Cited by 156Digitalization, Law, and RegulationEthics and Social Impacts of AIPrivacy, Security, and Data Protection

Forgetting Footprints, Shunning Shadows. A Critical Analysis Of The “Right To Be Forgotten” In Big Data Practice

Open access
Koops, Bert-Jaap·2011·SCRIPTed: A Journal of Law, Technology & Society

Abstract

The so-called “right to be forgotten” has been put firmly on the agenda, both of academia and of policy. Although the idea is intuitive and appealing, the legal form and practical implications of a right to be forgotten have hardly been analysed so far. This contribution aims to critically assess what a right to be forgotten could or should entail in practice. It outlines the current socio-technical context as one of Big Data, in which massive data collections are created and mined for many purposes. Big Data involves not only individuals’ digital footprints (data they themselves leave behind) but, perhaps more importantly, also individuals’ data shadows (information about them generated by others). And contrary to physical footprints and shadows, their digital counterparts are not ephemeral but persistent. This presents particular challenges for the right to be forgotten, which are discussed in the form of three key questions. Against whom can the right be invoked? When and why can the right be invoked? And how can the right be effected? Advocates of a right to be forgotten must clarify which conceptualisation of such a right they favour – a comprehensive, usercontrol-based right to have data deleted in due time, or a narrower, context-specific right to a “clean slate” – and how they think the considerable obstacles presented in this paper can be overcome, if people are really to be enabled to have their digital footprints forgotten and to shun their data shadows.

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 · 10.2966/scrip.080311.229

Cites

Statistics

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?

  • The increased density of recorded life events could undermine the adaptive function of forgetting.

    “the increased density of recorded life events could undermine the adaptive function of forgetting (Heersmink, 2017;Heersmink & Carter, 2020;Koops, 2011;Jacquemard et al., 2014;Mayer-Sch€ onberger, 2009;Storm & Soares, in press;van House & Churchill, 2008).”

Self-check

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

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

Cited by

Sorted by citations

Authors
Koops, B.-J.
Affiliations
Tilburg University (NL)
Corresponding author
Koops, Bert-Jaap
Venue
SCRIPTed: A Journal of Law, Technology & Society
Published
2011-12-01
Volume
8
Issue
3
Pages
229-256
ISSN
1744-2567 (ISSN-L)
OpenAlex
W2108830329
Cited by
156
References
0
Citations by year
2026: 2 · 2025: 5 · 2024: 5 · 2023: 7 · 2022: 5 · 2021: 39 · 2020: 23 · 2019: 5 · 2018: 16 · 2017: 7 · 2016: 11 · 2015: 3 · 2014: 18 · 2013: 7 · 2012: 3
FWCI
113.09
Type
journal article
Language
en
Open access
Locations
  • SCRIPTed A Journal of Law Technology & Society (publishedVersion, cc-by-nc-nd)
  • SSRN Electronic Journal (acceptedVersion)
  • Data Archiving and Networked Services (DANS) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
European Commission
Topics
  • Social Sciences › Law › Digitalization, Law, and Regulation
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
Keywords
right to be forgotten, big data, digital footprint, data deletion, personal data protection, clean slate, user control, data persistence, privacy law

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