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Deconstructing datafication’s brave new world
Open accessAbstract
As World Economic Forum’s definition of personal data as ‘the new “oil” – a valuable resource of the 21st century’ shows, large-scale data processing is increasingly considered the defining feature of contemporary economy and society. Commercial and governmental discourse on data frequently argues its benefits, and so legitimates its continuous and large-scale extraction and processing as the starting point for developments in specific industries, and potentially as the basis for societies as a whole. Against the background of the General Data Protection Regulation, this article unravels how general discourse on data covers over the social practices enabling collection of data, through the analysis of high-profile business reports and case studies of health and education sectors. We show how conceptualisation of data as having a natural basis in the everyday world protects data collection from ethical questioning while endorsing the use and free flow of data within corporate control, at the expense of its potentially negative impacts on personal autonomy and human freedom.
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“Yet, outreach strategies must also remain vigilant: AI-powered tools embedded in social platforms (e.g., chatbots like Meta AI) may influence civic discourse by prioritizing algorithmic popularity over democratic deliberation (Couldry and Yu 2018; Gal 2025).”
From Digital civics in action: the promise and emerging practices of generative AI in grassroots community advocacy (2026) · cites this paper as Couldry and Yu 2018
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“Yet, outreach strategies must also remain vigilant: AI-powered tools embedded in social platforms (e.g., chatbots like Meta AI) may influence civic discourse by prioritizing algorithmic popularity over democratic deliberation (Couldry and Yu 2018; Gal 2025).”
THE DYNAMICS OF DIGITAL CAPTURE: HOW INDUSTRIES TIE AUDIENCES TO EMERGING TECHNOLOGIES
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Metadata
- Authors
- Couldry, N., & Yu, J.
- Affiliations
- London School of Economics and Political Science (GB)
- London School of Economics and Political Science, UK
- ORCID
- Venue
- New Media & Society
- Publisher
- SAGE Publications
- Published
- 2018-05-19
- Volume
- 20
- Issue
- 12
- Pages
- 4473-4491
- ISSN
- 1461-4448 (ISSN-L)
- 1461-7315
- OpenAlex
- W2799457552
- Cited by
- 116
- References
- 44
- Citations by year
- 2026: 7 · 2025: 8 · 2024: 13 · 2023: 7 · 2022: 18 · 2021: 21 · 2020: 28 · 2019: 11 · 2018: 3
- FWCI
- 31.29
- Type
- journal article
- Language
- en
- Open access
- green
- orcid.org
- Locations
- New Media & Society (publishedVersion, public-domain)
- London School of Economics and Political Science Research Online (London School of Economics and Political Science) (acceptedVersion)
- London School of Economics and Political Science Theses Online (London School of Economics and Political Science) (submittedVersion)
- Funders
- John Templeton Foundation
- University of Chicago
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Law › Digitalization, Law, and Regulation
- Social Sciences › Communication › Cultural Studies and Postmodernism
- Keywords
- datafication, personal data, General Data Protection Regulation, data ethics, data collection, individual autonomy, health data, educational data, business reports
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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