CAN GENERATIVE ARTIFICIAL INTELLIGENCE (AI) ASSISTANTS’ EVALUATION OF ENVIRONMENTAL, SOCIAL, AND GOVERNANCE (ESG) PERFORMANCE REPLACE PROFESSIONAL EVALUATION?

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This article explores how evaluation of companies’/stocks’ environmental, social, and governance (ESG) performance by generative artificial intelligence (AI) compares with traditional, proprietary, professional evaluation, and whether the former is able to replace the latter. The generative AI assistant utilized in the underlying study was Microsoft Copilot, which was requested to accord rating scores to the three individual ESG components, namely, (1) Environmental, (2) Social, and (3) Governance of the top 40 companies/stocks among the S&P 500. The traditional, proprietary, professional evaluation of the companies’/stocks’ ESG performance for these three components adopted in this article was the rating scores by Sustainalytics of Morningstar. The correlation coefficient between Copilots’ rating score for each of these three components over the top 40 companies/stocks and the corresponding rating score from Sustainalytics was computed. Subsequently, multiple regression of Sustainalytics’s ESG Risk Rating score (i.e., a summary ESG score from Sustainalytics as the dependent variable) on Copilot’s rating scores for the three components above (as the independent variables) over the top 40 companies/stocks was performed. It was found that the correlation coefficients were respectively -.576 (p = 0.000), -.166 (p = .306), and -.171 (p = .291). The multiple regression included Copilot’s rating scores for all the three components above as the independent variables with the R2 = .441, the F-test’s F statistic = 9.486 (df = (3, 36) and p = 0.000), the respective regression coefficients being -5.886, 2.176, and -2.185 and the corresponding t-tests’ t values being -3.289 (p = 0.002), .955 (p = .346, and -1.075 (p =.290).

Original languageEnglish
Title of host publicationProceedings of the International Conferences on Applied Computing and WWW/Internet 2024
EditorsPaula Miranda, Pedro Isaias, Pedro Isaias, Luis Rodrigues
PublisherIADIS Press
Pages301-308
Number of pages8
ISBN (Electronic)9789898704627
Publication statusPublished - 2024
Event21st International Conference on Applied Computing 2024, AC 2024 and 23rd International Conference on WWW/Internet 2024, ICWI 2024 - Zagreb, Croatia
Duration: 26 Oct 202428 Oct 2024

Publication series

NameProceedings of the International Conferences on Applied Computing and WWW/Internet 2024

Conference

Conference21st International Conference on Applied Computing 2024, AC 2024 and 23rd International Conference on WWW/Internet 2024, ICWI 2024
Country/TerritoryCroatia
CityZagreb
Period26/10/2428/10/24

Keywords

  • AI
  • Artificial Intelligence
  • Environmental
  • ESG
  • Governance
  • Social

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