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

Mikkel Flyverbom, Anders Koed Madsen, Andreas Rasche

    Research output: Contribution to conferencePaperResearchpeer-review

    Abstract

    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.
    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.

    Conference

    ConferenceThe 32nd EGOS Colloquium 2016
    Number32
    CountryItaly
    CityNapoli
    Period07/07/201609/07/2016
    Internet address

    Cite this

    Flyverbom, M., Madsen, A. K., & Rasche, A. (2016). How Big Data Reshapes Knowledge for International Development: A Governmentality Perspective. Paper presented at The 32nd EGOS Colloquium 2016, Napoli, Italy.
    Flyverbom, Mikkel ; Madsen, Anders Koed ; Rasche, Andreas. / How Big Data Reshapes Knowledge for International Development : A Governmentality Perspective. Paper presented at The 32nd EGOS Colloquium 2016, Napoli, Italy.35 p.
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    title = "How Big Data Reshapes Knowledge for International Development: A Governmentality Perspective",
    abstract = "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.",
    author = "Mikkel Flyverbom and Madsen, {Anders Koed} and Andreas Rasche",
    year = "2016",
    language = "English",
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    Flyverbom, M, Madsen, AK & Rasche, A 2016, 'How Big Data Reshapes Knowledge for International Development: A Governmentality Perspective' Paper presented at, Napoli, Italy, 07/07/2016 - 09/07/2016, .

    How Big Data Reshapes Knowledge for International Development : A Governmentality Perspective. / Flyverbom, Mikkel; Madsen, Anders Koed; Rasche, Andreas.

    2016. Paper presented at The 32nd EGOS Colloquium 2016, Napoli, Italy.

    Research output: Contribution to conferencePaperResearchpeer-review

    TY - CONF

    T1 - How Big Data Reshapes Knowledge for International Development

    T2 - A Governmentality Perspective

    AU - Flyverbom,Mikkel

    AU - Madsen,Anders Koed

    AU - Rasche,Andreas

    PY - 2016

    Y1 - 2016

    N2 - 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.

    AB - 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.

    M3 - Paper

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    Flyverbom M, Madsen AK, Rasche A. How Big Data Reshapes Knowledge for International Development: A Governmentality Perspective. 2016. Paper presented at The 32nd EGOS Colloquium 2016, Napoli, Italy.