Is Consent‑GPT valid? Public attitudes to generative AI use in surgical consent
Metadatos
Mostrar el registro completo del ítemAutor
Winifred Allen, Jemima; Rodríguez Hannikainen, Ivar Allan; Savulescu, Julian; Wilkinson, Dominic; Earp, Brian DavidEditorial
Springer
Materia
Artifcial intelligence in healthcare Consent delegation Empirical bioethics
Fecha
2025-10-09Referencia bibliográfica
Allen, J.W., Hannikainen, I.R., Savulescu, J. et al. Is Consent-GPT valid? Public attitudes to generative AI use in surgical consent. AI & Soc (2025). https://doi.org/10.1007/s00146-025-02644-9
Patrocinador
National Research Foundation Singapore (Grant number AISG3-GV-2023-012 ); Wellcome Trust (Grant number 203132/Z/16/Z)Resumen
Healthcare systems often delegate surgical consent-seeking to members of the treating team other than the surgeon (e.g.,
junior doctors in the UK and Australia). Yet, little is known about public attitudes toward this practice compared to emerging AI-supported options. This frst large-scale empirical study examines how laypeople evaluate the validity and liability
risks of using an AI-supported surgical consent system (Consent-GPT). We randomly assigned 376 UK participants (demographically representative for age, ethnicity, and gender) to evaluate identical transcripts of surgical consent interviews
framed as being conducted by either Consent-GPT, a junior doctor, or the treating surgeon. Participants broadly agreed that
AI-supported consent was valid (87.6% agreement), but rated it signifcantly lower than consent sought solely by human
clinicians (treating surgeon: 97.6% agreement; junior doctor: 96.2%). Participants expressed substantially lower satisfaction
with AI-supported consent compared to human-only processes (Consent-GPT: 59.5% satisfed; treating surgeon 96.8%; junior
doctor: 93.1%), despite identical consent interactions (i.e., the same informational content and display format). Regarding
justifcation to sue the hospital following a complication, participants were slightly more inclined to support legal action in
response to AI-supported consent than human-only consent. However, the strongest predictor was proper risk disclosure,
not the consent-seeking agent. As AI integration in healthcare accelerates, these results highlight critical considerations for
implementation strategies, suggesting that a hybrid approach to consent delegation that leverages AI’s information sharing
capabilities while preserving meaningful human engagement may be more acceptable to patients than an otherwise identical
process with relatively less human-to-human interaction.





