Both routers run OSPF, but no adjacency forms — even though both routers can ping each other. The engineer finds one router is in area 0 and the other in area 1. OSPF adjacency requires matching area numbers, hello/dead timers, and network type. IP reachability alone is not enough.
What to study next
Got this wrong? Here's your next step.
Review OSPF neighbour requirements — matching area type, hello and dead timers, network type, stub flags, and authentication. Study show ip ospf neighbor states (INIT, 2-WAY, FULL). Then practise related AI Associate OSPF questions on adjacency and route selection.
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FAQ
Questions learners often ask
What does this AI Associate question test?
Ethical Considerations of AI — This question tests Ethical Considerations of AI — OSPF neighbours must agree on key parameters..
What is the correct answer to this question?
The correct answer is: Remove postal code from the model and retrain using only non-biased features. — Option D is correct because removing the biased feature and using alternative features is a direct way to mitigate bias. Option A is wrong as it does not address the root cause. Option B is wrong because it only adds transparency, not fairness. Option C is wrong because disclosure does not fix the bias.
What should I do if I get this AI Associate question wrong?
Review OSPF neighbour requirements — matching area type, hello and dead timers, network type, stub flags, and authentication. Study show ip ospf neighbor states (INIT, 2-WAY, FULL). Then practise related AI Associate OSPF questions on adjacency and route selection.
What is the key concept behind this question?
OSPF neighbours must agree on key parameters.
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Last reviewed: Jun 23, 2026
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.
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