Digital methods as ‘experimental a priori’ – how to navigate vague empirical situations as an operationalist pragmatist

Digitalisation and computation presents us with a vague empirical world that unsettles established links between measurements and values. As more and more actors use digital media to produce data about aspects of the world they deem important, new possibilities for inscribing their lives emerge. The practical work with digital methods thus often involves the production of social visibilities that are misfits in the context of established data practices. In this paper I argue that this dissonance carries the distinct critical potential to design data experiments that (a) uses the act of operationalisation as an engine for creating intersubjective clarity about the meaning of existing concepts and (b) takes advantage of algorithmic techniques to provoke a reassessment of some of the core assumptions that shape the way we pose empirical problems are normally framed. Drawing on the work of Kant, Peirce, Dewey and C.I. Lewis I propose to think of this critical potential as the possibility to practice what I term 'experimental a priori' and I use qualitative vignettes from two years of data experiments with GEHL architects to illustrate what this entails in practice. Faced with the task of using traces from Facebook as an empirical source to produce a map of urban political diversity, the architects found themselves in a need to revisit inherited assumptions about the ontology of urban space and the way it can even be formulated as a problem of diversity. While I describe this as a form of obstructive data practice that is afforded by digital methods, I also argue that it cannot be realised without deliberate design interventions. I therefore end the paper by outlining five design principles that can productively guide collective work with digital methods. These principles contribute to recent work within digital STS on the recalibration of problem spaces and the design of data sprints. However, the concept of ‘experimental a priori’ can also serve as a philosophical foundation for knowledge production within computational humanities more broadly.