Measuring Sustainability with AI

Wei Jiang (), Meng Wang and Baozhong Yang ()
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Wei Jiang: Emory University
Meng Wang: University of South Florida
Baozhong Yang: Georgia State University

A chapter in Artificial Intelligence, Finance, and Sustainability, 2024, pp 33-57 from Springer

Abstract: Abstract Measuring the ESG exposure and performance of companies is crucial in the realm of climate finance and the sustainable economy. Various stakeholders, including retail and institutional investors, corporations, and regulators rely on various ESG measures and ratings to inform their investments, managerial, and regulatory policies for sustainable development. With the advancement of artificial intelligence (AI) and natural language processing (NLP) models, researchers can now develop new ESG measures through the analysis of textual data, for example, in financial disclosures and media reports. These measures can be calculated in real time and provide essential information to the market that complements traditional ESG ratings. In this chapter, we summarize and review AI and NLP methodologies that generate new measures of firms’ ESG exposure in the recent literature, along with the research findings leveraging such measures. We present in detail an application of large language models (LLMs) in classifying specific versus general corporate ESG discussions. Finally, we discuss potential avenues for future research within this domain.

Keywords: ESG; Climate change; Sustainability; Artificial intelligence; Machine learning; Textual analysis; Natural language processing; ChatGPT; Large language models (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-66205-8_3

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DOI: 10.1007/978-3-031-66205-8_3

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