Validating what counts as knowledge: The algorithmic gaze and nested multifocality in the biosciences

Abstract In this article, we introduce the notions of algorithmic gaze and nested multifocality as analytical categories to investigate the production of evidence in contemporary biosciences. We take a critical stance against certain rhetorics of data-driven science that suggest what counts as evidence is increasingly less the result of experimental procedures and more the outcome of computational methods and pattern recognition algorithms. Drawing on an ethnographic study of a translational medicine project involving the clinic, the biological lab, and bioinformatic work – as well as interviews with bioinformaticians and computational biologists – this paper shows how evidence emerges through the negotiation of different gazes and professional visions. We define the algorithmic gaze as the correlate of a computational style of reasoning, whose output is validated insofar as it incorporates both the clinical and the molecular gaze. The concept of nested multifocality accounts for an epistemic condition in which evidence is not only relative to epistemic cultures and specific research situations, but also emerges through a broader multifocal vision that accommodates different gazes and professional visions.