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

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.