Recently, a number of scholars have warned against the risk of a new form of deliberately deceptive communication companies use to assure stakeholders of their good intentions in the adoption and development of digital technologies and advanced information systems based on artificial intelligence. This corporate behaviour, defined as machinewashing, in an attempt to empower engagement processes in the stakeholders’ network and satisfy stakeholder expectations with regard to the ethical implications of the use of artificial intelligence, has, in the final instance, the prevailing purpose of achieving better levels of corporate performance and reputation. However, thus far, scholars have not provided any empirical studies on the existence of corporate machinewashing strategies, and there is a significant lack of clarity as to how to measure machinewashing. Utilising the corporate digital responsibility theory, this paper offers an original methodological contribution to the nascent research field dedicated to machinewashing behaviour. Particularly, this paper provides considerations for detecting machinewashing through an analysis based on the comparison between the information capacity of the reporting and the information reliability level as a proxy for machinewashing strategies and, thus, for the real impact of digitalisation strategies on stakeholders. To this end, we conducted an exploratory content analysis of the reports of ten Italian listed companies from ten different industries. Overall, looking at the gap between what companies say about the impact of digitalisation from an ethical perspective, and what really happens, our results define a possible path for identifying machinewashing, the fields where it happens and the practices that companies use in order to realise these strategies.
Measuring machinewashing under the corporate digital responsibility theory: A proposal for a methodological path
Bernini, Francesca;Ferretti, Paola;
2024-01-01
Abstract
Recently, a number of scholars have warned against the risk of a new form of deliberately deceptive communication companies use to assure stakeholders of their good intentions in the adoption and development of digital technologies and advanced information systems based on artificial intelligence. This corporate behaviour, defined as machinewashing, in an attempt to empower engagement processes in the stakeholders’ network and satisfy stakeholder expectations with regard to the ethical implications of the use of artificial intelligence, has, in the final instance, the prevailing purpose of achieving better levels of corporate performance and reputation. However, thus far, scholars have not provided any empirical studies on the existence of corporate machinewashing strategies, and there is a significant lack of clarity as to how to measure machinewashing. Utilising the corporate digital responsibility theory, this paper offers an original methodological contribution to the nascent research field dedicated to machinewashing behaviour. Particularly, this paper provides considerations for detecting machinewashing through an analysis based on the comparison between the information capacity of the reporting and the information reliability level as a proxy for machinewashing strategies and, thus, for the real impact of digitalisation strategies on stakeholders. To this end, we conducted an exploratory content analysis of the reports of ten Italian listed companies from ten different industries. Overall, looking at the gap between what companies say about the impact of digitalisation from an ethical perspective, and what really happens, our results define a possible path for identifying machinewashing, the fields where it happens and the practices that companies use in order to realise these strategies.File | Dimensione | Formato | |
---|---|---|---|
Business Ethics Env Resp - 2024 - Bernini - Measuring machinewashing under the corporate digital responsibilit.pdf
accesso aperto
Tipologia:
Versione finale editoriale
Licenza:
Creative commons
Dimensione
481.58 kB
Formato
Adobe PDF
|
481.58 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.