Question 489 of 753
AI Associate Ethical Considerations of AI Practice Question
An AI Associate deploys an Einstein Bot that uses sentiment analysis to escalate frustrated customers. After launch, the bot escalates disproportionately for non-native English speakers. What is the most likely cause?
⚠ Common exam trap
Salesforce often tests the concept that bias in AI systems typically originates from the training data or model design, not from operational configuration issues like thresholds or routing, which are common distractors.
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
✓
The sentiment model was trained on a non-representative dataset.
The sentiment analysis model likely exhibits bias due to training data that does not adequately represent the linguistic patterns, idioms, or expressions of non-native English speakers. This causes the model to misinterpret neutral or positive statements from these users as negative or frustrated, leading to disproportionate escalations. A non-representative dataset is a common source of algorithmic bias in AI systems.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
The sentiment model was trained on a non-representative dataset.
Why this is correct
Training data lacking linguistic diversity causes biased sentiment detection.
- ✗
The bot is routing to the wrong department.
Why it's wrong here
Routing is not the cause of disproportionate escalation.
- ✗
The escalation threshold is set too low.
Why it's wrong here
Threshold affects volume, not demographic disparity.
- ✗
The bot is not properly connected to the escalation queue.
Why it's wrong here
The bot escalates, so connection works.
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Last reviewed: Jun 30, 2026
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.
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