Consent-GPT: is it ethical to delegate procedural consent to conversational AI?
Consent-GPT: is it ethical to delegate procedural consent to conversational AI?
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DOI：
10.1136/jme-2023-109347
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发表时间：
2023-10-27
影响因子：
4.1
通讯作者：
Wilkinson，Dominic
中科院分区：
文献类型：
--
作者：
Allen，Jemima Winifred;Earp，Brian D.;Wilkinson，Dominic
在医疗或外科手术之前获得患者的知情同意是安全和合乎道德的临床实践的基本组成部分。目前，将同意过程的重要部分委托给不执行该程序的临床团队成员（例如，初级医生）是常规做法。然而，通常的同意代表缺乏足够的时间和临床知识，以充分促进患者的自主权和知情决策。这些问题可以通过多种方式加以解决。解决这一临床困境的一个可能的方法是使用大型语言模型（llm）的会话人工智能。这些模型在医学上的潜在益处引起了相当大的兴趣。对于委托程序同意，LLM可以改善患者对相关程序信息的获取，从而增强知情决策。在本文中，我们首先概述了一个在手术前授权法学硕士同意的假设示例。然后，我们讨论了现有的同意授权的临床指导方针，以及当前实践可能无法满足知情同意的伦理目的的一些方式。我们概述并讨论了在医学中授权法学硕士同意的伦理含义，结论是至少在某些临床情况下，法学硕士的好处可能远远超过当前实践的好处。
Obtaining informed consent from patients prior to a medical or surgical procedure is a fundamental part of safe and ethical clinical practice. Currently, it is routine for a significant part of the consent process to be delegated to members of the clinical team not performing the procedure (eg, junior doctors). However, it is common for consent-taking delegates to lack sufficient time and clinical knowledge to adequately promote patient autonomy and informed decision-making. Such problems might be addressed in a number of ways. One possible solution to this clinical dilemma is through the use of conversational artificial intelligence using large language models (LLMs). There is considerable interest in the potential benefits of such models in medicine. For delegated procedural consent, LLM could improve patients’ access to the relevant procedural information and therefore enhance informed decision-making.In this paper, we first outline a hypothetical example of delegation of consent to LLMs prior to surgery. We then discuss existing clinical guidelines for consent delegation and some of the ways in which current practice may fail to meet the ethical purposes of informed consent. We outline and discuss the ethical implications of delegating consent to LLMs in medicine concluding that at least in certain clinical situations, the benefits of LLMs potentially far outweigh those of current practices.