There are various ways in which Large Language Models (LLMs), the latest breakthrough in Artificial Intelligence, are relevant for medicine: this paper focuses on their potential for supporting and improving argumentation in healthcare, both for patients and for practitioners. The message is mostly positive, suggesting adoption of such systems, but with specific cautions: most notably, the need to leverage them for enhancing human communicative and epistemic performance, rather than replacing it, and the importance of training users on few key principles to guide their deployment of LLMs in healthcare. The paper is accompanied by four concrete use cases, included in the supplementary materials, that constitute an integral and crucial part of this contribution.

Large Language Models, argumentation, and healthcare: A socio-cognitive perspective

Paglieri F.
Primo
2025

Abstract

There are various ways in which Large Language Models (LLMs), the latest breakthrough in Artificial Intelligence, are relevant for medicine: this paper focuses on their potential for supporting and improving argumentation in healthcare, both for patients and for practitioners. The message is mostly positive, suggesting adoption of such systems, but with specific cautions: most notably, the need to leverage them for enhancing human communicative and epistemic performance, rather than replacing it, and the importance of training users on few key principles to guide their deployment of LLMs in healthcare. The paper is accompanied by four concrete use cases, included in the supplementary materials, that constitute an integral and crucial part of this contribution.
2025
Istituto di Scienze e Tecnologie della Cognizione - ISTC
argumentative practice
chatbots
doctor-patient interactions
generative Artificial Intelligence
healthcare training
Large Language Models
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/583392
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ente

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact