How Big Data Reshapes Knowledge for International Development: A Governmentality Perspective

Mikkel Flyverbom, Anders Koed Madsen, Andreas Rasche

    Research output: Contribution to conferencePaperResearchpeer-review

    116 Downloads (Pure)


    The aim of this paper is conceptualize and illustrate how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. Based on a review of relevant literature on the uses of big data in the context of development, we unpack how digital traces from cell phone data, social media data or data from internet searches are used as sources of knowledge in this area. We draw on insights from governmentality studies and argue that big data’s impact on how relevant development problems are governed revolves around (1) new techniques of visualizing development issues, (2) a reliance on algorithmic operations that synthesize large-scale data, (3) and novel ways of rationalizing the knowledge claims that underlie development efforts. Our discussion shows that the reliance on big data challenges some aspects of traditional ways to collect and analyze data for development (e.g. via household surveys and deductive approaches), and we articulate intersections between different kinds of knowledge production, different ways of collecting and controlling data, and different epistemic foundations for addressing and governing development problems.
    Original languageEnglish
    Publication date2016
    Number of pages35
    Publication statusPublished - 2016
    EventThe 32nd EGOS Colloquium 2016: Organizing in the Shadow of Power - Napoli, Italy
    Duration: 7 Jul 20169 Jul 2016
    Conference number: 32


    ConferenceThe 32nd EGOS Colloquium 2016
    Internet address

    Cite this