Summary of Integrating Esg and Ai: a Comprehensive Responsible Ai Assessment Framework, by Sung Une Lee et al.
Integrating ESG and AI: A Comprehensive Responsible AI Assessment Framework
by Sung Une Lee, Harsha Perera, Yue Liu, Boming Xia, Qinghua Lu, Liming Zhu, Jessica Cairns, Moana Nottage
First submitted to arxiv on: 2 Aug 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel ESG-AI framework is introduced, comprising three key components that provide a structured approach to integrating environmental, social, and governance considerations with artificial intelligence (AI) investments. The framework, developed through engagements with 28 companies, aims to mitigate risks and enhance long-term value creation by aligning AI initiatives with broader societal goals. It provides an overview of the environmental and social impacts of AI applications, enabling investors to assess materiality and evaluate a company’s commitment to responsible AI. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI is becoming increasingly important across many industries, but investing in it without considering its impact on the environment and society can be risky. To make sure AI investments are ethical and sustainable, a new framework is being introduced that combines environmental, social, and governance considerations with AI. This framework was created by working with 28 companies and provides a structured approach to making responsible AI investments. It helps investors understand how AI affects the environment and society, so they can make informed decisions. |
