ISO 42001:2023 Artificial Intelligence Management System Foundation Quiz 02 24Mar25 - Practice Quiz

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Question 1 of 30

InnovAI Solutions, an AI development firm, is implementing ISO 50003:2021 to certify its AI-driven energy management system (EnMS) designed to optimize energy consumption in large data centers. Due to recent upgrades and the integration of the AI system, the historical energy consumption data is limited and considered unreliable. The historical data predates the AI implementation and major infrastructure changes. The Chief Sustainability Officer, Dr. Anya Sharma, needs to determine the most appropriate method for establishing initial energy baselines as required by ISO 50003:2021. Dr. Sharma understands that the baseline will be used to measure the effectiveness of the AI-driven EnMS. Considering the limited and unreliable historical data, which approach aligns best with the principles of ISO 50003:2021 for establishing energy baselines?

Establish an initial baseline using statistical analysis of the available historical data, acknowledging its limitations, and then iteratively refine the baseline as more reliable data becomes available from the AI-driven system, incorporating normalization techniques to account for operational variations.

Rely solely on expert opinions from energy consultants to estimate the baseline energy consumption, documenting the assumptions made, and deferring data-driven validation until a later stage.

Postpone establishing any energy baseline until a full year of data is collected from the AI-driven system, ensuring a comprehensive dataset before making any assumptions about energy performance.

Extrapolate the limited historical data using linear regression to project future energy consumption, assuming that the operational changes introduced by the AI system will have a negligible impact on overall energy use.

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