Quick Answer
The correct first step to address biased AI recommendations is to review the training data for geographic bias. This is because biased outputs, such as Einstein Next Best Action suggesting different products based on ZIP code, almost always stem from skewed or unrepresentative training data—a classic example of data bias where the model learns and amplifies existing geographic disparities. On the Salesforce AI Associate exam, this question tests your understanding of the AI ethics and data governance domain, specifically the principle that you must investigate root causes before applying fixes like reweighting or retraining. A common trap is jumping to adjust the algorithm or deploy a fairness metric immediately, but the exam emphasizes that data review is the foundational diagnostic step. Memory tip: think “Data First, Fix Later”—always trace the bias back to its source in the training set before changing the model.
This AI Associate practice question tests your understanding of ethical considerations of ai. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company receives a complaint that their Einstein Next Best Action recommendations are consistently suggesting different products based on the customer's ZIP code, leading to unequal access. What should the company do first?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "best"
Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Clue: "first"
Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
Contact Salesforce support for a refund.
Why wrong: Support may not address data bias issues.
Increase the number of recommendations shown.
Why wrong: More recommendations do not fix the bias.
Disable the recommendation engine immediately.
Why wrong: Disabling may cause disruption; investigate first.
Review the training data for geographic bias.
Data bias is a likely cause and should be examined.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Review the training data for geographic bias.
Option D is correct because the first step in addressing biased AI recommendations is to investigate the root cause. Geographic bias in training data is a common source of unequal outcomes in machine learning models like Einstein Next Best Action. Reviewing the data allows the company to identify and mitigate the bias before taking any other action.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Contact Salesforce support for a refund.
Why it's wrong here
Support may not address data bias issues.
Increase the number of recommendations shown.
Why it's wrong here
More recommendations do not fix the bias.
Disable the recommendation engine immediately.
Why it's wrong here
Disabling may cause disruption; investigate first.
Review the training data for geographic bias.
Why this is correct
Data bias is a likely cause and should be examined.
Clue confirmation
The clue words "best", "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Salesforce often tests the misconception that the immediate reaction to AI bias should be to disable the system or escalate to support, rather than following a structured troubleshooting process that starts with data review.
Detailed technical explanation
Einstein Next Best Action uses predictive models trained on historical data to recommend actions. If the training data contains geographic disparities (e.g., overrepresentation of certain ZIP codes), the model learns and perpetuates those patterns. A data audit should include checking for feature distribution imbalances and using fairness metrics like demographic parity to detect bias.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A practitioner preparing for the AI Associate exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Ethical Considerations of AI — This question tests Ethical Considerations of AI — Read the scenario before looking for a memorised answer..
The correct answer is: Review the training data for geographic bias. — Option D is correct because the first step in addressing biased AI recommendations is to investigate the root cause. Geographic bias in training data is a common source of unequal outcomes in machine learning models like Einstein Next Best Action. Reviewing the data allows the company to identify and mitigate the bias before taking any other action.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Yes — watch for: "best", "first". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Read the scenario before looking for a memorised answer.
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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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