AI0-001 AI Security, Ethics and Governance Practice Question
This AI0-001 practice question tests your understanding of ai security, ethics and governance. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 credit union uses an AI model to approve personal loans. The model was trained on historical data from the past five years. A recent internal review shows that the model approves loans predominantly for white applicants compared to other ethnicities, even when income and credit scores are similar. The credit union wants to comply with fair lending laws without significantly reducing overall approval rates. The data science team has access to the training data. What is the most appropriate remediation step?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Resample the training data to ensure balanced representation of ethnicities
Option B is correct because resampling (oversampling minority groups or undersampling majority) can balance the representation and reduce bias. Option A is wrong because equalizing rates without addressing data bias may not be sustainable. Option C is wrong because skipping the model is not practical. Option D is wrong because simple reweighting may not correct complex biased patterns.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Apply a fairness constraint that penalizes the model for disparate impact
Why it's wrong here
Fairness constraints can be effective but are complex; resampling is simpler and more direct.
✗
Discontinue the AI model and use manual approval for all loans
Why it's wrong here
Manual approval may be less efficient and still biased.
✓
Resample the training data to ensure balanced representation of ethnicities
Why this is correct
Resampling addresses the root cause by balancing training data.
Related concept
Static NAT maps one inside address to one outside address.
✗
Adjust the approval threshold so that approval rates are equal across ethnic groups
Why it's wrong here
This could lead to unqualified approvals or rejections without fixing the model.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
Static NAT maps one inside address to one outside address.
PAT allows many inside hosts to share one public address using ports.
Inside local and inside global describe the private and translated addresses.
NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
→Identify inside and outside interfaces first.
→Check whether the scenario needs static NAT, dynamic NAT or PAT.
→Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI0-001 NAT questions on configuration and troubleshooting.
AI Security, Ethics and Governance — This question tests AI Security, Ethics and Governance — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Resample the training data to ensure balanced representation of ethnicities — Option B is correct because resampling (oversampling minority groups or undersampling majority) can balance the representation and reduce bias. Option A is wrong because equalizing rates without addressing data bias may not be sustainable. Option C is wrong because skipping the model is not practical. Option D is wrong because simple reweighting may not correct complex biased patterns.
What should I do if I get this AI0-001 question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI0-001 NAT questions on configuration and troubleshooting.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Question Discussion
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