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Accepted Paper:

How big-data and AI decisionmaking is impacting decisionmaking of medical experts  
Roanne van Voorst (University of Amsterdam)

Paper short abstract:

Within the literary discussion on ethical AI, Several scholars have concluded that what is lacking is on-the-ground empirical evidence that shows how socalled ‘responsible’ big data-systems and AI unfolds in daily work practice. This paper aims to contribute by providing etnographic data from two contrasting cases in the realm of public health.

Paper long abstract:

This paper shares etnographic data on the practical outcomes of three different cases of big-data and AI-usage that are currently used in the realm of public health: a free-of-charge health incentive application that is used by volunteering citizens aiming to improve their health, and an application that is used against payment that is used by people who are concerned about the potentiality of skin cancer. The case were selected for two main reasons: firstly, they are both widely regarded as succesful and ‘best case’ examples, which makes it well possible that they will soon be scaled up widely and makes it all the more relevant to study their impacts for public health. Secondly, they are both characterized by the medical experts and other stakeholders involved in their management and creation, as ‘ethical’ or responsible AI – as said, there is not much empirical data that researchers the concrete usage of such ethically designed systems, while these case studies were well suited for such an analysis. The research involved observations during stakeholder meetings, observations of the interaction between medical experts and data analysts with health data systems, and semi structured in depth interviews with most important stakeholders.

Panel P24
Digitalization of health: a panel on AI, big-data and applications used in health governance
  Session 1 Monday 6 June, 2022, -