Achieving Responsible AI through ESG: Insights and Recommendations from Industry Engagement

• URL: http://arxiv.org/abs/2409.10520v1
• Date: Fri, 30 Aug 2024 05:48:03 GMT
• Title: Achieving Responsible AI through ESG: Insights and Recommendations from Industry Engagement
• Authors: Harsha Perera, Sung Une Lee, Yue Liu, Boming Xia, Qinghua Lu, Liming Zhu, Jessica Cairns, Moana Nottage,
• Abstract summary: This study examines how leading companies align Responsible AI (RAI) with their Environmental, Social, and Governance (ESG) goals. We identify a strong link between RAI and ESG practices, but a significant gap exists between internal RAI policies and public disclosures. We provide recommendations to strengthen RAI strategies, focusing on transparency, cross-functional collaboration, and seamless integration into existing ESG frameworks.
• Score: 15.544366555353262
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: As Artificial Intelligence (AI) becomes integral to business operations, integrating Responsible AI (RAI) within Environmental, Social, and Governance (ESG) frameworks is essential for ethical and sustainable AI deployment. This study examines how leading companies align RAI with their ESG goals. Through interviews with 28 industry leaders, we identified a strong link between RAI and ESG practices. However, a significant gap exists between internal RAI policies and public disclosures, highlighting the need for greater board-level expertise, robust governance, and employee engagement. We provide key recommendations to strengthen RAI strategies, focusing on transparency, cross-functional collaboration, and seamless integration into existing ESG frameworks.

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