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医疗保健领域中利益相关者对符合伦理道德且值得信赖的语音人工智能的看法。

Stakeholder perspectives on ethical and trustworthy voice AI in health care.

作者信息

Bélisle-Pipon Jean-Christophe, Powell Maria, English Renee, Malo Marie-Françoise, Ravitsky Vardit, Bensoussan Yael

机构信息

Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada.

Vanderbilt University Medical Center, Department of Otolaryngology-Head & Neck Surgery, Nashville, TN, Canada.

出版信息

Digit Health. 2024 Jul 23;10:20552076241260407. doi: 10.1177/20552076241260407. eCollection 2024 Jan-Dec.

Abstract

OBJECTIVE

Voice as a health biomarker using artificial intelligence (AI) is gaining momentum in research. The noninvasiveness of voice data collection through accessible technology (such as smartphones, telehealth, and ambient recordings) or within clinical contexts means voice AI may help address health disparities and promote the inclusion of marginalized communities. However, the development of AI-ready voice datasets free from bias and discrimination is a complex task. The objective of this study is to better understand the perspectives of engaged and interested stakeholders regarding ethical and trustworthy voice AI, to inform both further ethical inquiry and technology innovation.

METHODS

A questionnaire was administered to voice AI experts, clinicians, scholars, patients, trainees, and policy-makers who participated at the 2023 Voice AI Symposium organized by the Bridge2AI-Voice AI Consortium. The survey used a mix of Likert scale, ranking and open-ended questions. A total of 27 stakeholders participated in the study.

RESULTS

The main results of the study are the identification of priorities in terms of ethical issues, an initial definition of ethically sourced data for voice AI, insights into the use of synthetic voice data, and proposals for acting on the trustworthiness of voice AI. The study shows a diversity of perspectives and adds nuance to the planning and development of ethical and trustworthy voice AI.

CONCLUSIONS

This study represents the first stakeholder survey related to voice as a biomarker of health published to date. This study sheds light on the critical importance of ethics and trustworthiness in the development of voice AI technologies for health applications.

摘要

目的

利用人工智能(AI)将声音作为一种健康生物标志物在研究中越来越受到关注。通过可获取的技术(如智能手机、远程医疗和环境录音)或在临床环境中收集声音数据的非侵入性意味着语音人工智能可能有助于解决健康差异问题,并促进边缘化社区的参与。然而,开发无偏差和无歧视的适用于人工智能的语音数据集是一项复杂的任务。本研究的目的是更好地了解积极参与且感兴趣的利益相关者对符合伦理且值得信赖的语音人工智能的看法,以为进一步的伦理探究和技术创新提供参考。

方法

对参加由Bridge2AI - 语音人工智能联盟组织的2023年语音人工智能研讨会的语音人工智能专家、临床医生、学者、患者、实习生和政策制定者进行了问卷调查。该调查采用了李克特量表、排序和开放式问题相结合的方式。共有27名利益相关者参与了该研究。

结果

该研究的主要结果包括确定伦理问题方面的优先事项、对语音人工智能符合伦理来源数据的初步定义、对合成语音数据使用的见解以及关于提高语音人工智能可信度的行动建议。该研究展示了各种不同的观点,并为符合伦理且值得信赖的语音人工智能的规划和开发增添了细微差别。

结论

本研究是迄今为止发表的第一项与将声音作为健康生物标志物相关的利益相关者调查。该研究揭示了伦理和可信度在开发用于健康应用的语音人工智能技术中的至关重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bcb2/11271113/7e59e1615586/10.1177_20552076241260407-fig1.jpg

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