Ethics of quantification: illumination, obfuscation and performative legitimation
Open accessAbstract
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.
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In many fields, an increasing amount of functions are being ceded to algorithms to the detriment of human control, raising concern for loss of fairness and equitability.
“In all these fields, an increasing amount of functions are being ceded to algorithms to the detriment of human control, raising concern for loss of fairness and equitability (Sareen et al., 2020).”
From Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward (2020) · cites this paper as Sareen et al., 2020
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“In all these fields, an increasing amount of functions are being ceded to algorithms to the detriment of human control, raising concern for loss of fairness and equitability (Sareen et al., 2020).”
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- Authors
- Sareen, S., Saltelli, A., & Rommetveit, K.
- Affiliations
- University of Bergen (NO)
- Corresponding author
- Sareen, Siddharth
- Venue
- Palgrave Communications
- Published
- 2020-01-31
- Volume
- 6
- Issue
- 1
- ISSN
- 2055-1045 (ISSN-L)
- OpenAlex
- W3004712712
- Cited by
- 45
- References
- 35
- Citations by year
- 2026: 12 · 2025: 2 · 2024: 5 · 2023: 6 · 2022: 3 · 2021: 7 · 2020: 10
- FWCI
- 8.86
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Humanities and Social Sciences Communications (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Universitetet i Bergen
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Social Sciences › Sociology and Political Science › Foucault, Power, and Ethics
- Keywords
- quantification, digitalization, big data, artificial intelligence, sociology of quantification, legitimation, obfuscation, illumination, governmentality, Internet of Things, behavior change, data processing
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