Knowledge check

Quiz

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Evaluate your understanding of this unit

Questions span sustainability definitions, environmental levers, data practices, lifecycle integration and governance.

Compare your output to the solution example provided. What did you do well? Where could you improve?Considering the ethical data management issues and solutions discussed in this exercise, how might you apply these principles to your own role and the specific industry you work in (or plan to work in)?

A) Reduce training time to improve AI performance.B) Ensure AI models operate indefinitely without updates.C) Balance AI performance with ethical, environmental and governance considerations.D) Focus only on reducing the cost of AI training.

Which of the following is NOT a sustainable design principle for ML development?

A Developing energy-efficient models.B) Using transfer learning to minimise redundant computation.C) Maximising dataset size to improve accuracy.D. Implementing modular AI architectures for long-term adaptability.

How can organisations measure and monitor the sustainability of their AI models?

A) Tracking energy consumption and emissions generated during model training.B) Ensuring AI models operate indefinitely without retraining.C) Prioritising model accuracy over efficiency.D) Using only cloud-based solutions to reduce hardware waste.

What is a key benefit of applying ESG principles to AI development?

A) Ensuring AI systems comply with environmental, social and governance standards.B) Eliminating the need for AI ethics audits.C) Reducing all AI model energy consumption to zero.D) Avoiding regulatory oversight by implementing AI models quickly.

Which of the following is an example of a sustainable AI improvement strategy?

A) Conducting periodic assessments to identify energy inefficiencies.B) Training larger models to ensure the highest possible accuracy.C) Using only on-premise servers for AI processing.D) Avoiding model retraining to save energy.

What is the main advantage of using modular AI architectures for sustainable ML?

A) They allow incremental updates without retraining the entire model.B) They require less data labelling.C) They eliminate the need for model monitoring.D) They increase model complexity to enhance accuracy.

Which of the following strategies helps organisations stay informed about AI sustainability?

A) Participating in AI sustainability conferences and research initiatives.B) Avoiding regulatory updates to maintain development speed.C) Relying only on internal data without external benchmarking.D. Prioritising model complexity over efficiency.

How can a company drive organisational change for sustainable AI adoption?

A) Encouraging cross-functional collaboration between AI engineers, compliance teams and sustainability experts.B) Training models indefinitely to maximise accuracy.C) Avoiding discussions on AI ethics to streamline development.D) Only considering sustainability after deployment.

Why is a sustainability action plan important for AI development?

A) It provides a structured approach to integrating sustainability into AI workflows.B) It eliminates the need for AI monitoring.C) It allows AI models to run indefinitely without updates.D) It prioritises model speed over energy efficiency.

What is one benefit of tracking AI model energy consumption?

A) It helps organisations identify opportunities to improve efficiency.B) It ensures AI models never require additional computing power.C) It eliminates the need for compliance with sustainability regulations.D) It guarantees that AI models will always be carbon neutral.

Action item: Knowledge check

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