AI Associate Practice Test 17 — 15 Questions

Question 1

A multinational corporation uses Einstein Discovery to predict employee performance. An audit reveals potential bias against employees in certain countries. Which THREE actions should they take to address ethical concerns? (Choose three.)

Accepted Answer

Investigate the training data for biased labels or sampling bias across countries. Option A (Investigate the training data for biased labels or sampling bias) is correct because data is often the source. Option C (Engage local ethics representatives from affected regions) ensures diverse perspectives. Option E (Implement a fairness metric and set acceptable thresholds) provides quantitative governance. Option B (Discontinue the model globally) may be too extreme. Option D (Use the model only in countries where it performs well) could still be unfair to others.

Answer

Discontinue use of the AI model worldwide immediately

Answer

Use the model only in countries where it shows no bias

Question 2

Which TWO actions align with ethical AI practices in Salesforce?

Accepted Answer

Monitoring models for bias. Options B and C are correct. Providing explanations for AI predictions ensures transparency, and monitoring models for bias is a core ethical practice. Option A is wrong because using data without consent violates privacy. Option D is wrong because automating all decisions removes human oversight. Option E is wrong because restricting to internal data may limit inclusivity.

Answer

Using only internal data for training

Answer

Automating all decisions without human review

Answer

Using customer data without explicit consent

Question 3

An organization uses Einstein to predict sales opportunities. They notice the model performs poorly for small businesses. What is the most ethical approach?

Accepted Answer

Retrain the model with more data from small businesses.. Option B is correct because adding representative data from small businesses addresses the bias. Option A is wrong because ignoring small businesses is unethical. Option C is wrong because using a completely different model may create inconsistent experiences. Option D is wrong because reducing complexity may not fix the data imbalance.

Answer

Reduce the model's complexity to improve performance.

Answer

Use a completely different model for small businesses.

Answer

Ignore small businesses as they contribute little revenue.

Question 4

Refer to the exhibit. A developer receives this fairness check error. What is the most likely cause?

Accepted Answer

The model has higher false positive and false negative rates for Group B.. Option B is correct because the exhibit clearly shows significantly higher false positive and false negative rates for Group B, indicating the model treats groups differently. Option A is wrong because overfitting is not indicated by these metrics. Option C is wrong because the recommendation is to fix the issue, not that the model is already fair. Option D is wrong because Group A has lower rates, suggesting Group B's data may be insufficient, but the cause is the disparity itself.

Answer

The error is due to insufficient training data for Group A.

Answer

The model is overfitting.

Answer

The recommendation suggests reweighting, so the model is already fair.

Question 5

Which TWO actions are most effective in promoting transparency in AI systems? (Choose two.)

Accepted Answer

Provide a model card that describes the purpose, accuracy, and limitations of the AI model.. Options B and C are correct. Option A is wrong because hiding the data sources reduces transparency. Option D is wrong as it relates to privacy, not transparency. Option E is wrong because publishing details without context can be confusing.

Answer

Publish the entire source code of the model online.

Answer

Withhold the data sources used for training to protect the company's competitive advantage.

Answer

Encrypt all customer data used in the model.

Question 6

A health app collects users' location data for AI-driven recommendations, but users are not informed about this data collection. Which ethical principle is most compromised?

Accepted Answer

Data minimization and consent. Option A is correct: Data minimization and consent require that only necessary data is collected with permission. Option B is wrong because transparency involves disclosure, but the deeper issue is unauthorized collection. Option C is wrong because accountability is about responsibility. Option D is wrong because fairness is about bias.

Answer

Transparency

Answer

Fairness

Answer

Accountability

Question 7

A Salesforce admin is setting up an AI-powered lead scoring system. To ensure ethical use, what should they prioritize?

Accepted Answer

Regularly audit the model for bias and adjust scoring to ensure fairness across customer segments. Ethical AI requires fairness, accountability, and transparency. Option C (regularly auditing for bias and ensuring fair treatment across segments) is the most comprehensive approach. Option A (prioritizing highest scoring leads) may ignore bias. Option B (using default model) may inherit biases. Option D (focusing only on data volume) does not address ethical concerns.

Answer

Ensure the training data includes as many records as possible

Answer

Set the system to automatically prioritize the highest-scoring leads

Answer

Use the default model provided by Salesforce without customization

Question 8

Refer to the exhibit. An organization implements this AI fairness policy for their Einstein Prediction Builder model. What is the most significant ethical gap in this policy?

Accepted Answer

It does not specify a process for reviewing and remediating models that fail the fairness threshold. The policy lacks enforcement of human oversight or a process for when the threshold is violated. Option A (It does not specify a process for reviewing models that fail the fairness threshold) is correct because ethical AI requires accountability and remediation. Option B (Protected attributes are too few) - race and gender are key, but not the main gap. Option C (Monitoring interval) is specified. Option D (Fairness metric choice) - demographic parity is common.

Answer

It does not include enough protected attributes

Answer

The demographic parity metric is inappropriate for this use case

Answer

The monitoring schedule is too frequent

Question 9

A data scientist is building a model for credit scoring. They have access to a dataset with historical bias. What should they do?

Accepted Answer

Apply fairness constraints during training.. Option B is correct because applying fairness constraints during training helps mitigate bias. Option A is wrong using biased data as is perpetuates bias. Option C is wrong discarding all biased variables may remove useful information and doesn't guarantee fairness. Option D is wrong increasing model complexity can amplify bias.

Answer

Discard all biased variables.

Answer

Use the data as is because it reflects reality.

Answer

Use a more complex model to reduce bias.

Question 10

Refer to the exhibit. What does the "Status: FAIL" indicate?

Accepted Answer

The model shows a significant disparity in true positive rates across age groups.. Option B is correct because equal opportunity difference measures disparity in true positive rates across groups; a result exceeding threshold indicates significant disparity. Option A is wrong the exhibit doesn't state deployment restriction. Option C is wrong overall accuracy is not measured here. Option D is wrong the data includes age_group.

Answer

The model's overall accuracy is low.

Answer

The data is missing age_group information.

Answer

The model is not allowed for deployment.

Question 11

A retail company deploys an AI system that adjusts prices dynamically based on customer browsing history. The system charges higher prices to returning customers. This practice is known as:

Accepted Answer

Unfair price discrimination. Option D is correct because price discrimination based on customer data is unfair and often unethical. Option A is wrong because personalization is about tailoring experience, not price gouging. Option B is wrong as dynamic pricing is legal but can be unethical. Option C is wrong because transparency issue is secondary.

Answer

Lack of transparency

Answer

Personalization

Answer

Dynamic pricing

Question 12

A company wants to ensure their AI is fair. Which TWO steps are appropriate?

Accepted Answer

Test model performance on different demographic groups. Options B and D are correct. Testing the model on different demographic groups helps identify disparities, and involving diverse stakeholders brings multiple perspectives. Option A is wrong because removing all sensitive attributes may not eliminate bias due to proxy features. Option C is wrong because a single metric cannot capture all fairness aspects. Option E is wrong because deploying quickly without testing can exacerbate unfairness.

Answer

Use a single fairness metric to evaluate the model

Answer

Deploy the model quickly to gather real-world data

Answer

Remove all sensitive attributes from the data

Question 13

A team is developing a chatbot for customer service. To ensure ethical AI, which practice should be incorporated?

Accepted Answer

Allow the chatbot to escalate to a human agent upon request.. Option A is correct because human escalation supports accountability and user control. Option B is wrong because indefinite data storage violates privacy. Option C is wrong because mimicking emotions may deceive users. Option D is wrong because a single data source may introduce bias.

Answer

Store all conversation data indefinitely for analysis.

Answer

Use a single data source for training to avoid inconsistency.

Answer

Design the chatbot to mimic human emotions perfectly.

Question 14

A company uses Salesforce Einstein to build an AI model that predicts customer churn. The model is trained on historical data from the past two years. During testing, the model shows significantly higher accuracy for male customers compared to female customers. What is the most ethical course of action?

Accepted Answer

Investigate the cause of the disparity, retrain the model with more representative data, and re-evaluate fairness.. Option B is correct because investigating and retraining the model to reduce bias is the ethical approach. Option A is wrong because ignoring the disparity could lead to unfair treatment. Option C is wrong because immediately deploying without correction is irresponsible. Option D is wrong because manually adjusting predictions introduces new biases.

Answer

Deploy the model but add a disclaimer that it may be less accurate for female customers.

Answer

Deploy the model as is, because it still meets the overall accuracy threshold.

Answer

Manually adjust the model's output to ensure equal churn predictions across genders.

Question 15

Which TWO are best practices for mitigating bias in AI models when using Salesforce Einstein? (Choose two.)

Accepted Answer

Use diverse and representative training data that reflects the target population.. Options A and D are correct. Option B is wrong because convenience sampling can introduce bias. Option C is wrong because ignoring small groups can perpetuate bias. Option E is wrong because focusing only on high-accuracy groups may sacrifice fairness.

Answer

Exclude demographic features that have small sample sizes to avoid statistical noise.

Answer

Prioritize accuracy for the majority group to maximize overall performance.

Answer

Rely on convenience sampling to quickly gather a large dataset.