This study explores the information regarding Artificial Intelligence (AI) included by European listed companies in their annual and/or sustainability reports. The study mainly focuses on (1) the development and use of AI systems/projects reported by companies, (2) the extent to which companies disclose ethical principles or guidelines regarding AI and (3) the factors explaining these practices. The study analyses the reports of 200 companies listed in the major indexes of Germany, Sweden, Finland, France, Spain, and Italy, both from qualitative and quantitative perspectives. All reports are analysed, using content analysis methodology, to identify expressions such as ‘arti-ficial intelligence’, ‘machine learning’, ‘deep learning’, and ‘big data’, and then classified accordingly. The study’s findings suggest a growing interest in the above-mentioned technologies, although 41.5% of companies do not report any activity in the field of AI. The adoption of ethical approaches to AI is at a very preliminary stage, and<5% of companies report on that issue. The quantitative analysis shows that larger companies, companies in the Technology and Telecom-munications industries, and companies based in Southern countries are more likely to disclose information on AI activity. The majority of companies that develop ethical principles are listed in the Northern region and belong to the Technology and Telecommunications industries. The study provides evidence of AI disclosure, a type of non-financial disclosure that has not been explored yet in the literature. Unlike existing studies, we propose a first definition of the topic and a taxonomy that can be used in further research on AI disclosure and can contribute to the development of KPIs in the field. Furthermore, this study provides a theoretical framework integrating some traditional theories, such as Voluntary disclosure theory, Signalling theory, and Legitimacy theory, specifically drawn to interpret AI disclosure practices, which can help with a further in-depth exploration of AI disclosure combining concurrent perspectives. The study’s results may serve as a starting point for researchers and companies interested in the topic.

Artificial intelligence activities and ethical approaches in leading listed companies in the European Union

DomenicaLavorato;Rita Lamboglia;
2021

Abstract

This study explores the information regarding Artificial Intelligence (AI) included by European listed companies in their annual and/or sustainability reports. The study mainly focuses on (1) the development and use of AI systems/projects reported by companies, (2) the extent to which companies disclose ethical principles or guidelines regarding AI and (3) the factors explaining these practices. The study analyses the reports of 200 companies listed in the major indexes of Germany, Sweden, Finland, France, Spain, and Italy, both from qualitative and quantitative perspectives. All reports are analysed, using content analysis methodology, to identify expressions such as ‘arti-ficial intelligence’, ‘machine learning’, ‘deep learning’, and ‘big data’, and then classified accordingly. The study’s findings suggest a growing interest in the above-mentioned technologies, although 41.5% of companies do not report any activity in the field of AI. The adoption of ethical approaches to AI is at a very preliminary stage, and<5% of companies report on that issue. The quantitative analysis shows that larger companies, companies in the Technology and Telecom-munications industries, and companies based in Southern countries are more likely to disclose information on AI activity. The majority of companies that develop ethical principles are listed in the Northern region and belong to the Technology and Telecommunications industries. The study provides evidence of AI disclosure, a type of non-financial disclosure that has not been explored yet in the literature. Unlike existing studies, we propose a first definition of the topic and a taxonomy that can be used in further research on AI disclosure and can contribute to the development of KPIs in the field. Furthermore, this study provides a theoretical framework integrating some traditional theories, such as Voluntary disclosure theory, Signalling theory, and Legitimacy theory, specifically drawn to interpret AI disclosure practices, which can help with a further in-depth exploration of AI disclosure combining concurrent perspectives. The study’s results may serve as a starting point for researchers and companies interested in the topic.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11367/100008
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