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Potentials and challenges of artificial intelligence-supported greenwashing detection in the energy sector

Research output: Contribution to journalJournal Articlepeer-review

Abstract

Fossil fuel actors have been using greenwashing strategies to enhance their public image by making ‘green’ and ‘sustainable’ claims, which can be misleading for the investing public. This is particularly concerning as it can lead to the unwitting investment in carbon-intensive businesses and investments. The challenge lies in verifying the accuracy of environmental practices due to the vague language used in environmental reporting and disclosures. This Perspective proposes the use of Artificial Intelligence (AI)-supported greenwashing detection tools to help identify and scrutinise greenwashing practices, especially through web scraping, natural language processing, and life cycle assessments to assess the claims made in environmental reports and disclosures using examples from three cases to detect deceptive practices and promote transparency in the industry. However, for AI to be effective in detecting greenwashing practices, it is essential to have trustworthy and readily available databases, as well as human expert involvement to check for any biases in the AI's analysis.

Original languageEnglish
Article number103638
Pages (from-to)1-6
Number of pages6
JournalEnergy Research and Social Science
Volume115
Early online date12 Jun 2024
DOIs
Publication statusPublished - Sept 2024

Bibliographical note

Publisher Copyright:
© 2024 Elsevier Ltd

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  3. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Greenwashing
  • Artificial intelligence
  • Energy transition
  • Environmental reporting
  • Climate risks

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