Question 340 of 1,000
Ethical AI and Data PrivacymediumMultiple 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. 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 data governance officer wants to ensure that customer data used in Einstein Prediction Builder is not retained by Salesforce after the prediction is made. Which Einstein Trust Layer capability guarantees this?

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

Zero data retention

Zero data retention is the specific commitment that customer data used for predictions is not stored or used for training base models. This is a key component of the Einstein Trust Layer.

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.

  • Grounding

    Why it's wrong here

    Grounding connects AI to CRM data but does not address data retention.

  • Audit trail

    Why it's wrong here

    Audit trail logs actions but does not prevent data retention.

  • Zero data retention

    Why this is correct

    Zero data retention ensures that customer data is not stored or used to improve base models after prediction.

    Related concept

    CIDR notation defines the prefix length.

  • PII masking

    Why it's wrong here

    PII masking redacts sensitive data but does not guarantee that data is not retained.

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.

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.

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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: Zero data retention — Zero data retention is the specific commitment that customer data used for predictions is not stored or used for training base models. This is a key component of the Einstein Trust Layer.

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

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.

What is the key concept behind this question?

CIDR notation defines the prefix length.

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Last reviewed: Jul 4, 2026

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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.