20+ practice questions focused on Ethical AI and Data Privacy — one of the most tested topics on the Salesforce AI Associate AI Associate exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Ethical AI and Data Privacy PracticeA sales operations manager notices that the AI-driven lead scoring model assigns lower scores to leads from a particular region, even though those leads historically convert at a higher rate. Which Salesforce Trusted AI principle is most directly violated?
Explanation: The AI-driven lead scoring model is producing outputs that do not match the ground truth (historical conversion rates), which is a direct failure of the Accuracy principle. Accuracy requires that AI systems perform as intended and produce reliable, correct predictions; here, the model's scores are systematically wrong for a specific region, violating that requirement.
What is the primary purpose of the Einstein Trust Layer in Salesforce's AI architecture?
Explanation: The Einstein Trust Layer is designed to provide security, privacy, and governance controls for AI features within the Salesforce platform.
An organization using Einstein Prediction Builder wants to ensure that no customer personally identifiable information (PII) is used in model training. Which data governance practice should they enforce?
Explanation: Option D is correct because the question specifically asks how to ensure no PII is used in model training. Data minimization by selecting only non-PII fields as predictors directly prevents PII from entering the training dataset at the source. This is a proactive governance practice that avoids reliance on post-processing or masking, which may still expose PII during intermediate steps.
A company deploys an AI-powered email composer that drafts responses to customer inquiries. To comply with GDPR, which control should they implement regarding automated decisions?
Explanation: Under GDPR, Article 22 grants individuals the right not to be subject to a decision based solely on automated processing, including profiling, which produces legal effects or similarly significant effects. For an AI email composer that drafts responses to customer inquiries, requiring human review before any AI-generated email is sent ensures that the final decision to communicate is not fully automated, thereby complying with GDPR's requirement for meaningful human intervention in automated decision-making.
A Salesforce admin wants to display an explanation for why a specific lead received a high score from Einstein Lead Scoring. Which Salesforce feature provides this transparency?
Explanation: Option A is correct because Score Factors in Einstein Lead Scoring provides transparency by listing the specific data points (e.g., lead source, industry, engagement history) that contributed to a lead's score. This feature allows admins to see exactly why a lead received a high score, enabling them to validate or adjust the scoring model. It directly addresses the need for explainability in AI-driven lead scoring.
+15 more Ethical AI and Data Privacy questions available
Practice all Ethical AI and Data Privacy questions1. Baseline your knowledge
Start with 10 questions to gauge your current understanding of Ethical AI and Data Privacy. This tells you whether you need a concept refresher or just practice.
2. Review every explanation
For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.
3. Focus on exam traps
Ethical AI and Data Privacy questions on the AI Associate frequently use trap wording. Look for subtle differences in answers that test your precision, not just general knowledge.
4. Reach 80% consistently
Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.
The exact number varies per candidate. Ethical AI and Data Privacy is tested as part of the Salesforce AI Associate AI Associate blueprint. Practicing with targeted Ethical AI and Data Privacy questions ensures you can handle any format or difficulty that appears.
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Difficulty is subjective, but Ethical AI and Data Privacy is a high-priority exam concept tested in multiple ways — direct recall, scenario analysis, and command-output interpretation. Consistent practice is the best way to build confidence.
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