Datafication and the Practice of Discovery

We are witnessing vertiginous growth in the generation, mobilisation and analysis of data for research purposes. As data grow bigger and easier to access, artificial intelligence is increasingly used to generate new knowledge by trawling through the digital blueprints generated by human interactions with technology. Thus the datafication of society is said to be revolutionizing how researchers investigate the world, resulting in improved scientific communications, faster data integration and analysis, and more reliable outputs.

This talk interrogates the role that big and open data play in scientific research and, more generally, as grounding for the development of empirical knowledge. I argue that data-driven modes of discovery do not constitute a rupture from previous ways of doing research and are not necessarily improving the reliability of the resulting insights. Rather, recourse to Big and Open Data continues - and exasperates - a long-standing understanding of discovery as grounded on data accumulation and the extraction of information, which does not align with the ways in which many researchers actually use and interpret data. Through a combination of qualitative research and philosophical analysis, I discuss this approach to scientific epistemology, which I call ’presence empiricism’, and review its multiple failings. I then propose an alternative framing of the role of data in the process of inquiry, which focuses on the limitations of data as research components and the unavoidable value judgements involved in using data as scientific evidence.

In cooperation with the Wissenschaftskolleg zu Berlin.