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

Harsha Perera, Sung Une Lee, Yue Liu, Boming Xia, Qinghua Lu +3 more
8/30/2024
cs.CYcs.AI

No confident code implementation found for this paper.

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{perera2024achieving,
  title  = {Achieving Responsible AI through ESG: Insights and Recommendations from Industry Engagement},
  author = {Harsha Perera and Sung Une Lee and Yue Liu and Boming Xia and Qinghua Lu and Liming Zhu and Jessica Cairns and Moana Nottage},
  year   = {2024},
  eprint = {2409.10520},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2409.10520v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2409.10520.svg)](https://codeofpaper.com/paper/2409.10520)

Discussion