AI Associate Ethical AI and Data Privacy Practice Question
A healthcare organization uses Einstein Next Best Action to recommend treatments to patients. They must comply with GDPR's right to explanation for automated decisions. Which combination of Einstein Trust Layer features is MOST essential to meet this requirement?
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
✓
Score factors and grounding
The right to explanation requires that individuals can obtain meaningful information about the logic involved in automated decisions. Score factors provide the most influential fields for a prediction, and grounding connects the AI to relevant CRM data, enabling a transparent explanation. Toxicity detection is not relevant. Audit trail logs actions but does not provide explanation to the patient.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Audit trail and PII masking
Why it's wrong here
Audit trail provides a log but not an explanation; PII masking protects privacy but does not explain decisions.
- ✗
Toxicity detection and audit trail
Why it's wrong here
Toxicity detection is for content safety, not explanation. Audit trail logs events but does not explain the reasoning to the patient.
- ✗
Zero Data Retention and PII masking
Why it's wrong here
These protect privacy but do not provide explanations for decisions.
- ✓
Score factors and grounding
Why this is correct
Score factors reveal the most influential features in the prediction, and grounding connects the AI to the specific CRM data used, enabling a clear explanation of the decision logic.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.