Big Data as Governmentality: How Large-Scale Data Reshapes International Development

Mikkel Flyverbom, Anders Koed Madsen, Andreas Rasche

    Research output: Contribution to conferencePaperResearchpeer-review

    Abstract

    This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects of the international development agenda to algorithms that synthesize large-scale data, (3) novel ways of rationalizing knowledge claims that underlie development policies, and (4) shifts in professional and organizational identities of those concerned with producing and processing data for development. Our discussion shows that big data problematizes selected aspects of traditional ways to collect and analyze data for development (e.g. via household surveys). We also demonstrate that using big data analyses to address development challenges raises a number of questions that can deteriorate its impact.
    Original languageEnglish
    Publication date2014
    Number of pages32
    Publication statusPublished - 2014
    Event55th ISA Annual Convention: International Studies Association Conference 2014 - Toronto, Canada
    Duration: 26 Mar 201429 Mar 2014
    Conference number: 55
    http://www.isanet.org/Conferences/Toronto2014.aspx

    Conference

    Conference55th ISA Annual Convention
    Number55
    CountryCanada
    CityToronto
    Period26/03/201429/03/2014
    Internet address

    Cite this

    Flyverbom, M., Madsen, A. K., & Rasche, A. (2014). Big Data as Governmentality: How Large-Scale Data Reshapes International Development. Paper presented at 55th ISA Annual Convention, Toronto, Canada.
    Flyverbom, Mikkel ; Madsen, Anders Koed ; Rasche, Andreas. / Big Data as Governmentality : How Large-Scale Data Reshapes International Development. Paper presented at 55th ISA Annual Convention, Toronto, Canada.32 p.
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    title = "Big Data as Governmentality: How Large-Scale Data Reshapes International Development",
    abstract = "This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects of the international development agenda to algorithms that synthesize large-scale data, (3) novel ways of rationalizing knowledge claims that underlie development policies, and (4) shifts in professional and organizational identities of those concerned with producing and processing data for development. Our discussion shows that big data problematizes selected aspects of traditional ways to collect and analyze data for development (e.g. via household surveys). We also demonstrate that using big data analyses to address development challenges raises a number of questions that can deteriorate its impact.",
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    author = "Mikkel Flyverbom and Madsen, {Anders Koed} and Andreas Rasche",
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    Flyverbom, M, Madsen, AK & Rasche, A 2014, 'Big Data as Governmentality: How Large-Scale Data Reshapes International Development' Paper presented at, Toronto, Canada, 26/03/2014 - 29/03/2014, .

    Big Data as Governmentality : How Large-Scale Data Reshapes International Development. / Flyverbom, Mikkel; Madsen, Anders Koed; Rasche, Andreas.

    2014. Paper presented at 55th ISA Annual Convention, Toronto, Canada.

    Research output: Contribution to conferencePaperResearchpeer-review

    TY - CONF

    T1 - Big Data as Governmentality

    T2 - How Large-Scale Data Reshapes International Development

    AU - Flyverbom, Mikkel

    AU - Madsen, Anders Koed

    AU - Rasche, Andreas

    PY - 2014

    Y1 - 2014

    N2 - This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects of the international development agenda to algorithms that synthesize large-scale data, (3) novel ways of rationalizing knowledge claims that underlie development policies, and (4) shifts in professional and organizational identities of those concerned with producing and processing data for development. Our discussion shows that big data problematizes selected aspects of traditional ways to collect and analyze data for development (e.g. via household surveys). We also demonstrate that using big data analyses to address development challenges raises a number of questions that can deteriorate its impact.

    AB - This paper conceptualizes how large-scale data and algorithms condition and reshape knowledge production when addressing international development challenges. The concept of governmentality and four dimensions of an analytics of government are proposed as a theoretical framework to examine how big data is constituted as an aspiration to improve the data and knowledge underpinning development efforts. Based on this framework, we argue that big data’s impact on how relevant problems are governed is enabled by (1) new techniques of visualizing development issues, (2) linking aspects of the international development agenda to algorithms that synthesize large-scale data, (3) novel ways of rationalizing knowledge claims that underlie development policies, and (4) shifts in professional and organizational identities of those concerned with producing and processing data for development. Our discussion shows that big data problematizes selected aspects of traditional ways to collect and analyze data for development (e.g. via household surveys). We also demonstrate that using big data analyses to address development challenges raises a number of questions that can deteriorate its impact.

    KW - Big data

    KW - International development

    KW - Governmentality

    KW - Algorithms

    KW - Knowledge production

    M3 - Paper

    ER -

    Flyverbom M, Madsen AK, Rasche A. Big Data as Governmentality: How Large-Scale Data Reshapes International Development. 2014. Paper presented at 55th ISA Annual Convention, Toronto, Canada.