Unpicking Epistemic Injustices in Digital Health: On the Implications of Designing Data-Driven Technologies for the Management of Long-Term Conditions
Unpicking Epistemic Injustices in Digital Health: On the Implications of Designing Data-Driven Technologies for the Management of Long-Term Conditions
复制标题
消除数字健康中的认知不公正：设计数据驱动技术对长期状况管理的影响
DOI：
10.1145/3600211.3604684
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Bennett S
中科院分区：
文献类型：
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作者：
Bennett S
人工智能（AI）在个人健康信息学（PHI）领域的应用为长期患病的人提供了个性化治疗和支持的潜在途径，然而，它们也带来了一些伦理挑战。虽然参与式方法可以通过积极地让医疗保健专业人员、患者和其他利益相关者参与设计和开发来帮助减轻担忧，但这些方法受到认识观点的限制以及从个人到群体的外推所带来的风险的限制。在本文中，我们利用与参与人类免疫缺陷病毒（HIV）护理的利益相关者，包括临床医生，保险提供商和制药行业代表的访谈，绘制意图和伦理考虑，为艾滋病毒感染者开发PHI工具。虽然艾滋病毒的治疗效果提高了患者的生活质量和预期寿命，但由于对艾滋病毒感染者的生活和老龄化的认识不足，管理和护理变得复杂。我们研究了认识不公正的关键概念如何为旨在解决这些差距的数据驱动技术的设计提供信息，帮助在更广泛的结构和社会历史影响中引导专家的观点。在为艾滋病毒感染者等边缘化人群（即可能遭受社会耻辱和资源不足，管理多种状况的人）设计时，这一点尤为重要，有助于确定和更好地考虑公平等基本道德因素。
Applications of Artificial Intelligence (AI) in the domain of Personal Health Informatics (PHI) offer potential avenues for personalised treatment and support for people living with long-term conditions, however, they also present a number of ethical challenges. Whilst participatory approaches can help mitigate concerns by actively involving healthcare professionals, patients, and other stakeholders in design and development, these are constrained by the limits of epistemic standpoints and the risks posed by extrapolation from individuals to groups. In this paper we draw upon interviews with stakeholders involved in Human Immunodeficiency Virus (HIV) care, including clinicians, insurance providers and pharmaceutical industry representatives, to map intentions and ethical considerations for developing PHI tools for people living with HIV. Whilst treatment efficacy for HIV has improved patient quality of life and life expectancy, management and care is complicated by knowledge gaps about what living and ageing with HIV entails. We investigate how the critical concept of epistemic injustice can inform the design of data-driven technologies intended to address these gaps, helping orient expert perspectives within the broader structures and socio-historical influences that shape them. This is of particular importance when designing for marginalized populations such as people with HIV (i.e. who may experience social stigma and be under-resourced, managing multiple conditions), helping to identify and better account for fundamental ethical considerations such as equity.