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促进公众参与医疗保健人工智能研究:实证方法的范围综述。

Facilitating public involvement in research about healthcare AI: A scoping review of empirical methods.

机构信息

Australian Centre for Health Engagement, Evidence and Values, School of Health and Society, Faculty of the Arts, Social Sciences, and Humanities, University of Wollongong, Australia.

出版信息

Int J Med Inform. 2024 Jun;186:105417. doi: 10.1016/j.ijmedinf.2024.105417. Epub 2024 Mar 22.

Abstract

OBJECTIVE

With the recent increase in research into public views on healthcare artificial intelligence (HCAI), the objective of this review is to examine the methods of empirical studies on public views on HCAI. We map how studies provided participants with information about HCAI, and we examine the extent to which studies framed publics as active contributors to HCAI governance.

MATERIALS AND METHODS

We searched 5 academic databases and Google Advanced for empirical studies investigating public views on HCAI. We extracted information including study aims, research instruments, and recommendations.

RESULTS

Sixty-two studies were included. Most were quantitative (N = 42). Most (N = 47) reported providing participants with background information about HCAI. Despite this, studies often reported participants' lack of prior knowledge about HCAI as a limitation. Over three quarters (N = 48) of the studies made recommendations that envisaged public views being used to guide governance of AI.

DISCUSSION

Provision of background information is an important component of facilitating research with publics on HCAI. The high proportion of studies reporting participants' lack of knowledge about HCAI as a limitation reflects the need for more guidance on how information should be presented. A minority of studies adopted technocratic positions that construed publics as passive beneficiaries of AI, rather than as active stakeholders in HCAI design and implementation.

CONCLUSION

This review draws attention to how public roles in HCAI governance are constructed in empirical studies. To facilitate active participation, we recommend that research with publics on HCAI consider methodological designs that expose participants to diverse information sources.

摘要

目的

随着对公众对医疗保健人工智能(HCAI)看法的研究不断增加,本综述旨在考察公众对 HCAI 看法的实证研究方法。我们绘制了研究向参与者提供有关 HCAI 信息的方式,并研究了研究将公众框定为 HCAI 治理的积极贡献者的程度。

材料与方法

我们在 5 个学术数据库和 Google 高级搜索中搜索了调查公众对 HCAI 看法的实证研究。我们提取了包括研究目的、研究工具和建议在内的信息。

结果

共纳入 62 项研究。大多数为定量研究(N=42)。大多数(N=47)报告为参与者提供了有关 HCAI 的背景信息。尽管如此,研究往往报告参与者缺乏对 HCAI 的先前了解是一个限制。超过四分之三(N=48)的研究提出了建议,设想将公众的意见用于指导人工智能的治理。

讨论

提供背景信息是促进与公众就 HCAI 进行研究的重要组成部分。报告参与者缺乏对 HCAI 的了解作为限制的研究比例很高,这反映了需要更多关于如何呈现信息的指导。少数研究采取了技术官僚立场,将公众视为人工智能的被动受益者,而不是 HCAI 设计和实施的积极利益相关者。

结论

本综述提请注意实证研究中如何构建公众在 HCAI 治理中的角色。为了促进积极参与,我们建议对公众进行 HCAI 研究的研究考虑采用将参与者暴露于多种信息源的方法设计。

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