Talk: Sabina Leonelli (TUM)

Title:

Scientific Inquiry in the Age of AI: An Empirically Grounded Critique of Presence Empiricism

Abstract:

The datafication of society and widespread adoption of generative AI are revolutionizing how researchers investigate the world, which is expected to result in improved scientific communications, faster data integration and analysis, and more reliable outputs. The analysis of Big and Open Data by AI models exemplifies the newest frontier of empirical research, and scientific success in extracting knowledge from such objects is often hailed as demonstrating the power of (increasingly automated) inductive reasoning: science as the collection and interpretation of facts about the world. In this lecture, I critique this view of scientific inquiry, which is predicated on the existence and availability of documents of the world from which insights can be distilled through highly formalised procedures amendable to automation. Building on in-depth, long-term studies of data and modelling practices in the biological and biomedical sciences (see www.opensciencestudies.eu, www.datasciencestudies.eu), I review the multiple failures of this form of empiricism, drawing attention especially to the intersection of moral and epistemic problems that this approach to research fails to address or even to recognize as significant, with severe implications for the reliability and the robustness of the knowledge thereby generated. The study of research practices calls for an alternative framing of empirical inquiry focused on the limitations of data as research components and the value judgements involved in using data as scientific evidence.