Flexibility and Adaptability CT-AI Practice Questions (Page 5)

Questions 21–25

1. 21application · medium

   A team is developing an AI system for a smart home that controls lighting based on user presence. The system currently uses fixed rules. The team wants the system to also adjust to seasonal changes in daylight hours. Which statement best distinguishes flexibility from adaptability in this context?

   • AFlexibility is about robustness to errors, while adaptability is about handling new inputs.
   • BFlexibility would require the system to be retrained, while adaptability would allow it to use existing rules.
   • CFlexibility and adaptability are synonymous in this context.
   • DFlexibility would allow the system to handle different daylight conditions using its existing rules, while adaptability would require the system to learn from new data.
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2. 22foundation · easy

   Which of the following is a scenario where an AI system must adjust its behavior or outputs in response to changing conditions?

   • AA weather forecasting model that is retrained every year with new historical data.
   • BA recommendation system that builds a new user profile from scratch for each new user.
   • CA spam filter that is updated with new spam patterns every month.
   • DA navigation app that recalculates the route when the user takes a wrong turn.
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4. 23application · medium

   A weather forecasting AI system is used by an agricultural company to advise farmers on irrigation. The system must adapt to changing climate patterns to remain accurate. Why is adaptability critical for this system?

   • ABecause the system must be robust to sensor failures.
   • BBecause climate patterns change over time, and the system must update its models to maintain accuracy.
   • CBecause the system must handle variations in input data formats from different weather stations.
   • DBecause the system must provide explanations for its forecasts to farmers.
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5. 24foundation · easy

   Which trade-off is most commonly associated with making an AI system highly flexible?

   • AIncreased flexibility often improves the system's explainability because it can handle more cases.
   • BIncreased flexibility often increases the system's reliability because it can handle more inputs.
   • CIncreased flexibility often reduces the need for adaptability because it can handle all variations.
   • DIncreased flexibility may reduce the system's robustness because it may accept inputs that are outside its safe operating range.
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6. 25foundation · easy

   When testing for adaptability, which of the following is a key aspect to verify?

   • AThe system can maintain performance under adversarial attacks.
   • BThe system can update its rules or model based on feedback or new data.
   • CThe system can handle variations in input without changing its model.
   • DThe system can provide explanations for its decisions.
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