ArticleDigital health
Stakeholder perspectives on ethical and trustworthy voice AI in health care.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The evolving literature on the ethics of artificial intelligence for healthcare: a PRISMA scoping review.Frontiers in digital health · 2025Pooled it
- Large Language Models for Optimizing Patient Recruitment Decisions in Voice Data Generation Projects.Laryngoscope investigative otolaryngology · 2026Article
- Artificial Intelligence in Voice Disorders: Current Landscape, Emerging Applications and Future Directions.World journal of otorhinolaryngology - head and neck surgery · 2026Review
- Agentic AI as a coordination paradigm in digital health and agri-food systems.Patterns (New York, N.Y.) · 2026Review
- Using voice and speech data in healthcare: a scoping review of the ethical, legal and social implications.Frontiers in digital health · 2026Review
- The epistemic economy of vocal biomarker startups: a qualitative interview study of data practices and governance.Frontiers in digital health · 2026Article
- Editorial: Advancing vocal biomarkers and voice AI in healthcare: multidisciplinary focus on responsible and effective development and use.Frontiers in digital health · 2026Article
- "Low Risk, High Happiness": A Review of Openly Declared Ethical and Legal Practices in Voice Biomarker Health-Tech Start-Ups.Health care analysis : HCA : journal of health philosophy and policy · 2025Article
- Ethical sourcing in the context of health data supply chain management: a value sensitive design approach.JAMIA open · 2025Article
- "Voice is the New Blood": a discourse analysis of voice AI health-tech start-up websites.Frontiers in digital health · 2025Article
- Master protocols in vocal biomarker development to reduce variability and advance clinical precision: a narrative review.Frontiers in digital health · 2025Review
- Ethics dumping in artificial intelligence.Frontiers in artificial intelligence · 2024Article
- Consensus-Based Definitions for Vocal Biomarkers: The International VOCAL Initiative.Digital biomarkersArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.