As AI/ML models, including Large Language Models, continue to scale with massive datasets, so does their consumption of undeniably limited natural resources, and impact on society. In this collaboration between AI, Sustainability, HCI and legal researchers, we aim to enable a transition to sustainable AI development by enabling stakeholders across the AI value chain to assess and quantitfy the environmental and societal impact of AI. We present the ESG Digital and Green Index (DGI), which offers a dashboard for assessing a company's performance in achieving sustainability targets. This includes monitoring the efficiency and sustainable use of limited natural resources related to AI technologies (water, electricity, etc). It also addresses the societal and governance challenges related to AI. The DGI creates incentives for companies to align their pathway with the Sustainable Development Goals (SDGs). The value, challenges and limitations of our methodology and findings are discussed in the paper.

翻译：随着包括大型语言模型在内的人工智能/机器学习模型借助海量数据集不断扩展规模，其对有限自然资源的消耗以及对社会的负面影响也日益加剧。本研究由人工智能、可持续性、人机交互及法律领域的研究人员合作开展，旨在通过帮助人工智能价值链各环节的相关方评估并量化人工智能的环境与社会影响，推动向可持续人工智能发展的转型。我们提出了ESG数字与绿色指数（DGI），该指数提供了一套仪表板，用于评估企业在实现可持续性目标方面的表现。这包括监测与人工智能技术相关的有限自然资源（如水、电力等）的利用效率及可持续性，同时也涉及人工智能相关的社会与治理挑战。DGI创建了激励机制，引导企业将其发展路径与可持续发展目标（SDGs）保持一致。本文还探讨了该方法与发现的价值、挑战及局限性。