Ethical Considerations of AI

A company uses Einstein Prediction Builder to recommend products. They notice the model often recommends high-priced items to users in affluent areas, potentially excluding others. What should the AI Associate do first?

An AI Associate deploys an Einstein Bot that uses sentiment analysis to escalate frustrated customers. After launch, the bot escalates disproportionately for non-native English speakers. What is the most likely cause?

A sales team uses Einstein Lead Scoring. They notice the model gives low scores to leads from certain industries. The AI Associate suspects bias. What should they do to validate?

An AI Associate is asked to build a model that predicts employee performance. The dataset includes gender, department, and tenure. Which practice could introduce ethical risk?

A financial services firm uses Einstein Next Best Action to offer credit products. The model recommends high-interest loans more often to minority groups. The AI Associate must mitigate this. What is the most effective approach?

A company's Einstein Sentiment model is used to flag negative customer feedback. The model was trained on English reviews only. When deployed globally, it misclassifies positive reviews in Spanish as negative. What is the primary ethical concern?

Which TWO actions help ensure transparency in AI systems according to Salesforce's ethical AI guidelines?

Which THREE factors should an AI Associate consider when evaluating a model for potential bias?

Which TWO practices are recommended when using AI for automated decision-making in hiring?

An AI Associate reviews the Lead Scoring model exhibit. What is the primary ethical concern with this model?

A healthcare organization is deploying an AI model to predict patient readmission risk. The model was trained on historical data that underrepresented minority populations. During testing, the model shows lower accuracy for those groups. What should the data scientist do first?

A financial institution uses an AI system to approve loan applications. The system denies loans to applicants from certain postal codes at a higher rate. The model includes 'postal code' as a feature. Which ethical consideration is most directly violated?

A company is developing a chatbot for customer service. They want to ensure the bot does not generate offensive responses. Which practice should they implement?

A credit scoring AI uses 50 features including zip code, age, and income. The model has high accuracy but denies credit disproportionately to a protected group. An audit reveals that zip code is a proxy for race. What is the best course of action?

A company wants to deploy an AI system that makes hiring decisions. To comply with ethical guidelines, what should they do before deployment?

An AI system used for medical diagnosis has been shown to have lower accuracy for certain ethnic groups. The development team is considering releasing it anyway because most patients are from the majority group. Which ethical principle is most compromised?

Which TWO actions best promote transparency in an AI system?

Which THREE factors should be considered when evaluating the fairness of an AI model?

Which TWO practices help ensure accountability in AI systems?

Refer to the exhibit. The fairness evaluation shows a disparate impact of 0.85, equal opportunity difference of 0.12, and demographic parity difference of 0.18. Which fairness thresholds are violated?

Refer to the exhibit. What is the most likely cause of the fairness issue?

A company is deploying an AI-powered chatbot to handle customer service inquiries. The bot uses historical chat data for training. Which ethical consideration is MOST important to address before deployment?

A healthcare provider uses an AI model to predict patient readmission risk. The model is trained on historical data that underrepresents minority populations. What is the MOST significant ethical risk?

A company is designing an AI system to screen job applicants. To ensure fairness, which practice should be implemented?

An AI system is used to approve loan applications. The model uses income, zip code, and credit score as features. What is a potential ethical concern?

A company deploys an AI recommender system that personalizes content. The system is trained on user click data. After deployment, the company notices that the system increasingly recommends sensationalist content, leading to user polarization. Which principle is being violated?

An AI model for predicting employee performance is found to have a higher false positive rate for women than for men. What is the best course of action?

A nonprofit uses an AI system to allocate resources to communities in need. The system uses historical data which shows that certain neighborhoods have lower service usage. What ethical risk should be considered?

A company is developing an AI system to assist with hiring. Which TWO practices are essential for ethical AI deployment?

An AI system is used to detect fraud in financial transactions. Which THREE steps should be taken to address ethical concerns?

Refer to the exhibit. A company uses an AI model for loan approvals. The error log shows a drift warning for a specific zip code, followed by a retraining failure due to insufficient data. What is the MOST ethical concern?

A financial institution deploys an AI system to recommend investment portfolios to retail clients. The system uses reinforcement learning to maximize returns based on client risk profiles. After six months, an internal audit reveals that the system has been consistently recommending high-risk, high-commission products to elderly clients with low risk tolerance, resulting in significant financial losses for those clients. The system's training data included historical transactions, which showed that elderly clients were less likely to complain or switch advisors. The institution's AI ethics policy mandates fairness, transparency, and accountability. The system currently provides no explanations for its recommendations, and there is no human oversight process. The compliance team needs to remediate the situation. Which course of action BEST addresses the ethical violations?

A global retail company deploys an AI-powered chatbot for customer service. The chatbot uses natural language processing to understand and respond to customer inquiries. After deployment, the company notices that the chatbot consistently provides less accurate and less helpful responses to customers from non-English-speaking regions, particularly those using dialects or slang. The company's data science team trained the model primarily on English-language customer service transcripts from the US and UK. The AI Ethics team has raised concerns about fairness and potential bias. The company wants to address this issue while maintaining overall performance and minimizing cost. Which action should the company take first?

A healthcare provider uses an AI system to predict patient readmission risk. The system was trained on historical data from the past five years, during which the hospital served a predominantly urban population. Recently, the hospital expanded to rural areas with different demographic and socioeconomic profiles. The AI predictions have been less accurate for rural patients, leading to misallocation of care resources. The AI Ethics committee is reviewing the system for potential bias. The model outputs a risk score from 0 to 100. The data science team has identified that the model uses features such as income, distance from hospital, and insurance type, which may correlate with race and socioeconomic status. The team wants to make the model fairer without retraining from scratch. Which approach best balances fairness and predictive accuracy?

A financial services company deploys an AI system to approve small business loans. The system uses a deep neural network trained on historical loan data. After deployment, an internal audit reveals that the approval rate for minority-owned businesses is 15% lower than for non-minority-owned businesses with similar financial profiles. The company's AI Ethics policy requires that AI systems be fair and transparent. The data science team has access to the training data, model architecture, and feature importance scores. The company wants to understand why the disparity exists and take corrective action. Which approach should the team take first?

A company uses an AI model to screen job applicants. They discover the model is rejecting candidates from a certain demographic at a higher rate. Which ethical principle is most clearly violated?

A Salesforce admin implements Einstein Bots for customer service. To ensure the bot does not use biased language, what should the admin do?

A company uses Einstein Prediction Builder to predict customer churn. They notice the model is less accurate for a certain segment. What is the best approach to mitigate bias?

A user asks an AI assistant to generate content that may be offensive. What should the AI do?

A company deploys an AI system that makes decisions about loan approvals. For transparency, what should they provide to applicants?

An AI model predicts employee performance. The HR team uses it to identify high-potential employees. What is a potential ethical risk?

A Salesforce customer uses Einstein Sentiment Analysis to analyze customer feedback. They find the model is less accurate for non-English languages. What ethical concern does this raise?

A developer creates a custom AI model using Salesforce's AI platform. They want to ensure the model is fair. What should they do first?

An organization uses Einstein Discovery to analyze survey data. The model reveals a correlation between age and satisfaction. What is the responsible use of this insight?

A company wants to ensure their AI model complies with ethical guidelines. Which TWO actions are essential? (Choose two.)

An AI system used for recruitment has been found to be biased. Which THREE steps should be taken to address this? (Choose three.)

A Salesforce administrator deploys an Einstein Bot. Which TWO ethical considerations should be addressed? (Choose two.)

Refer to the exhibit. Based on the JSON policy for AI fairness checks, which fairness metric is NOT enabled?

Refer to the exhibit. An AI model's accuracy is shown for four demographic groups. Which group should be investigated for potential bias?

Refer to the exhibit. This JSON snippet is from the Einstein Trust Layer configuration. What is the purpose of this configuration?

A company uses Einstein Prediction Builder to score leads. The model systematically gives lower scores to leads from a particular geographic region, even though those leads often convert. Which action should the company take to address this ethical concern?

An admin wants to use Einstein Reply Recommendations in Service Cloud. Which ethical consideration is most important to implement before enabling the feature?

A company uses Einstein GPT to generate email responses. They want to automatically audit generated responses for potentially harmful or biased language before sending. Which Salesforce feature should they use?

Which two actions are consistent with Salesforce's ethical AI principles when deploying a custom AI model on Salesforce?

Refer to the exhibit. A Salesforce developer configures the Einstein Trust Layer as shown. What is the primary purpose of enabling data masking?

A developer is creating a custom AI model on Salesforce. To ensure the model is fair across demographic groups, which activity should be included in the development process?

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?

According to Salesforce's AI ethics principles, which three pillars should guide the development of AI applications?

Refer to the exhibit. An admin sees this error in the Einstein activity log. What is the most likely cause?

A company wants to use Einstein Vision for product categorization. To ensure ethical use, they should:

A Salesforce admin is configuring Einstein Search for an organization with users in multiple countries. Which ethical consideration is most important?

To comply with Salesforce's AI ethics principles when using Einstein Bots, which two practices should be implemented?

Refer to the exhibit. A company configures a Prompt Builder policy for Einstein GPT. What is the primary role of the 'checkPromptOutput' flag?

A user asks an Einstein chatbot 'What is my current account balance?' The chatbot has been trained on transactions but is not supposed to reveal account data. Which ethical principle is at risk?

A company uses Einstein Analytics to predict employee performance and identifies low-performing employees with high confidence. What is a potential ethical concern?

A sales team uses Einstein Lead Scoring. They notice leads from certain industries are always low-scored. What should they do?

Which THREE are key ethical considerations for AI according to Salesforce?

A Salesforce admin wants to deploy an Einstein bot that uses natural language processing. Which practice best ensures ethical use?

A data scientist is training a model to predict customer churn. To ensure fairness, what should the data scientist do?

Refer to the exhibit. A Salesforce admin is reviewing an AI model's fairness report. Which action should the admin take?

An AI system used for medical diagnosis occasionally produces incorrect results. A doctor notices the errors but continues using the system without reporting them. Which ethical principle is primarily at risk?

An AI system for hiring is deployed. After six months, the HR team notices that the model's recommendations closely mimic past human hires, which were biased. The team wants to correct this. What should be their first step?

Refer to the exhibit. An AI loan approval policy is defined as a JSON rule set. Which ethical issue is most prominent based on this policy?

When implementing AI in Salesforce, which practice best supports the ethical principle of transparency?

A company deployed an AI chatbot for customer service. After a week, they receive complaints that the chatbot responds differently based on customer accent. The ethical issue is most likely due to:

A company's Einstein Discovery model for customer lifetime value shows a significant correlation between predicted value and customer's postal code. The company is concerned about ethical implications. What is the most appropriate response?

A company is deploying an AI-powered chatbot for customer service. The chatbot is trained on historical support tickets. Which ethical consideration is MOST important to address before deployment?

Which TWO actions are essential for ensuring transparency in an AI system? (Choose two.)

Which THREE strategies can help mitigate bias in an AI model? (Choose three.)

Which THREE components are essential for an ethical AI governance framework within a large enterprise?

A financial services firm deployed an AI model to automate loan approvals. The model was trained on historical loan data from the past 10 years, which shows that applicants from certain zip codes have higher default rates. After six months, the company's compliance team receives complaints that applicants from predominantly low-income neighborhoods are being rejected at a much higher rate than applicants from affluent areas, even when their financial profiles are similar. The model's overall accuracy remains high (95%), and the loan default rate has decreased by 15% since deployment. The company wants to address the ethical concerns without sacrificing performance. Which course of action should the company take?

A social media platform uses an AI model to automatically detect and remove hate speech. The model uses natural language processing and was trained on public posts. Recently, an internal audit reveals that the model removes posts from minority ethnic groups at a rate 3 times higher than from majority groups, even when the content is similar. The model achieves high precision and recall on the test set. The platform's content moderation team is overwhelmed with appeals. The company wants to maintain a safe environment while being fair. Which approach best addresses both goals?

An insurance company uses an AI model to set auto insurance premiums. The model uses factors including driving history, age, and ZIP code. A regulator finds that premiums in certain low-income neighborhoods are significantly higher than in affluent neighborhoods with similar risk profiles. The company's actuaries argue that the model is actuarially sound because it accurately predicts claims based on historical data. The company wants to comply with ethical guidelines and avoid legal action. Which action should they take?

A government agency uses an AI system to allocate resources for public services such as healthcare and education. The system is designed to optimize overall efficiency based on historical usage data. After deployment, it becomes clear that underserved regions with less historical data receive significantly less funding than well-served regions. The agency's mission is to promote equity. The system's performance metrics show high efficiency, but community leaders protest the unfair distribution. What should the agency do?

An organization uses an AI-powered resume screening tool to shortlist candidates for a software engineering role. The tool was trained on historical hiring data from the past five years, during which the company predominantly hired male candidates. After deployment, the tool consistently ranks female candidates lower, even when they have equivalent qualifications. The AI team reports that the overall model accuracy is 92%, and they argue that performance is strong. However, the diversity and inclusion team raises ethical concerns about gender bias. The Salesforce AI Associate is asked to evaluate the situation. What should the associate recommend?