CoChat
Sign Up
Cited by 116Ethics and Social Impacts of AIDigitalization, Law, and RegulationCultural Studies and Postmodernism

The DOI matches its Crossref record; 43 of the 44 references it cites were found in a registry or an index.

Deconstructing datafication’s brave new world

Open access
Couldry, Nick, Yu, Jun·2018·New Media & Society
DOI 10.1177/1461444818775968
Open this paper in CoChat — free accountOpen PDF

Abstract

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.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1177/1461444818775968

Cites

43 of 43 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 17

  1. Couldry N, Colonized by Data
  2. (European) General Data Protection Regulation (GDPR) (2016) REGULATION (EU) 2016/679 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 27 April 2016. Official Journal of the European Union. Available at: http://ec.europa.eu/justice/data-protection/reform/files/regulation_oj_en.pdf (accessed 20 September 2017)
  3. Gandy OH, 1993, The Panoptic Sort
  4. Ibarra IA, Goff L, Hernandez DJ, et al. (2017) Should we treat data as labor? Moving beyond ‘free’. American Economic Association Papers & Proceedings 1(1). Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3093683 (accessed 3 January 2018).
  5. IBM (2016) First IBM Watson Education App for iPad Delivers Personalized Learning for K-12 Teachers and Students. Available at: http://www-03.ibm.com/press/us/en/pressrelease/50815.wss (accessed 10 September 2017).
  6. IBM Newsroom (n.d.) Available at: https://www-03.ibm.com/press/us/en/index.wss (accessed 20 September 2017).
  7. Lanier J, 2014, Who Owns the Future?
  8. Lupton D, 2016, The Quantified Self
  9. Pearson (n.d.) Available at: https://www.pearson.com/ (accessed 15 September 2017).
  10. Pearson (2014a) Impacts of the digital ocean on education. Report, February. Available at: https://www.pearson.com/content/dam/one-dot-com/one-dot-com/global/Files/about-pearson/innovation/open-ideas/DigitalOcean.pdf (accessed 15 September 2017).
  11. Pearson (2014b) Preparing for a renaissance in assessment. Report, December. Available at: https://www.pearson.com/content/dam/one-dot-com/one-dot-com/uk/documents/educator/primary/preparing_for_a_renaissance_in_assessment_and_summary_text_december_2014.pdf
  12. Quan-Haase A, Wellman B (2005) Hyperconnected net work. Working Paper Series, KMDI-WP-2005-2, 9 June. Available at: https://pdfs.semanticscholar.org/41ec/9ad4f369d6ff7610554739b7c9ee0752d7cd.pdf (accessed 5 September 2017).
  13. Richards N, 2015, Intellectual Privacy
  14. Rifkin J, 2013, The Zero Marginal Cost Society
  15. Siemens G, 2012, Educational Technology and Society, 15, 1
  16. Weigend A, 2017, Data for the People
  17. Williamson B, 2016, Surveillance Futures, 50

Cited by

Sorted by citations

See all 116

Related

See all

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
DOI
10.1177/1461444818775968
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
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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 ›

Are you an author, or do you see a problem with this page? Request a review