A new position paper argues that evaluating the environmental impact of AI systems requires a comprehensive life cycle assessment approach. Current methods that focus solely on training or inference costs are insufficient due to the increasing complexity of AI development and deployment pipelines. The paper advocates for incorporating all costs, from hardware manufacturing to operational use, to accurately gauge AI's resource utilization and downstream effects. AI
IMPACT Establishes a framework for more accurate AI environmental cost accounting, potentially influencing future development practices and policy.
RANK_REASON This is a research paper discussing a methodology for evaluating AI resource utilization. [lever_c_demoted from research: ic=1 ai=1.0]
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