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← Ethical AI and Data Privacy practice sets

AI Associate Ethical AI and Data Privacy • Complete Question Bank

AI Associate Ethical AI and Data Privacy — All Questions With Answers

Complete AI Associate Ethical AI and Data Privacy question bank — all 0 questions with answers and detailed explanations.

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Certifications/AI Associate/Practice Test/Ethical AI and Data Privacy/All Questions
Question 1mediummultiple choice
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A sales operations manager notices that the AI-driven lead scoring model assigns lower scores to leads from a particular region, even though those leads historically convert at a higher rate. Which Salesforce Trusted AI principle is most directly violated?

Question 2easymultiple choice
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What is the primary purpose of the Einstein Trust Layer in Salesforce's AI architecture?

Question 3hardmultiple choice
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An organization using Einstein Prediction Builder wants to ensure that no customer personally identifiable information (PII) is used in model training. Which data governance practice should they enforce?

Question 4mediummultiple choice
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A company deploys an AI-powered email composer that drafts responses to customer inquiries. To comply with GDPR, which control should they implement regarding automated decisions?

Question 5mediummultiple choice
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A Salesforce admin wants to display an explanation for why a specific lead received a high score from Einstein Lead Scoring. Which Salesforce feature provides this transparency?

Question 6easymultiple choice
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What is the purpose of ‘toxicity detection’ in the Einstein Trust Layer?

Question 7hardmultiple choice
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A data scientist is building a churn prediction model for a subscription service. The dataset includes highly correlated features: ‘number of support tickets’ and ‘average response time’. Which action is BEST to ensure model accuracy and interpretability?

Question 8mediummultiple choice
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Under the Salesforce Data Processing Addendum (DPA), what is Salesforce's commitment regarding customer data used in AI services?

Question 9easymultiple choice
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Which Salesforce AI feature provides audit logging of when AI recommendations are generated and acted upon?

Question 10mediummultiple choice
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A marketing manager wants to use Einstein to personalize email content for each customer. However, they are concerned about violating CCPA if they use certain data. Which data use would be MOST likely to raise a CCPA concern?

Question 11hardmultiple choice
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An AI model predicts loan approvals, and the bank notices that the model disproportionately denies loans to a certain demographic group. Which combination of actions addresses the AI bias according to Salesforce's Trusted AI principles?

Question 12mediummultiple choice
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When using Einstein Copilot to generate email content, what mechanism ensures that the AI does not use customer data to improve the underlying large language model?

Question 13mediummulti select
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A company is deploying an AI system to recommend products to customers. To comply with GDPR's right to explanation, which TWO practices should they implement? (Choose 2)

Question 14hardmulti select
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A healthcare provider is using Einstein to predict patient readmission risks. They must ensure the model is both accurate and fair. Which THREE actions should they take? (Choose 3)

Question 15easymulti select
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A sales manager wants to use Einstein Lead Scoring but is concerned about transparency for the sales team. Which TWO features should they enable to provide explainability? (Choose 2)

Question 16mediummulti select
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A sales rep receives an AI-generated lead score of 95, but the rep notices the lead's email domain is 'example.com' and the phone number is invalid. The rep suspects the AI model is overvaluing certain features. Which TWO actions should the rep take to investigate and address the issue?

Question 17easymultiple choice
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Which of the following is a key feature of Salesforce Einstein Trust Layer that protects customer data when using AI?

Question 18mediummultiple choice
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A company uses Einstein Discovery to predict customer churn. They want to ensure the predictions are explainable to non-technical stakeholders. What is the best way to provide explanation?

Question 19hardmultiple choice
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A healthcare CRM administrator wants to use AI to recommend treatment plans based on patient data. Which combination of Salesforce Trusted AI principles is MOST critical to consider?

Question 20mediummultiple choice
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A lead scoring model trained on historical sales data is found to assign lower scores to leads from certain postal codes. What is the MOST likely cause?

Question 21hardmulti select
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A company deploying Einstein Bots for customer service wants to ensure compliance with GDPR's right to explanation. Which TWO measures should they implement?

Question 22easymultiple choice
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Which Salesforce feature allows administrators to mask personally identifiable information (PII) in prompts sent to large language models?

Question 23mediummultiple choice
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A marketing manager wants to use AI to generate personalized email content for customers. According to Salesforce's Trusted AI principles, what should the manager ensure before sending?

Question 24mediummultiple choice
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What is the purpose of grounding in the Einstein Trust Layer?

Question 25hardmultiple choice
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A company is concerned about the data minimization principle when using AI to predict customer lifetime value. Which approach aligns with this principle?

Question 26easymultiple choice
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Which Salesforce Trusted AI principle emphasizes that AI systems should be designed to benefit people and avoid causing harm?

Question 27mediummulti select
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A company uses Einstein to generate automated email responses. To comply with CCPA, which THREE practices should they adopt?

Question 28mediummultiple choice
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A data scientist is building a model to recommend products. They notice the model rarely recommends certain categories to users from a specific demographic. What should the scientist do first to address potential bias?

Question 29hardmultiple choice
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What is the role of the Data Processing Addendum (DPA) in the context of AI and data privacy on Salesforce?

Question 30easymultiple choice
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When a Salesforce admin enables 'Score Factors' for an AI prediction, what does this provide to end users?

Question 31mediummultiple choice
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A sales operations manager wants to use Einstein Lead Scoring to prioritize leads. They have historical data showing that leads from a certain postal code have a low conversion rate. However, they suspect the low conversion is due to a past marketing campaign that was poorly targeted, not the demographics of that area. What is the BEST way to ensure the AI model does not unfairly penalize leads from that postal code?

Question 32easymultiple choice
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A Salesforce admin wants to ensure that customer data used by Einstein features is not retained by Salesforce to train foundation models. Which component of the Einstein Trust Layer enforces this commitment?

Question 33mediummultiple choice
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A company deploys an AI-powered email composer for sales reps. The legal team requires that every AI-generated email be reviewed by a human before sending to a customer. Which approach aligns with Salesforce's Trusted AI Principle of Empathy and Human Oversight?

Question 34hardmultiple choice
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A data scientist is building a churn prediction model using Einstein Discovery. They want to ensure the model does not rely on sensitive attributes like race or gender, even if those are correlated with other features. Which technique is MOST aligned with Salesforce's data minimisation principle?

Question 35mediummultiple choice
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A financial services company uses Einstein Bots to answer customer inquiries. A customer asks the bot to explain why their loan application was rejected. The bot provides a response based on AI predictions. Which Salesforce Trusted AI Principle is MOST directly addressed by the bot's ability to explain the decision?

Question 36easymultiple choice
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A company wants to use Einstein Sentiment Analysis to classify customer feedback. What is the FIRST step they should take to ensure ethical use of customer data?

Question 37mediummultiple choice
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A sales manager notices that Einstein Lead Scoring assigns lower scores to leads from a specific region. After investigation, they find that the historical conversion data for that region is sparse and unrepresentative. What should the manager do to improve the model's fairness?

Question 38hardmultiple choice
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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?

Question 39mediummultiple choice
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A company is deploying Einstein Article Recommendations on its customer portal. They want to ensure customers know that recommendations are AI-generated. Which action aligns with the Salesforce Trusted AI Principle of Honesty?

Question 40easymultiple choice
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A company wants to use Einstein Prediction Builder to predict which customers are likely to churn. They have a dataset that includes customers' names, email addresses, and detailed purchase history. According to the data minimisation principle, which fields should be included in the model?

Question 41mediummultiple choice
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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?

Question 42hardmultiple choice
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A company uses Einstein Discovery to build a model that predicts customer lifetime value. They want to ensure the model's decisions are auditable and that they can track the business impact of AI recommendations over time. What should they implement?

Question 43mediummulti select
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A company is implementing Einstein Next Best Action for their customer service agents. They want to ensure that AI recommendations are provided as suggestions but that agents retain the final say. Which TWO practices support this goal of human oversight?

Question 44mediummulti select
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A company must comply with GDPR when using Einstein Features to process customer data for AI predictions. Which THREE actions are required under GDPR that relate directly to AI-driven decisions?

Question 45hardmulti select
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A sales team uses Einstein Lead Scoring and notices that the model gives disproportionately low scores to leads from a certain demographic group. The team suspects historical bias in the training data. Which THREE steps should they take to address this bias?

Question 46mediummultiple choice
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A sales team is using Einstein Lead Scoring and notices that leads from a certain geographic region are consistently scored lower, even when the lead's profile matches high-performing customers from other regions. What is the most likely cause and recommended first step?

Question 47easymultiple choice
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A company wants to implement an AI-powered customer service chatbot that generates responses based on customer inquiries. To comply with GDPR requirements for automated decision-making, what must the company provide to customers?

Question 48mediummultiple choice
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A financial services company is deploying Einstein Prediction Builder to predict loan default risk. They are concerned about using sensitive attributes like race or gender in the model. Which data governance practice should they apply?

Question 49hardmultiple choice
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A Salesforce admin is configuring Einstein Bots for a customer service channel. They want the bot to automatically send promotional offers to customers identified as high-value. Which combination of settings best ensures ethical AI and compliance with data privacy regulations?

Question 50easymultiple choice
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A company uses Einstein Discovery to analyze sales data and provide recommendations. A sales rep wants to understand why a specific opportunity was predicted to close. Which Einstein feature should the rep use?

Question 51mediummultiple choice
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A healthcare organization is using Einstein Bots to schedule patient appointments. They are subject to HIPAA regulations. What is the most important configuration they must apply to the Einstein Trust Layer?

Question 52hardmultiple choice
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A data scientist is training a custom AI model using Salesforce Data. They want to ensure that the model does not inadvertently learn patterns from Personal Identifiable Information (PII) fields such as Social Security numbers. Which approach aligns with Salesforce's responsible AI practices?

Question 53mediummultiple choice
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A company is implementing Einstein Lead Scoring and wants to ensure transparency for sales reps. According to Salesforce's Trusted AI principles, what should the company communicate to users about the AI-generated scores?

Question 54easymultiple choice
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What is the primary purpose of the Einstein Trust Layer's zero data retention setting?

Question 55mediummultiple choice
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A company is using Einstein Article Recommendations in Service Cloud. They notice that articles about a specific product are never recommended, even when relevant. After reviewing, they find that the training data did not include any cases where that product was mentioned. Which Salesforce Trusted AI principle is most directly violated?

Question 56hardmultiple choice
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A Salesforce administrator is setting up Einstein Next Best Action for a marketing campaign. They want to ensure that customer consent preferences are respected. Which action should they take?

Question 57mediummultiple choice
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A company is deploying an AI model to automatically approve or reject small loan applications. To comply with the right to explanation under GDPR, what capability must the system provide?

Question 58mediummulti select
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A healthcare company is using Einstein Bots to handle patient intake. They want to ensure compliance with HIPAA and the Salesforce Trusted AI principles. Which TWO features of the Einstein Trust Layer should they enable?

Question 59easymulti select
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A sales manager is reviewing the AI predictions from Einstein Opportunity Scoring. Which THREE actions should the manager take to ensure ethical use of AI according to Salesforce Trusted AI principles?

Question 60mediummulti select
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A retailer is using Einstein Product Recommendations on their ecommerce site. They want to avoid biased recommendations that might disadvantage certain customer groups. Which THREE steps should they take?

Question 61mediummultiple choice
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A sales operations team notices that an Einstein Lead Scoring model assigns lower scores to leads from a particular geographic region, even though those leads have historically converted at a higher rate. What is the most likely cause of this discrepancy?

Question 62mediummultiple choice
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A healthcare organization uses Einstein Prediction Builder to predict patient no-show rates. They want to ensure that protected health information (PHI) like patient names and social security numbers are not used in the model. Which Salesforce Trusted AI principle or feature directly addresses this requirement?

Question 63hardmultiple choice
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A financial services company is deploying an Einstein chatbot that provides investment advice. They want to ensure that if the chatbot generates a potentially harmful recommendation (e.g., suggesting a risky trade), the message is blocked before reaching the customer. Which Einstein Trust Layer capability should they rely on?

Question 64easymultiple choice
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A marketing manager wants to understand why a specific lead received a high score from an Einstein model. Which Salesforce feature provides the most detailed explanation?

Question 65mediummultiple choice
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A company is subject to GDPR and wants to use customer purchase history to predict future buying behavior. What is the primary requirement they must fulfill under GDPR when using customer data for AI predictions?

Question 66hardmultiple choice
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A data scientist is building a custom AI model using Salesforce Data Cloud to predict customer churn. They want to ensure that the model does not inadvertently use gender as a feature to avoid biased predictions. Which step is MOST appropriate?

Question 67mediummultiple choice
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A sales rep receives an AI-generated recommendation to upsell a product to a customer. The rep wants to verify the reasoning behind the recommendation before acting. What Salesforce feature can the rep use to see the key factors that influenced the recommendation?

Question 68easymultiple choice
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Which Salesforce Trusted AI principle ensures that users are informed when they are interacting with an AI-generated output or recommendation?

Question 69hardmultiple choice
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A company is using Einstein Service Replies to generate suggested responses for service agents. They want to ensure that agents always review and approve the suggested reply before it is sent to the customer. Which configuration best supports this requirement?

Question 70mediummultiple choice
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A data governance officer wants to ensure that customer data used in Einstein Prediction Builder is not retained by Salesforce after the prediction is made. Which Einstein Trust Layer capability guarantees this?

Question 71easymultiple choice
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A company wants to use AI to automatically qualify leads without human intervention. However, they are concerned about potential bias in the model. Which Salesforce approach can help them detect and mitigate bias in their lead scoring model?

Question 72mediummultiple choice
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A company is developing an AI system that makes loan approval decisions. Under GDPR, customers have the right to request an explanation of how the decision was made. Which Salesforce feature provides this explanation?

Question 73hardmulti select
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A company is deploying an Einstein chatbot to handle customer support inquiries. They want to ensure compliance with data privacy regulations and ethical AI principles. Which TWO actions should they take?

Question 74mediummulti select
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A data scientist is building a custom AI model using Salesforce Data Cloud. They want to follow best practices for data minimisation and consent management. Which THREE steps should they take?

Question 75mediummulti select
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A company is implementing Einstein Prediction Builder to forecast sales opportunities. They want to ensure transparency and trust with their sales team. Which TWO practices should they adopt?

Question 76mediummultiple choice
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A sales operations manager wants to ensure that the AI-driven lead scoring model in Salesforce does not discriminate against certain demographic groups. Which Salesforce tool or feature should they use to regularly check for bias in the model's predictions?

Question 77hardmultiple choice
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A healthcare organization uses Einstein Next Best Action to recommend treatment plans to practitioners. A patient disputes a recommendation, claiming it was based on inaccurate historical data. Under GDPR, the patient has the right to obtain an explanation of the automated decision. Which Salesforce feature directly supports this right to explanation?

Question 78easymultiple choice
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A company is deploying Einstein Reply Recommendations for a sales team. To comply with Salesforce's Trusted AI principle of transparency, what must the company ensure about the AI-generated replies?

Question 79mediummulti select
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A financial services firm uses Einstein Discovery to predict loan default risk. To comply with data minimisation principles and avoid using sensitive PII unnecessarily, which TWO actions should the data science team take?

Question 80hardmulti select
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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?

Question 81mediummulti select
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A company uses Einstein Bots to handle customer inquiries. To comply with GDPR's right to explanation for automated decisions affecting customers, which TWO capabilities must the bot implementation include?

Question 82easymulti select
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A marketing team uses Einstein Send Time Optimization to determine the best time to send emails. To ensure the company follows Salesforce's Trusted AI principle of Honesty, which THREE practices should be adopted?

Question 83hardmulti select
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A company uses Einstein Prediction Builder to forecast customer churn. The data science team discovers that the model is heavily influenced by a field containing the customer's income, which the company legally cannot use for automated decisions in certain jurisdictions. Which TWO steps should the team take to address this ethical and compliance issue?

Question 84mediummulti select
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A customer service director wants to implement an AI-powered chat assistant that can answer common questions. To align with Salesforce's Trusted AI principle of Empathy, which THREE design choices should the director make?

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