Question 789 of 1,000

Ethical AI and Data Privacy →mediumMultiple ChoiceObjective-mapped

AI Associate Ethical AI and Data Privacy Practice Question

This AI Associate practice question tests your understanding of ethical ai and data privacy. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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 healthcare organization uses Einstein Prediction Builder to predict patient no-show rates. They want to ensure that protected health information (PHI) like patient names and social security numbers are not used in the model. Which Salesforce Trusted AI principle or feature directly addresses this requirement?

A
Zero data retention
Why wrong: Zero data retention ensures customer data is not stored after prediction, but does not prevent it from being used as a feature during prediction.
B
Explainability
Why wrong: Explainability ensures the model's outputs are understandable, but does not directly restrict which data fields are used.
C
Human oversight
Why wrong: Human oversight requires review of AI actions, but does not prevent PHI from being used as a feature.
D
Data minimisation
Data minimisation means using only the data necessary for the task, avoiding sensitive PII in model training.

Full breakdown with real-world context →

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

✓

Data minimisation

Data minimisation is a key principle: only use relevant features for the model and avoid including sensitive PII unnecessarily. The Einstein Trust Layer's PII masking also helps, but the principle that directly addresses using only relevant fields is data minimisation.

Key principle: Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

✗
Zero data retention
Why it's wrong here
Zero data retention ensures customer data is not stored after prediction, but does not prevent it from being used as a feature during prediction.
✗
Explainability
Why it's wrong here
Explainability ensures the model's outputs are understandable, but does not directly restrict which data fields are used.
✗
Human oversight
Why it's wrong here
Human oversight requires review of AI actions, but does not prevent PHI from being used as a feature.
✓
Data minimisation
Why this is correct
Data minimisation means using only the data necessary for the task, avoiding sensitive PII in model training.
Related concept
CIDR notation defines the prefix length.

Common exam traps

Common exam trap: usable hosts are not the same as total addresses

Subnetting questions often tempt you into counting all addresses. In normal IPv4 subnets, the network and broadcast addresses are not usable host addresses.

Trap categories for this question

Command / output trap
Explainability ensures the model's outputs are understandable, but does not directly restrict which data fields are used.

Detailed technical explanation

How to think about this question

Subnetting questions test whether you can identify the network, broadcast address, usable range, mask and correct subnet. Slow down enough to calculate the block size correctly.

KKey Concepts to Remember

CIDR notation defines the prefix length.
Block size helps identify subnet boundaries.
Network and broadcast addresses are not usable hosts in normal IPv4 subnets.
The required host count determines the smallest suitable subnet.

TExam Day Tips

Write the block size before choosing the subnet.
Check whether the question asks for hosts, subnets or a specific address range.
Do not confuse /24, /25, /26 and /27 host counts.

Key takeaway

Count usable hosts — not total addresses — and remember that the network and broadcast addresses are not available to hosts in standard IPv4 subnets.

Real-world example

How this comes up in practice

A network engineer segments a warehouse floor into three subnets: 20 scanners, 5 printers, and 2 management hosts. Picking the wrong mask wastes addresses or leaves too few usable hosts. Exam questions test whether you can apply CIDR notation, calculate block size, and identify the correct usable-host range for a given prefix.

What to study next

Got this wrong? Here's your next step.

Review block sizes, usable host formulas (2^n − 2), and how to find network and broadcast addresses for /24 through /30. Then practise related AI Associate subnetting questions on CIDR, address ranges, and subnet selection.

Related AI Associate practice-question pages

Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.

Ethical AI and Data Privacy practice questions

Practise AI Associate questions linked to Ethical AI and Data Privacy.

Salesforce Einstein AI Features practice questions

Practise AI Associate questions linked to Salesforce Einstein AI Features.

AI Fundamentals practice questions

Practise AI Associate questions linked to AI Fundamentals.

AI Capabilities in CRM practice questions

Practise AI Associate questions linked to AI Capabilities in CRM.

Ethical Considerations of AI practice questions

Practise AI Associate questions linked to Ethical Considerations of AI.

Data for AI practice questions

Practise AI Associate questions linked to Data for AI.

AI Associate fundamentals practice questions

Practise AI Associate questions linked to AI Associate fundamentals.

AI Associate scenario practice questions

Practise AI Associate questions linked to AI Associate scenario.

AI Associate troubleshooting practice questions

Practise AI Associate questions linked to AI Associate troubleshooting.

Practice this exam

Start a free AI Associate practice session

Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.

10 questions 20 questions 30 questions 50 questions Timed 30

AI Associate practice-test guide →Study guide →Browse all practice tests

FAQ

Questions learners often ask

What does this AI Associate question test?

Ethical AI and Data Privacy — This question tests Ethical AI and Data Privacy — CIDR notation defines the prefix length..

What is the correct answer to this question?

The correct answer is: Data minimisation — Data minimisation is a key principle: only use relevant features for the model and avoid including sensitive PII unnecessarily. The Einstein Trust Layer's PII masking also helps, but the principle that directly addresses using only relevant fields is data minimisation.

What should I do if I get this AI Associate question wrong?

What is the key concept behind this question?

CIDR notation defines the prefix length.

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 →

How Courseiva writes practice questions · Editorial policy

Last reviewed: Jul 4, 2026

Question Discussion

Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.

Loading comments…

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.