AI Associate Ethical AI and Data Privacy Practice Test 2 — 15 Questions

Question 1

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

Accepted Answer

Empathy. The Salesforce Trusted AI principle of Empathy emphasizes that AI systems should be designed with a human-centered approach, ensuring they benefit people and avoid causing harm. This principle guides the ethical development of AI by prioritizing user well-being and societal impact over purely technical or business objectives.

Answer

Safety

Answer

Accuracy

Answer

Honesty

Question 2

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

Accepted Answer

Provide an opt-out mechanism for customers who do not want AI-generated communications. The CCPA grants consumers the right to opt out of the sale or use of their personal information for automated decision-making, including AI-generated communications. Einstein’s automated email responses rely on customer data, so providing a clear opt-out mechanism ensures compliance with CCPA’s requirement for consumer control over data-driven communications.

Answer

Store all AI-generated emails indefinitely for auditing

Answer

Obtain consent only once at account creation

Question 3

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

Accepted Answer

It contractsually obligates Salesforce to protect customer data and outlines data processing terms for AI services. The Data Processing Addendum (DPA) is a legally binding contract between Salesforce and its customers that defines how Salesforce will process customer data, including data used by AI features like Einstein. It ensures Salesforce adheres to data protection laws (e.g., GDPR, CCPA) by specifying data handling, security measures, and sub-processor obligations, making it essential for compliance when using AI services on the platform.

Answer

It lists all AI features available in Salesforce

Answer

It provides a template for customers to build their own AI models

Answer

It is a user guide for configuring AI privacy settings

Question 4

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?

Accepted Answer

Collect more data from that region to provide a representative sample for retraining. The core issue is data sparsity and unrepresentative historical conversion data for that region. By collecting more data from that region, the model can be retrained on a balanced dataset, which directly addresses the root cause of the biased lead scoring. This aligns with the principle of fairness in AI, where models must be trained on representative data to avoid systematic discrimination.

Answer

Adjust the lead scoring formula manually to increase scores for that region

Answer

Remove the region field from the model

Answer

Accept the scores as-is because the model is certified

Question 5

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?

Accepted Answer

Include a note stating 'Recommended by Einstein AI' on each recommendation. The Salesforce Trusted AI Principle of Honesty requires transparency about AI-generated content. By explicitly stating 'Recommended by Einstein AI' on each recommendation, the company clearly discloses that the recommendations are AI-generated, building trust with customers. This aligns with the principle's focus on avoiding deception and ensuring users understand the nature of the content they are seeing.

Answer

Provide a chatbot that can explain the recommendations

Answer

Use a generic label like 'Recommended for you'

Answer

Do not mention AI; just show the recommendations

Question 6

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.. To avoid biased recommendations, the retailer should audit outputs for disparate impact (B), include diverse training data to represent all groups (E), and provide customers with reasons for recommendations to ensure transparency (A). Removing all demographic data from model features (C) is not recommended because it can prevent detection of bias and may not eliminate it; instead, the goal is to ensure fair representation and accountability.

Answer

Remove all customer demographic data from the model features.

Answer

Use only historical purchase data to train the model.

Question 7

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

Accepted Answer

To provide a secure gateway for AI data processing, including data masking and toxicity detection. The Einstein Trust Layer is designed to provide security, privacy, and governance controls for AI features within the Salesforce platform.

Answer

To replace all third-party AI services with Salesforce-owned models

Answer

To automatically generate AI models without any human oversight

Answer

To train large language models on customer data for better predictions

Question 8

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?

Accepted Answer

Data minimisation by selecting only non-PII fields as predictors. The question specifically asks how to ensure no PII is used in model training. Data minimization by selecting only non-PII fields as predictors directly prevents PII from entering the training dataset at the source. This is a proactive governance practice that avoids reliance on post-processing or masking, which may still expose PII during intermediate steps.

Answer

Enabling zero data retention in the Trust Layer

Answer

Data anonymization via the Einstein Trust Layer

Answer

Regularly auditing the model for bias

Question 9

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?

Accepted Answer

Score Factors in Einstein Lead Scoring. Score Factors in Einstein Lead Scoring provides transparency by listing the specific data points (e.g., lead source, industry, engagement history) that contributed to a lead's score. This feature allows admins to see exactly why a lead received a high score, enabling them to validate or adjust the scoring model. It directly addresses the need for explainability in AI-driven lead scoring.

Answer

Einstein Activity Capture

Answer

Einstein Copilot prompt template

Answer

Einstein Trust Layer audit trail

Question 10

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

Accepted Answer

Customer data is not used to train or improve Salesforce's base AI models. Salesforce's DPA states that customer data will not be used to train or improve Salesforce's base AI models, ensuring customer data privacy.

Answer

Customer data may be used to improve Salesforce's AI models unless the customer opts out

Answer

Customer data is anonymized and then used to train public AI models

Answer

Customer data is only used to train models for that specific customer

Question 11

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

Accepted Answer

Einstein Trust Layer audit trail. The Einstein Trust Layer includes an audit trail that logs when AI recommendations are generated and when users act on them. This audit trail is essential for compliance and governance, as it records the AI's decision-making process and user interactions, ensuring transparency and accountability in AI-driven recommendations.

Answer

Einstein Discovery

Answer

Einstein Copilot

Answer

Einstein Prediction Builder

Question 12

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?

Accepted Answer

Customer location data from mobile devices. CCPA gives consumers the right to know what personal information is collected and used. Using purchase history and browsing behavior are typical for personalization, but using location data without explicit consent may be problematic.

Answer

Customer purchase history from the past year

Answer

Customer email address

Answer

Customer browsing behavior on the company website

Question 13

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?

Accepted Answer

Audit the model for bias, provide transparency on decision factors, and require human review for denied applications. It aligns with Salesforce's Trusted AI principles, which emphasize accountability, transparency, and human oversight. Auditing the model for bias identifies disparities, providing transparency on decision factors ensures stakeholders understand how outcomes are determined, and requiring human review for denied applications introduces a safeguard against automated discrimination. This combination addresses bias without abandoning AI's benefits.

Answer

Disable the AI model and make all decisions manually

Answer

Remove demographic data from the model entirely and continue using it

Answer

Retrain the model with more data from the affected group and deploy automatically

Question 14

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)

Accepted Answer

Provide a list of the most influential factors for each recommendation. GDPR's right to explanation requires that individuals can understand the logic behind automated decisions. Providing a list of the most influential factors for each recommendation directly addresses this by offering transparency into the model's decision-making process, such as feature importance scores from a tree-based or linear model.

Answer

Store all recommendation logs for at least 10 years

Answer

Allow customers to opt out of all AI recommendations

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Use only anonymized data for recommendations

Question 15

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)

Accepted Answer

Score Factors on the lead record. Score Factors show why a lead scored as it did, and labeling AI-generated scores helps reps understand that the score is AI-driven.

Answer

Einstein Copilot

Answer

Einstein Activity Capture

Answer

Einstein Trust Layer audit trail