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.
    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.

    Conference

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

    Keywords

      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.