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What is the primary purpose of establishing AI ethics guidelines in an organization?

A financial services company is implementing an AI model to predict loan eligibility. During testing, they discover the model consistently denies loans to applicants from certain geographic regions. What type of AI issue does this represent?

Which principle of AI transparency requires organizations to provide clear information about how AI systems make decisions?

A healthcare organization wants to use AI to analyze patient data for diagnostic purposes. What is the MOST important ethical consideration they must address first?

What does the term 'machine learning' fundamentally describe?

An organization discovers that their AI customer service chatbot has learned to use inappropriate language from unfiltered training data. What aspect of responsible AI practices was most likely overlooked?

Which Salesforce Einstein feature uses AI to predict the likelihood of winning an opportunity?

A sales manager wants to receive AI-powered recommendations on which deals to prioritize based on their team's historical performance and current pipeline. Which Einstein feature would best address this need?

What is the primary function of Einstein Bots in the Salesforce ecosystem?

A company uses Salesforce Service Cloud and wants to automatically categorize incoming cases by topic and urgency without manual intervention. Which Einstein capability would best accomplish this?

An administrator wants to create a custom AI prediction model to forecast customer churn without writing code. Which Salesforce Einstein tool should they use?

What role does Einstein Discovery play in the Salesforce ecosystem?

A retail company wants to use Einstein Vision to analyze product images uploaded by customers. What is a prerequisite for training an effective Einstein Vision model?

Why is data quality critical for effective AI model performance?

A company has collected 10 years of customer data but wants to build a prediction model for current customer behavior. What data consideration should they prioritize?

What is the purpose of splitting data into training, validation, and test sets when building AI models?

A data scientist notices that their AI model performs exceptionally well on training data but poorly on new customer data. What issue does this indicate, and what is a potential solution?

What is feature engineering in the context of preparing data for AI models?

A healthcare provider wants to implement an AI system to recommend treatment plans based on patient histories. What is the MOST important implementation consideration?

A retail company implements an AI-powered recommendation engine on their e-commerce site. What metric would BEST indicate whether the AI implementation is delivering business value?