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Ethics of quantification: illumination, obfuscation and performative legitimation

Author

Listed:
  • Siddharth Sareen

    (University of Bergen
    University of Bergen)

  • Andrea Saltelli

    (University of Bergen)

  • Kjetil Rommetveit

    (University of Bergen)

Abstract

The increasing use of quantification in all spheres of society is paralleled by the rise of digitalisation. These intertwining developments not only revolutionise data treatment, but also its societal effects. On the one hand, they have wonderfully enabling societal effects. On the other hand, they give rise to complex ethical dilemmas that motivate this call for an ethics of quantification. The central claim of this Comment is that quantification necessarily has two faces: illumination and obfuscation. Aspects that can be socially legitimated are illuminated, while those that cannot be so legitimated are obfuscated. This obfuscation poses ethical problems, hence its effects require rigorous analysis. Three ontologies of quantification are delineated to enable such examination: (i) as the disembodied practice of data processing in the ‘ether’—this foregrounds elements of big data and artificial intelligence; (ii) as the situated practice and effects of quantification within societal contexts—this attends to governing subjects through numbers; and (iii) as increasingly incorporated in physical reality—this focuses on governmentality of behaviours and behavioural change as mediated through everyday objects through an ‘Internet of Things’. Drawing on scholarship from the emerging sociology of quantification, the ethics of quantification is defined as the iterative illumination of obfuscation in legitimation by quantification. This is key for ensuring contextually desirable illuminating functions of quantification in all three ontologies.

Suggested Citation

  • Siddharth Sareen & Andrea Saltelli & Kjetil Rommetveit, 2020. "Ethics of quantification: illumination, obfuscation and performative legitimation," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-5, December.
  • Handle: RePEc:pal:palcom:v:6:y:2020:i:1:d:10.1057_s41599-020-0396-5
    DOI: 10.1057/s41599-020-0396-5
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    References listed on IDEAS

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    1. Valentin Amrhein & Sander Greenland & Blake McShane, 2019. "Scientists rise up against statistical significance," Nature, Nature, vol. 567(7748), pages 305-307, March.
    2. Andrea Saltelli, 2019. "A short comment on statistical versus mathematical modelling," Nature Communications, Nature, vol. 10(1), pages 1-3, December.
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    Cited by:

    1. Marta Kuc-Czarnecka & Samuele Lo Piano & Andrea Saltelli, 2020. "Quantitative Storytelling in the Making of a Composite Indicator," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(3), pages 775-802, June.
    2. Marta Kuc-Czarnecka & Magdalena Olczyk, 2020. "How ethics combine with big data: a bibliometric analysis," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-9, December.
    3. Siddharth Sareen, 2020. "Social and technical differentiation in smart meter rollout: embedded scalar biases in automating Norwegian and Portuguese energy infrastructure," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-8, December.
    4. Andrea Saltelli & Monica Fiore, 2020. "From sociology of quantification to ethics of quantification," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-8, December.
    5. Samuele Lo Piano, 2020. "Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-7, December.
    6. Jill Walker Rettberg, 2020. "Situated data analysis: a new method for analysing encoded power relationships in social media platforms and apps," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.

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