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 healthcare organization uses Einstein Discovery to predict patient readmission risk. The model uses protected attributes like race and age as features. Which action best aligns with Salesforce's ethical AI principles?

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?

An AI Associate reviews the bot configuration and test results. Which action best addresses the ethical issue?

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?

An AI system recommends job candidates to recruiters. The system was trained on resumes of past successful hires, most of whom were male. As a result, it consistently ranks female candidates lower. What is the most appropriate mitigation?

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 team is deploying an AI model for credit scoring. The model uses a complex neural network with high accuracy. The team has performed bias testing and used a representative dataset. According to the policy, what is the MOST significant ethical gap?

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 company uses an AI model to screen job candidates. They discover the model is rejecting candidates from certain zip codes. What should they do first?

A Salesforce admin wants to use Einstein Prediction Builder to predict customer churn. What ethical consideration is most important?

A company deploys an AI chatbot for customer service. After training on historical chats, the chatbot frequently gives incorrect answers to minority language queries. What is the likely cause?

An organization uses Einstein Recommendation Builder to suggest products. They want to ensure recommendations are fair across demographics. Which action should they take?

A healthcare company uses AI to predict patient readmission rates. What is a critical ethical requirement?

A financial institution uses AI for loan approvals. They notice the model is denying loans to women more often. After retraining with balanced data, the disparity persists. What is the next best step?

A company uses AI to monitor employee productivity. Employees feel surveilled. What ethical principle is being violated?

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

An AI system for medical diagnosis is trained on data from one region. When deployed globally, it performs poorly. This is an issue of?

Which TWO actions align with ethical AI practices in Salesforce?

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

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

Refer to the exhibit. A company uses this policy for a customer-facing AI model. What is the most critical ethical risk?

Refer to the exhibit. What action should be taken?

Refer to the exhibit. Which ethical principle is violated?

A company uses an AI model to screen job applications. They discover the model is less likely to recommend female candidates. What should the company prioritize first?

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?

A company deploys an AI system that recommends loan amounts. They want to ensure explainability. Which approach best aligns with ethical AI?

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

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

A financial institution uses an AI model to approve credit. The model shows disparate impact against a protected group. Under Salesforce's ethical AI principles, what is the most appropriate action?

A company uses Einstein's predictive lead scoring. The model inadvertently overweights leads from certain geographic regions. Which action aligns with Salesforce's Responsible AI principles?

An organization is deploying an AI system for loan decisions. They want to ensure human oversight. Which is the best implementation?

Which TWO practices contribute to ethical AI transparency?

Which THREE actions align with Salesforce's responsible AI principles?

Which TWO are best practices for mitigating bias in AI models?

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

Refer to the exhibit. An administrator runs an audit on a sentiment analysis model. What is the primary ethical concern?

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

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?

A retail company wants to use Einstein AI to personalize marketing offers. They plan to include customer purchase history and demographic data. What is the essential first step to ensure ethical use of customer data?

A financial institution deploys an AI model to approve loan applications. The model uses features like income, credit score, and postal code. An audit reveals that the model denies loans at a higher rate for applicants in certain postal codes, which correlate with minority neighborhoods. What should the institution do to align with ethical AI principles?

A healthcare provider uses Einstein's Prediction Builder to predict patient readmission risk. The model outputs a risk score, but clinicians do not understand how the score is calculated. According to ethical AI principles, what should the provider implement?

A company uses an AI chatbot that automatically responds to customer service inquiries. When a customer questions the bot's response, there is no mechanism for the customer to appeal or speak to a human. What ethical principle is being violated?

A company is building an AI model to score sales leads. They have a dataset with historical leads, including whether they converted. The dataset contains 90% male and 10% female leads. The model will be used to prioritize leads for sales follow-ups. What is the primary ethical concern?

A company deploys an Einstein AI model that recommends products to customers. To ensure transparency, what should the company include in the customer-facing interface?

A company wants to use Einstein OCR to extract text from uploaded documents. To protect customer privacy, what should they ensure before processing documents containing personal data?

A hospital uses an AI model to predict patient deterioration. The model was trained on data from a single hospital with a predominantly white patient population. When deployed at a hospital serving a diverse population, the model underperforms for minority groups. What is the most effective way to address this ethical issue?

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

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

Which THREE are key principles of Salesforce's AI Ethics framework? (Choose three.)

A company is developing an AI model to screen job applications. The training data is heavily skewed toward candidates from a specific demographic. What is the most important step the team should take to address potential ethical concerns?

A retail company uses AI to personalize marketing emails. A customer complains that their data was used without explicit permission. What ethical principle was most likely violated?

A financial services firm uses a deep learning model to approve loans. The model is highly accurate but cannot explain its decisions. Regulators now require the firm to provide reasons for loan denials. What is the best approach to address this ethical concern?

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?

A company launches a chatbot that interacts with customers. The chatbot does not disclose that it is an AI. Which ethical principle is most directly violated?

An autonomous vehicle AI is trained in simulation but performs poorly in rain and snow. The development team decides to deploy anyway, arguing that bad weather is rare. What ethical concern is most critical?

A social media platform's AI recommends content that inadvertently amplifies misinformation. An ethical review board is considering changes. Which of the following actions best addresses the unintended harm?

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?

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?

Which TWO of the following are considered core ethical principles in AI according to Salesforce’s AI Ethics?

Which THREE of the following are effective strategies to mitigate bias in AI models?

Which TWO of the following are required for GDPR compliance when using AI with personal data?

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?

Refer to the exhibit. An AI model audit shows performance differences across demographic groups. Which ethical concern is most critical?

Refer to the exhibit. The error log from an AI recommendation system indicates that it cannot explain a decision. Which ethical concern does this directly raise?

A company uses Einstein Prediction Builder to predict customer churn. They notice the model is less accurate for a particular demographic group. According to ethical AI principles, what should the company do first?

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

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

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 financial services company uses Einstein AI to recommend credit limits. The model tends to assign lower limits to applicants from a certain region. Which action best aligns with ethical AI practices?

A healthcare organization uses AI to prioritize patient appointments. The AI gives lower priority to patients with a specific chronic condition. To ensure ethical AI, what should the organization do?

A company is developing an AI system to screen job applications. They want to ensure compliance with ethical AI standards and avoid discrimination. Which approach demonstrates the most robust ethical governance?

A large enterprise uses multiple Salesforce AI services including Einstein Bots, Prediction Builder, and Next Best Action. They want to create a consistent ethical AI policy across all services. Which action is most effective?

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 Einstein Vision for product quality inspection. To ensure ethical use, which TWO practices should they adopt? (Choose two.)

A Salesforce admin is configuring Einstein Next Best Action. Which TWO actions demonstrate ethical AI practices? (Choose two.)

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.)

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?

Refer to the exhibit. Which ethical principle is most at risk based on this AI governance configuration?

Refer to the exhibit. Which ethical principle is most at risk with this AI model configuration?

A company deployed an AI chatbot to handle customer service. The chatbot sometimes generates responses that are biased against certain demographics. The company wants to mitigate this. What is the best first step?

A sales team uses an AI tool to prioritize leads. The tool is found to give lower scores to leads from certain regions. What ethical principle is most violated?

During model development, the data scientist realizes the training data is not representative of the intended population. What should they do?

An AI system for hiring is found to have a disparate impact on a protected class. The company is legally required to...

A company wants to use customer data to train an AI model. Which ethical consideration is paramount?

A developer notices that an AI model performs differently for different age groups. What should be done?

An organization wants to implement AI in a way that builds trust. Which practice is most important?

A company is deploying an AI system that makes recommendations to users. To ensure ethical use, they should:

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

Which TWO components are essential for an AI ethics governance framework?

Which TWO approaches are recommended for mitigating bias in AI models?

Which THREE are core principles in Salesforce's AI ethics framework?

Refer to the exhibit. The model is deployed and monitoring triggers an alert for a fairness violation. What does this indicate?

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

Refer to the exhibit. Which ethical principle is most directly violated?

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?

A Salesforce admin builds an Einstein Prediction Builder model to predict customer churn. The model assigns higher churn risk to customers in a certain demographic group. What is the MOST ethical FIRST step?

A healthcare organization uses Salesforce to manage patient records. They want to deploy an AI system that predicts patient readmission risk. Which practice BEST ensures ethical use of patient data?

A company uses Einstein Bots to handle sales inquiries. The bot sometimes provides incorrect product information, leading to customer dissatisfaction. What is the MOST ethical course of action?

A sales team uses an AI tool to recommend products to customers. The tool recommends high-commission products over what best fits the customer. Which ethical principle is being violated?

A financial institution uses Einstein Discovery to analyze loan applications. The model denies loans at a higher rate for a particular ethnicity. The data is unbiased, but the model learned societal biases. Which action BEST aligns with ethical AI practices?

A company uses Einstein Sentiment to analyze customer feedback. The tool incorrectly flags negative sentiment for customers with heavy accents. Which ethical issue is present?

A nonprofit uses Salesforce AI to prioritize outreach to donors. The model recommends contacting only high-income individuals. Which ethical principle is most compromised?

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:

A company is developing an AI system to screen job applicants. Which TWO practices are essential for ethical AI in hiring?

A healthcare provider uses AI to predict patient outcomes. Which THREE measures should be implemented to ensure ethical AI use?

A Salesforce admin is configuring Einstein Bots. Which TWO actions are essential to maintain ethical AI practices?

Refer to the exhibit. A company has the Einstein LLM policy shown. What is the primary ethical gap in this policy?

A large financial institution uses Einstein Discovery to automate loan pre-approval decisions. The model was trained on ten years of historical data. After deployment, the compliance team finds that the approval rate for minority groups is 15% lower than the majority group, even after controlling for credit score and income. The data is balanced across groups. The model uses features like zip code, employment history, and debt-to-income ratio. The institution has a strict policy of fairness and non-discrimination. The AI team proposes three options: (1) remove zip code and employment history from the model, (2) add a fairness constraint to the model training, (3) lower the decision threshold for minority groups to balance approval rates. The compliance officer must choose the most ethical and effective course of action that aligns with Salesforce AI ethical guidelines. Which option should they choose?

A global e-commerce company deploys Einstein Bots in multiple countries. The bot uses natural language processing to handle customer returns. In one region, customers frequently complain that the bot does not understand their local dialect and incorrectly rejects valid returns. The company wants to maintain consistent customer experience while respecting regional diversity. The bot's language model was trained mainly on English data from the US and UK. The AI ethics board is concerned about fairness and transparency. They consider four options: (A) use a single, centrally-trained model with fallback to human agents for non-English queries, (B) deploy separate models fine-tuned on each dialect but with centralized monitoring, (C) disable the bot in regions with dialect issues, (D) use a translation layer to convert all inputs to English before processing. What is the best ethical approach?

A healthcare company uses an AI model built on Salesforce to predict patient readmission risk. The model is trained on historical data that underrepresents certain ethnic groups. During testing, the model shows significantly higher false negative rates for those groups, meaning it fails to flag high-risk patients. The ethical concern is most directly related to which AI principle?

A financial services firm deploys an Einstein AI chatbot that provides investment advice. A customer asks why a particular recommendation was made. The chatbot is unable to provide any reasoning. Which ethical principle is most directly violated?

A Salesforce admin is configuring an AI model to automatically approve customer refunds under $50. To ensure ethical use, what is the most important action?

A retail company uses Einstein to personalize product recommendations. The AI model is trained on customer purchase data that includes sensitive attributes like race and gender. The company wants to ensure ethical use. Which action would best address fairness concerns?

A company deploys an AI system to screen job applications. The system is found to consistently reject candidates from a particular university, even though those candidates are qualified. What is the most ethical first step?

A Salesforce developer is building an AI model to predict customer churn. What is the most important ethical consideration when collecting training data?

A company uses an AI model to automate customer service responses. A customer receives an incorrect response that results in a financial loss. Who is primarily accountable for this error?

A bank uses Einstein to approve loan applications. The model is trained on data that includes zip codes. Analysis shows that applicants from low-income zip codes are disproportionately rejected, even when their credit profiles are similar. What is the most likely ethical issue?

A company is implementing an AI system to recommend marketing campaigns. To align with Salesforce's ethical AI principles, which practice is most important?

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 TWO are key principles of Salesforce's AI ethics? (Choose two.)

A large e-commerce company uses Salesforce Einstein to recommend products to customers. The AI model is trained on purchase history, browsing behavior, and demographic data including age and gender. Recently, the company received complaints that the model seems to recommend lower-priced items to female customers and higher-priced items to male customers for the same product categories. The data science team confirms the model has a statistically significant difference in recommendation value by gender. The company's ethical AI policy requires fairness, transparency, and human oversight. The compliance team is considering several actions. Which action should the company take first?

A non-profit organization uses Salesforce AI to help prioritize grant applications. The AI scores applications based on historical funding decisions, project impact, and community need indicators. After deployment, staff notices that applications from rural areas consistently receive lower scores than those from urban areas, even when project quality is similar. The organization's mission is to serve underserved communities, including rural areas. The AI model is trained on historical data that favored larger, urban projects. The ethics committee is meeting to decide next steps. What is the most appropriate action to align ethical AI with the organization's mission?

A small business uses a pre-built Salesforce AI model to predict inventory needs. The model recommends ordering extra stock based on seasonal trends. One month, the model fails to predict a sudden demand spike, resulting in stockouts and lost sales. The business owner is frustrated and considers disabling the AI. The owner wants to know if this is an ethical issue and what to do next. As an AI ethics advisor, what is the best response?

A company deployed an AI model for lead scoring. After several months, they notice that leads from certain geographic regions consistently receive higher scores than leads from other regions with similar demographic profiles. The company wants to ensure ethical AI usage. What should they do first?

A customer service department uses an AI chatbot to handle common inquiries. Recently, customers have reported that the chatbot sometimes responds with offensive or inappropriate language. The company wants to uphold ethical standards. Which approach is the best practice?

Which TWO actions are most effective for ensuring fairness in an AI model used for loan approvals?

Which TWO actions promote transparency in AI decision-making?

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 hospital uses an AI triage system to prioritize patients in the emergency department. The AI was trained on historical patient data and assigns priority scores based on vital signs and symptoms. Recently, a study finds that the system consistently assigns lower priority to elderly patients compared to younger patients with similar clinical presentations. The hospital's ethics committee is concerned about age discrimination. The current model achieves high accuracy in predicting outcomes, and doctors have come to rely on it for efficiency. What should the hospital do to address the ethical concern while maintaining clinical effectiveness?

A retail company uses an AI recommendation engine to suggest products to online shoppers. The engine uses past purchase history and browsing behavior. Recently, a customer advocacy group publishes a report showing that the engine recommends higher-priced products to customers in affluent zip codes and lower-priced products to customers in lower-income areas, even when both groups have similar browsing histories. The company's revenue has increased since implementing the engine, and marketing teams are pleased. However, the company wants to maintain a reputation for fairness. Which action should the company take?

An HR department uses an AI tool to screen resumes for a software engineering position. The tool was trained on resumes of past successful hires, who were predominantly male. The tool has been in use for three months, during which only 10% of candidates shortlisted for interviews are female, even though 40% of applicants are female. The hiring managers are satisfied with the quality of candidates shortlisted, as most perform well in interviews. However, the company's diversity and inclusion officer raises an ethical concern. What should the company do to address this bias?

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?

A university uses an AI system to predict first-year student retention. The system uses factors such as high school GPA, SAT scores, and socioeconomic indicators. After two years, administrators notice that the model consistently predicts lower retention probabilities for students from low-income families, even when their academic profiles are strong. The university's mission emphasizes equity and inclusion. The admissions office is considering using the predictions to allocate support resources. The model's accuracy on historical data is 85%. What should the university do to align with ethical AI principles?

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 news aggregator app uses an AI algorithm to personalize the news feed for each user. The algorithm selects articles based on past clicks and reading time. Recently, a study reveals that the algorithm disproportionately shows sensational and polarizing news to users from certain political orientations, while showing more neutral content to others. The company's user engagement metrics have increased, but journalists express concern about reinforcing echo chambers and misinformation. The company wants to uphold ethical standards while keeping users engaged. What should they do?

A credit scoring company develops an AI model that includes social media activity as a factor. The model awards higher scores to individuals with many online connections and consistent posting. Consumer advocates argue that this penalizes individuals with limited internet access or those who value privacy. The company defends the model, stating that it predicts creditworthiness better than traditional models. However, a regulatory body is investigating potential discrimination. The company wants to address ethical concerns without completely abandoning the model. Which approach is most appropriate?

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?

A company is implementing Salesforce Einstein AI for lead scoring. Which TWO actions align with ethical AI practices?

A retail company uses Salesforce Einstein Vision to analyze customer images for product recommendations. The AI team notices that the model performs poorly on images of customers with darker skin tones, leading to fewer recommendations for that demographic. The team has access to a dataset of diverse skin tones but the company's data privacy policy prohibits using demographic data in training. What should the team do?

A financial services firm deploys Einstein Prediction Builder to predict loan default risk. The model uses sensitive attributes like zip code and age. During testing, the model shows a disparate impact on minority neighborhoods. The compliance team requires explanation of individual predictions for regulatory audits. The data science team wants to use a complex deep learning model that is not interpretable. Which approach best balances performance and ethical responsibility?

A company has deployed an AI-powered chatbot to handle customer service inquiries. The chatbot is designed to answer frequently asked questions and escalate complex issues to human agents. Which action best aligns with ethical AI principles regarding transparency?

Refer to the exhibit. A Salesforce AI Associate is reviewing the AI model evaluation data. Which TWO ethical concerns should the associate identify?

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?