The Impact of Using GenAI on Energy Consumption and CO2 Emissions CT-GENAI Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   If a generative AI model consumes the same amount of electricity in two different data centers, which factor would cause the CO2 emissions to differ?

   • AThe energy mix of the local electricity grid
   • BThe programming language used to implement the model
   • CThe number of GPUs in the data center
   • DThe size of the training dataset
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2. 2foundation · easy

   When evaluating the environmental impact of using GenAI in software testing, which of the following is a key trade-off to consider?

   • AThe number of test cases versus the number of developers on the team
   • BThe cost of test automation tools versus the cost of manual testing
   • CThe energy cost of running GenAI versus the energy saved by automating test generation
   • DThe speed of test execution versus the accuracy of test results
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4. 3application · medium

   A company runs GenAI test generation in a data center powered by a mix of 60% natural gas and 40% renewables. The sustainability team wants to reduce CO2 emissions. They are considering two options: (1) improving the energy efficiency of the GenAI model to use 20% less energy, or (2) switching to a 100% renewable energy contract for the data center. Which option is more effective at reducing emissions?

   • AImproving efficiency by 20% reduces emissions by 20%
   • BNeither option reduces emissions because GenAI always produces CO2
   • CBoth options reduce emissions by the same amount
   • DSwitching to 100% renewable energy eliminates all CO2 emissions from the data center's electricity use
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5. 4application · hard

   A test team is deciding between two GenAI models for generating unit test cases. Model X is a large model that was pre-trained on a massive corpus. Model Y is a smaller model fine-tuned specifically on the team's codebase. Both produce acceptable test quality for the team's needs. The team wants to minimize the total energy footprint of using GenAI in their testing process. What should they consider?

   • AModel X is always more energy-efficient because it requires no additional training
   • BModel Y is always more energy-efficient because it is smaller
   • CModel X has lower total energy because it was pre-trained once and shared across many users
   • DModel Y likely has lower inference energy per test case, but the fine-tuning phase adds one-time training energy
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6. 5foundation · easy

   Which of the following is an example of efficient resource use to reduce CO2 emissions from GenAI in testing?

   • AUsing a larger model to ensure high-quality test cases
   • BScheduling heavy GenAI test generation during periods when renewable energy is abundant
   • CKeeping the model running continuously to avoid cold starts
   • DRunning all GenAI tasks on the default cloud region regardless of its energy mix
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