AI Associate Ethical AI and Data Privacy Practice Question
A customer service manager wants to use Einstein Bots to handle common inquiries. They are concerned about the bot generating offensive responses. Which Einstein Trust Layer feature should they enable to minimize this risk?
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
✓
Toxicity detection
Toxicity detection is a feature of the Einstein Trust Layer that identifies and filters harmful or offensive language before it is sent to customers. This directly addresses the concern about offensive responses, aligning with the Safety principle.
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 protects customer data privacy but does not filter offensive content.
- ✗
Grounding
Why it's wrong here
Grounding connects AI to CRM data for relevance, but does not filter offensive content.
- ✓
Toxicity detection
Why this is correct
Toxicity detection scans for harmful language and can block or flag responses, ensuring the bot is safe for customers.
- ✗
PII masking
Why it's wrong here
PII masking protects sensitive data but does not address content offensiveness.
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JA
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.