mlsanityData to 14 Oct 2026

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

arXiv 2001.02479 ↗First posted 8 Jan 2020cs.HC cs.CYcited by 27

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Abstract (arXiv)

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 the minimal requirements that we set 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.

Key facts. Cited by 27 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Jan 2020.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 5; 2024: 5; 2025: 4; 2026: 10.

27 papers.

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  1. 2024LLM Whisperer: An Inconspicuous Attack to Bias LLM Responsescited by 15
  2. 2025DECEPTICON: How Dark Patterns Manipulate Web Agentscited by 15
  3. 2023Designing Fiduciary Artificial Intelligencecited by 8
  4. 2025SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agentscited by 8
  5. 2022Regulating Gatekeeper AI and Data: Transparency, Access, and Fairness under the DMA, the GDPR, and beyondcited by 4
  6. 2021A Decentralized Approach towards Responsible AI in Social Ecosystemscited by 3
  7. 2022Automated detection of dark patterns in cookie banners: how to do it poorly and why it is hard to do it any other waycited by 3
  8. 2024Locally Private Estimation with Public Featurescited by 3
  9. 2025On the Regulatory Potential of User Interfaces for AI Agent Governancecited by 3
  10. 2026More Human or More AI? Visualizing Human-AI Collaboration Disclosures in Journalistic News Productioncited by 3
  11. 2026Convenience vs. Control: A Qualitative Study of Youth Privacy with Smart Voice Assistantscited by 2
  12. 2023Automating privacy decisions -- where to draw the line?cited by 1
15 more
  1. 2023Targeted and Troublesome: Tracking and Advertising on Children's Websitescited by 1
  2. 2026Jurisdiction as Structural Barrier: How Privacy Policy Organization May Reduce Visibility of Substantive Disclosurescited by 1
  3. 2023Mapping the Empirical Evidence of the GDPR (In-)Effectiveness: A Systematic Reviewcited by 0
  4. 2023Why is the User Interface a Dark Pattern? : Explainable Auto-Detection and its Analysiscited by 0
  5. 2024Mapping the Scholarship of Dark Pattern Regulation: A Systematic Review of Concepts, Regulatory Paradigms, and Solutions from an Interdisciplinary Perspectivecited by 0
  6. 2024From Exploration to Revelation: Detecting Dark Patterns in Mobile Appscited by 0
  7. 2024How To Think About End-To-End Encryption and AI: Training, Processing, Disclosure, and Consentcited by 0
  8. 2025Using Salient Object Detection to Identify Manipulative Cookie Banners that Circumvent GDPRcited by 0
  9. 2026From Fragmentation to Integration: Exploring the Design Space of AI Agents for Human-as-the-Unit Privacy Managementcited by 0
  10. 2026On the Suitability of LLM-Driven Agents for Dark Pattern Auditscited by 0
  11. 2026Tiny, Hardware-Independent, Compression-based Classificationcited by 0
  12. 2026Designing for Disagreement: Front-End Guardrails for Assistance Allocation in LLM-Enabled Robotscited by 0
  13. 2026The Privacy Guardian Agent: Towards Trustworthy AI Privacy Agentscited by 0
  14. 2026Privacy Washing: Detecting Internal Contradictions in Privacy Policiescited by 0
  15. 2026Before Acting, Change the State: Prospective State Intervention for Web Agents under Deceptive Interfacescited by 0