Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework
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arXiv
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| Auteurs principaux: | , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909280372785152 |
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| author | Lee, Sung Une Perera, Harsha Liu, Yue Xia, Boming Lu, Qinghua Zhu, Liming Cairns, Jessica Nottage, Moana |
| author_facet | Lee, Sung Une Perera, Harsha Liu, Yue Xia, Boming Lu, Qinghua Zhu, Liming Cairns, Jessica Nottage, Moana |
| contents | Artificial Intelligence (AI) is a widely developed and adopted technology across entire industry sectors. Integrating environmental, social, and governance (ESG) considerations with AI investments is crucial for ensuring ethical and sustainable technological advancement. Particularly from an investor perspective, this integration not only mitigates risks but also enhances long-term value creation by aligning AI initiatives with broader societal goals. Yet, this area has been less explored in both academia and industry. To bridge the gap, we introduce a novel ESG-AI framework, which is developed based on insights from engagements with 28 companies and comprises three key components. The framework provides a structured approach to this integration, developed in collaboration with industry practitioners. The ESG-AI framework provides an overview of the environmental and social impacts of AI applications, helping users such as investors assess the materiality of AI use. Moreover, it enables investors to evaluate a company's commitment to responsible AI through structured engagements and thorough assessment of specific risk areas. We have publicly released the framework and toolkit in April 2024, which has received significant attention and positive feedback from the investment community. This paper details each component of the framework, demonstrating its applicability in real-world contexts and its potential to guide ethical AI investments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_00965 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework Lee, Sung Une Perera, Harsha Liu, Yue Xia, Boming Lu, Qinghua Zhu, Liming Cairns, Jessica Nottage, Moana Artificial Intelligence Artificial Intelligence (AI) is a widely developed and adopted technology across entire industry sectors. Integrating environmental, social, and governance (ESG) considerations with AI investments is crucial for ensuring ethical and sustainable technological advancement. Particularly from an investor perspective, this integration not only mitigates risks but also enhances long-term value creation by aligning AI initiatives with broader societal goals. Yet, this area has been less explored in both academia and industry. To bridge the gap, we introduce a novel ESG-AI framework, which is developed based on insights from engagements with 28 companies and comprises three key components. The framework provides a structured approach to this integration, developed in collaboration with industry practitioners. The ESG-AI framework provides an overview of the environmental and social impacts of AI applications, helping users such as investors assess the materiality of AI use. Moreover, it enables investors to evaluate a company's commitment to responsible AI through structured engagements and thorough assessment of specific risk areas. We have publicly released the framework and toolkit in April 2024, which has received significant attention and positive feedback from the investment community. This paper details each component of the framework, demonstrating its applicability in real-world contexts and its potential to guide ethical AI investments. |
| title | Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2408.00965 |