AI Associate Ethical AI and Data Privacy Practice Test 4 — 15 Questions

Question 1

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?

Accepted Answer

The model may be biased due to underrepresented data from that region in the training set. Audit the model for bias and review training data demographics.. The low scores for a specific region likely indicate bias in the model due to historical data imbalances. The first step should be to audit the model for bias using tools like Fairness in AI or reviewing training data distribution.

Answer

The model is accurate; the region is genuinely underperforming. The team should accept the scores.

Answer

The region has lower quality leads, so the scores are correct. The team should focus on other regions.

Answer

Retrain the model with more data from that region, even if it means duplicating records.

Question 2

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?

Accepted Answer

A clear explanation of how the AI reaches its conclusions and the option to request human review.. Under GDPR Article 22, customers have the right to request an explanation of automated decisions and to contest them. Transparency about AI limitations is also part of Salesforce's Honesty principle.

Answer

The ability to opt out of all AI interactions entirely.

Answer

A copy of the AI model's source code upon request.

Answer

An assurance that no personal data is used in training the AI model.

Question 3

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?

Accepted Answer

Exclude sensitive attributes from the model features unless they are essential and legally permitted, and ensure no proxies exist.. Data minimisation is a core principle: only use relevant features for the prediction. Sensitive attributes that could lead to discriminatory decisions should be excluded unless legally required and properly managed.

Answer

Use synthetic data to replace sensitive attributes with random values.

Answer

Include all available attributes to maximize model accuracy, then apply fairness constraints.

Answer

Mask the sensitive attributes but still include them in the model training.

Question 4

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?

Accepted Answer

Enable the Einstein Trust Layer with toxicity detection and PII masking, and require human approval before the bot sends any promotional messages.. The Einstein Trust Layer provides toxicity detection to prevent harmful outputs, PII masking to protect sensitive data, and audit trails for governance. Direct human review of promotional offers is also important for empathy and oversight.

Answer

Disable the Einstein Trust Layer to improve response speed, and rely on the bot's internal moderation.

Answer

Use a custom AI model without the Trust Layer, but log all bot decisions for audit.

Answer

Enable the Einstein Trust Layer with toxicity detection only, and allow the bot to send messages automatically.

Question 5

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?

Accepted Answer

The 'Score Factors' or 'Prediction Explanation' component available on the record page.. Einstein Discovery provides 'score factors' that show the most influential fields and their impact on the prediction, enabling transparency.

Answer

The 'Model Performance' tab in Einstein Discovery Settings.

Answer

The 'Prediction Summary' report in Einstein Analytics.

Answer

The 'Data Quality' dashboard to check if the prediction is reliable.

Question 6

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?

Accepted Answer

Enable PII masking and configure it to identify and mask health-related data fields.. HIPAA requires protection of Protected Health Information (PHI). PII masking in the Einstein Trust Layer ensures that PHI is not exposed or retained in logs or training.

Answer

Set up an audit trail for all bot interactions.

Answer

Enable toxicity detection to ensure the bot does not use offensive language.

Answer

Disable data retention to ensure no customer data is stored.

Question 7

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?

Accepted Answer

Exclude PII fields from the training dataset entirely and use only non-sensitive features.. Data minimisation and privacy by design dictate that PII should be excluded from training data to prevent the model from memorizing or relying on sensitive information.

Answer

Use the PII fields but restrict the model from outputting them through post-processing filters.

Answer

Anonymize the PII fields by hashing them and include the hashed values as features.

Answer

Include all fields initially, then use feature importance to prune PII fields after training.

Question 8

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?

Accepted Answer

The scores are AI-generated, the key factors influencing each score are available, and reps should use their judgment.. The Honesty and Transparency principles require that users are informed that scores are AI-generated, understand the factors influencing them, and are aware of limitations.

Answer

The scores are based on a secret algorithm to prevent gaming the system.

Answer

Only managers can see the score factors to avoid confusion.

Answer

The scores are 100% accurate and should be followed without question.

Question 9

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

Accepted Answer

To ensure that customer data is not used to train or improve Salesforce's base AI models.. Zero data retention ensures that customer data used in prompts or predictions is not stored by Salesforce to train or improve base models, protecting privacy.

Answer

To comply with Salesforce's internal data management policies only.

Answer

To improve model accuracy by preventing old data from influencing predictions.

Answer

To reduce storage costs for the customer.

Question 10

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?

Accepted Answer

Accuracy. Accuracy requires that the model should be accurate and tested. If the training data is missing entire categories, the model cannot be accurate for those categories, violating accuracy.

Answer

Empathy

Answer

Honesty

Answer

Safety

Question 11

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?

Accepted Answer

Configure the recommendation strategy to check the 'HasOptedOutOfEmail' field and exclude customers who have opted out.. Consent management involves checking the customer's communication preferences and honoring opt-outs. This can be done by configuring the recommendation logic to check consent fields or using Data Cloud's consent data.

Answer

Include all customers and let the AI decide who to target, as consent is not relevant for recommendations.

Answer

Anonymize customer data before running the AI model so consent is not needed.

Answer

Use a data extension to store consents and manually update it weekly.

Question 12

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?

Accepted Answer

The ability for the applicant to chat with a human agent and receive the specific reasons for the decision.. The right to explanation requires that individuals can obtain meaningful information about the logic of automated decisions, including the factors that led to the outcome.

Answer

A downloadable PDF report of the model's accuracy metrics.

Answer

A live video feed of the data center where the model runs.

Answer

A promise that the model was certified by an external auditor.

Question 13

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?

Accepted Answer

Audit trail to log all AI decisions and interactions for compliance reviews.. PII masking directly protects health information, while audit trail provides accountability and traceability for compliance.

Answer

Zero data retention to ensure customer data is not stored.

Answer

Grounding to connect AI responses to CRM data.

Answer

Toxicity detection to identify harmful language.

Question 14

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?

Accepted Answer

Provide sales reps with explanations of the key factors influencing each score.. Accuracy validation, transparency through explanation, and human oversight align with Salesforce's principles.

Answer

Keep the model's logic secret to prevent gaming the system.

Answer

Override the scores without review if they conflict with intuition.

Question 15

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?

Accepted Answer

Provide customers with a reason why a particular product was recommended.. Auditing for bias, ensuring diverse training data, and providing transparency are key to mitigating bias and following Trusted AI principles.

Answer

Remove all customer demographic data from the model features.

Answer

Use only historical purchase data to train the model.