持续性
独创性
转化式学习
概念框架
领域(数学)
构造(python库)
生成语法
工程伦理学
知识管理
管理科学
数据科学
计算机科学
社会学
工程类
社会科学
人工智能
定性研究
数学
程序设计语言
纯数学
生物
生态学
教育学
作者
Charl de Villiers,Ruth Dimes,Matteo Molinari
标识
DOI:10.1108/sampj-02-2023-0097
摘要
Purpose The ability of generative artificial intelligence (AI) tools such as ChatGPT to produce convincing, human-like text has major implications for the future of corporate reporting, including sustainability reporting. As the importance of sustainability reporting continues to grow, this study aims to critically analyse the benefits and pitfalls of automated text generation and processing. Design/methodology/approach This study develops a conceptual framework to delineate the field, assess the implications and form the basis for the generation of research questions. This study uses Alvesson and Deetz’s critical framework, considering insight (a review of literature and practice in the field), critique (consideration of the influences on the production and use of non-financial information and the implications for assurers of such information) and transformative redefinition (considering the implications of generative AI for sustainability reporting and proposing a research agenda). Findings This study highlights the implications of generative AI for sustainability accounting, reporting, assurance and report usage, including the risk of AI facilitating greenwashing, and the importance of more research on the use of AI for these matters. Practical implications The paper highlights to stakeholders the implications of AI for all aspects of sustainability reporting, including accounting, reporting, assurance and usage of reports. Social implications The implications of AI need to be understood in society, which this paper facilitates. Originality/value This study critically analyses the potential use of AI for sustainability reporting, construct a conceptual framework to delineate the field and develop a research agenda.
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