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Accepted Contribution:

The importance of researching medical AI with affected populations  
Tereza Hendl (University of Augsburg) Bianca Jansky (University of Augsburg, Germany)

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Short abstract:

In this paper, we discuss our trajectory of researching patient-led open-source health innovation in the context of T1D Diabetes without and with affected people who use health innovation products. We reflect on the importance of research methodologies that learn from embodied and lived knowledges.

Long abstract:

Health innovation is mainly envisioned in direct connection to medical research institutions or pharmaceutical and technology companies. Yet, these types of innovation often do not meet the needs and expectations of individuals affected by various health conditions. With the emergence of digital health technologies and social media, we can observe a shift, which involves people living with illness modifying and improving medical and health devices outside of the formal research and development sector, figuring both as users and innovators. In our previous research, we have taken a closer look at the ethics of open-source patient-led innovation in the context of type 1 diabetes care, arguing that it comes short of being a "bottom-up" kind of innovation fostering the needs of the most under-served populations. Along the journey of investigating concerns of intersectional and global health justice, we have also become increasingly more attentive to the need of researching such concerns with T1D innovation users themselves. In this paper, we share what we have learnt through subsequent dialogues and consultations with academics, innovators, carers and persons with lived experiences of T1D. In particular, we share a range of specific and crucial socio-ethical issues and health needs we would have not come to be aware of had we not engaged with affected experts during our research. Building on our self-reflective trajectory, we draw crucial lessons about the type of concerns that are missing from digital health ethics debates and research methodologies without direct engagement with and learning from embodied and lived knowledges.

Combined Format Open Panel P131
How to research medical AI?
  Session 2 Friday 19 July, 2024, -