Algorithmic Experience: Exploring the Potential of AI Technologies for Medical Knowledge Integration

In this chapter, we conceptually and empirically investigate how AI technology might shape medical knowledge production, specifically the diversification of what is considered valuable knowledge in evidence-based medicine (EBM). We outline different conceptual perspectives on knowledge production and general logics and practices underlying AI, in particular, dominant concerns about how the use of AI will enhance existing processes in EBM, including fortifying underlying epistemic assumptions. As a contrast, we explore possible other future directions for the relationship between AI and medical knowledge production by drawing on early empirical findings from a collaborative project with the Dutch National Institute for Public Health and the Environment. In this project, we experiment with using AI-based methods to harness experiential knowledge for vaccination guideline development. Through empiricising and experimenting with AI, we explore alternative pathways for using AI to broaden the evidence and knowledge base available for guideline development. Doing and experimenting with AI, allowed us to gain more nuanced insights into the situatedness, concrete potential and challenges of employing AI technology, concluding that the study of AI technologies in relation to knowledge production and -integration may benefit from not just an empirical but an experimental turn too.