Describe How AI Is Used in Varied Industries CERTIFIED-AI-EXPERT Practice Questions (Page 4)

Questions 16–20

1. 16foundation · easy

   Which of the following is a key business benefit that AI adoption can bring to the retail industry?

   • AImproved customer experience through personalized recommendations
   • BGuaranteed increase in profit margins
   • CElimination of all manual labor in warehouses
   • DReduced need for regulatory compliance
   Reveal Solution Discussion Select an answer first
2. 17expert · hard

   A government agency wants to use AI to automate the review of public comments on proposed regulations. The agency receives thousands of comments, many of which are form letters or duplicates. The goal is to identify unique, substantive comments that require a response. The agency has strict data governance requirements and must ensure the AI system is transparent and auditable. Which approach best meets the agency's needs?

   • AUse a text classification model to categorize comments by topic and sentiment, and then manually review the categories.
   • BUse a deep learning model to rank comments by importance and automatically respond to the top-ranked comments without human review.
   • CUse a large language model (LLM) to summarize all comments and generate a single report for the agency's review.
   • DUse a clustering algorithm to group similar comments, then use a rule-based filter to remove duplicates and form letters, and finally have staff review the remaining unique comments.
   Reveal Solution Discussion Select an answer first
4. 18expert · hard

   A bank wants to implement an AI system to automate loan approval decisions. The bank must comply with fair lending laws, which prohibit discrimination based on race, gender, or other protected attributes. The data scientists have built a model with high accuracy, but they are concerned about bias. The bank's legal team requires that the model's decisions be explainable and that any potential bias be identified and mitigated. Which approach best addresses the bank's compliance and fairness requirements?

   • AUse a fairness-aware machine learning framework to detect and mitigate bias during model training, and use explainable AI techniques to document decisions.
   • BRemove all protected attributes from the dataset and assume the model will be fair since it cannot directly see race or gender.
   • CUse a black-box model and hire a third-party auditor to review a sample of decisions for fairness after deployment.
   • DDeploy the model as-is and rely on its high accuracy, since the model was trained on historical data that reflects past lending decisions.
   Reveal Solution Discussion Select an answer first
5. 19expert · hard

   A hospital wants to implement an AI system to predict patient deterioration in the ICU. The system will use real-time vital signs and lab results to alert staff. The hospital has a small data science team and limited IT resources. The system must be reliable and available 24/7, and any downtime could have serious consequences. Which implementation strategy best balances the need for reliability with the limited resources?

   • AOutsource the entire AI system to a third-party vendor and have them manage the model and infrastructure remotely.
   • BUse a cloud-based AI service from a major vendor that offers a managed prediction API with built-in high availability and automatic scaling.
   • CBuild a custom AI model in-house and deploy it on the hospital's own servers with a basic monitoring setup.
   • DDeploy an open-source AI model on a single on-premises server and have IT staff manually restart it if it fails.
   Reveal Solution Discussion Select an answer first
6. 20application · medium

   A media streaming company wants to reduce customer churn by identifying subscribers who are likely to cancel. They have data on viewing history, subscription length, and customer support interactions. The company wants to proactively offer discounts or personalized content to at-risk subscribers. Which AI use case directly supports this goal?

   • AA recommendation system that suggests new content to all subscribers to increase overall engagement.
   • BA churn prediction model that scores each subscriber's likelihood of cancellation based on their usage and interaction history.
   • CA customer segmentation model that groups subscribers by demographics and viewing preferences.
   • DA sentiment analysis model that analyzes customer support chat logs to gauge overall satisfaction.
   Reveal Solution Discussion Select an answer first