Unpicking Epistemic Injustices in Digital Health: On the Implications of Designing Data-Driven Technologies for the Management of Long-Term Conditions
SJ Bennett, Caroline Claisse, Ewa Luger, Abigail Durrant
Abstract
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.