Building on critical approaches that understand algorithms in terms of communication, culture and organization, this paper offers the supplementary conceptualization of algorithms as organizational figuration, defined as material and meaningful sociotechnical arrangements that develop in spatiotemporal processes and are shaped by multiple enactments of affordance–agency relations. We develop this conceptualization through a case study of a Danish fintech start-up that uses machine learning to create opportunities for sustainable pensions investments. By way of ethnographic and literary methodology, we provide an in-depth (...) analysis of the dynamic trajectory in and through which the organization gives shape to and takes shape from its key algorithmic tool, mapping the shifting sociotechnical arrangements of the start-up, from its initial search for a viable business model through the development of the algorithm to the public launch of its product. On this basis, we argue that conceptualizing algorithms as organizational figuration enables us to detail not only what algorithms do but also what they are. (shrink)

A recent report from the UN makes the case for “global data literacy” in order to realise the opportunities afforded by the “data revolution”. Here and in many other contexts, data literacy is characterised in terms of a combination of numerical, statistical and technical capacities. In this article, we argue for an expansion of the concept to include not just competencies in reading and working with datasets but also the ability to account for, intervene around and participate in the wider (...) socio-technical infrastructures through which data is created, stored and analysed – which we call “data infrastructure literacy”. We illustrate this notion with examples of “inventive data practice” from previous and ongoing research on open data, online platforms, data journalism and data activism. Drawing on these perspectives, we argue that data literacy initiatives might cultivate sensibilities not only for data science but also for data sociology, data politics as well as wider public engagement with digital data infrastructures. The proposed notion of data infrastructure literacy is intended to make space for collective inquiry, experimentation, imagination and intervention around data in educational programmes and beyond, including how data infrastructures can be challenged, contested, reshaped and repurposed to align with interests and publics other than those originally intended. (shrink)

Science and technology studies is famous for questioning conceptual and material boundaries by following controversies that cut across them. However, it has recently been argued that in research involving online platforms, there are also more practical boundaries to negotiate that are created by the variable availability, visibility, and structuring of data. In this paper, I highlight a potential tension between our inclination toward following controversies and “following the medium” and suggest that sometimes following controversies might involve going “against platforms” as (...) well as with them. I will illustrate this dilemma through an analysis of the controversy over the coverage of the Fukushima disaster on English language Wikipedia, which concerns boundaries between expert and lay knowledge but also the social and technical functioning of Wikipedia itself. For this reason, I show that following the controversy might mean making use of less formatted and less obvious data than Wikipedia normally provides. While this is not an argument against the use of automated digital research tools such as scrapers, I suggest that both quantitative and qualitative researchers need to be more willing to tweak their approaches based on the specificities of the case. (shrink)