Under what circumstances do we attribute a mind to AI systems? And, in this case, how do we think their mind works? Answering these questions is crucial to inform the design of safe and trustable AI, to inform research on the ethical, social and legal issues raised by the increasing presence of AI systems in everyday life and to investigate how they can be used as tools to study human and social cognition. This work proposes a philosophical reflection on the possible structure of people’s mental models of AI systems. We distinguish between two possible styles of modeling that people may adopt in everyday contexts. Both involve the attribution of mental states and cognitive abilities to the AI system, even though they differ from one another in some relevant aspects. One modeling style is akin to folk psychology and relies on the attribution of beliefs, desires, and other propositional attitudes to the system. The other, which we will refer to as folk-cognitivist, is more akin to the account of the structure of the mind that characterizes classical cognitive science. These modeling styles correspond to different classes of mentalistic stances that people may adopt when they interact with AI systems in ordinary contexts.
Larghi, S., Datteri, E. (2024). Mentalistic Stances Towards AI Systems: Beyond the Intentional Stance. In A. Aldini (a cura di), Software Engineering and Formal Methods. SEFM 2023 Collocated Workshops CIFMA 2023 and OpenCERT 2023, Eindhoven, The Netherlands, November 6–10, 2023, Revised Selected Papers (pp. 28-41). Springer [10.1007/978-3-031-66021-4_2].
Mentalistic Stances Towards AI Systems: Beyond the Intentional Stance
Larghi, Silvia
;Datteri, Edoardo
2024
Abstract
Under what circumstances do we attribute a mind to AI systems? And, in this case, how do we think their mind works? Answering these questions is crucial to inform the design of safe and trustable AI, to inform research on the ethical, social and legal issues raised by the increasing presence of AI systems in everyday life and to investigate how they can be used as tools to study human and social cognition. This work proposes a philosophical reflection on the possible structure of people’s mental models of AI systems. We distinguish between two possible styles of modeling that people may adopt in everyday contexts. Both involve the attribution of mental states and cognitive abilities to the AI system, even though they differ from one another in some relevant aspects. One modeling style is akin to folk psychology and relies on the attribution of beliefs, desires, and other propositional attitudes to the system. The other, which we will refer to as folk-cognitivist, is more akin to the account of the structure of the mind that characterizes classical cognitive science. These modeling styles correspond to different classes of mentalistic stances that people may adopt when they interact with AI systems in ordinary contexts.File | Dimensione | Formato | |
---|---|---|---|
Larghi-Datteri-2024-SEFM 2023-VoR.pdf
Solo gestori archivio
Tipologia di allegato:
Publisher’s Version (Version of Record, VoR)
Licenza:
Tutti i diritti riservati
Dimensione
330.34 kB
Formato
Adobe PDF
|
330.34 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.