AI Associate Ethical AI and Data Privacy Practice Question
A retail company uses Einstein Article Recommendations to suggest knowledge articles to customer service agents. To ensure compliance with the Salesforce Trusted AI principle of Safety, which THREE measures should the company implement?
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
✓
Use grounding to connect the AI recommendations to the company's CRM data
Safety involves preventing harmful outputs. Human review, toxicity detection, and using grounding to ensure relevance all mitigate harmful recommendations. Hiding the model's confidence score reduces transparency, and logging without review does not prevent harm.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Log all recommendations without setting up any review process
Why it's wrong here
Logging alone does not prevent harmful outputs; active review is needed.
- ✓
Use grounding to connect the AI recommendations to the company's CRM data
Why this is correct
Grounding ensures recommendations are based on vetted data, reducing the chance of unsafe outputs.
- ✓
Enable toxicity detection in the Einstein Trust Layer to filter inappropriate content
Why this is correct
Toxicity detection automatically flags harmful content, enhancing safety.
- ✗
Hide the model's confidence score from agents to avoid over-reliance
Why it's wrong here
Hiding confidence reduces transparency and does not directly improve safety.
- ✓
Require human agents to review and approve recommendations before sharing with customers
Why this is correct
Human oversight ensures that potentially harmful content is not sent automatically.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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