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Dark Patterns after the GDPR: Scraping Consent Pop-ups and Demonstrating their Influence

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

DOI

  • Midas Nouwens
  • Ilaria Liccardi, Massachusetts Institute of Technology
  • ,
  • Michael Veale, University College London
  • ,
  • David Karger, Massachusetts Institute of Technology
  • ,
  • Lalana Kagal, Massachusetts Institute of Technology

New consent management platforms (CMPs) have been introduced to the web to conform with the EU's General Data Protection Regulation, particularly its requirements for consent when companies collect and process users' personal data. This work analyses how the most prevalent CMP designs affect people's consent choices. We scraped the designs of the five most popular CMPs on the top 10,000 websites in the UK (n=680). We found that dark patterns and implied consent are ubiquitous; only 11.8% meet our minimal requirements based on European law. Second, we conducted a field experiment with 40 participants to investigate how the eight most common designs affect consent choices. We found that notification style (banner or barrier) has no effect; removing the opt-out button from the first page increases consent by 22-23 percentage points; and providing more granular controls on the first page decreases consent by 8-20 percentage points. This study provides an empirical basis for the necessary regulatory action to enforce the GDPR, in particular the possibility of focusing on the centralised, third-party CMP services as an effective way to increase compliance.

Original languageEnglish
Title of host publicationCHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Number of pages13
Place of publicationNew York
PublisherAssociation for Computing Machinery
Publication year2020
Article number3376321
ISBN (Electronic)9781450367080
DOIs
Publication statusPublished - 2020
Event2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020 - Honolulu, United States
Duration: 25 Apr 202030 Apr 2020

Conference

Conference2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020
LandUnited States
ByHonolulu
Periode25/04/202030/04/2020
SponsorACM SIGCHI

    Research areas

  • consent management platforms, controlled experiment, dark patterns, gdpr, notice and consent, web scraper

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