I am Definitely Manipulated, Even When I am Aware of it. It s Ridiculous! -- Dark Patterns from the End-User Perspective
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Abstract (arXiv)
Online services pervasively employ manipulative designs (i.e., dark patterns) to influence users to purchase goods and subscriptions, spend more time on-site, or mindlessly accept the harvesting of their personal data. To protect users from the lure of such designs, we asked: are users aware of the presence of dark patterns? If so, are they able to resist them? By surveying 406 individuals, we found that they are generally aware of the influence that manipulative designs can exert on their online behaviour. However, being aware does not equip users with the ability to oppose such influence. We further find that respondents, especially younger ones, often recognise the "darkness" of certain designs, but remain unsure of the actual harm they may suffer. Finally, we discuss a set of interventions (e.g., bright patterns, design frictions, training games, applications to expedite legal enforcement) in the light of our findings.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 26 Apr 2021.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 3; 2026: 1.
8 papers.
- 2025Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversightcited by 15
- 2025DECEPTICON: How Dark Patterns Manipulate Web Agentscited by 13
- 2023Designing Fiduciary Artificial Intelligencecited by 8
- 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
- 2024The Voice: Lessons on Trustworthy Conversational Agents from "Dune"cited by 1
- 2024From Exploration to Revelation: Detecting Dark Patterns in Mobile Appscited by 0
- 2025Deception at Scale: Deceptive Designs in 1K LLM-Generated Ecommerce Componentscited by 0
- 2026Responsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot Interactioncited by 0
- 2026Responsible Personalisation: The Double-Edged Sword of Personalisation in Human-Robot Interaction7 Jul 2026
- 2025DECEPTICON: How Dark Patterns Manipulate Web Agents28 Dec 2025
- 2025Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight12 Sep 2025
- 2025Deception at Scale: Deceptive Designs in 1K LLM-Generated Ecommerce Components19 Feb 2025
- 2024From Exploration to Revelation: Detecting Dark Patterns in Mobile Apps27 Nov 2024
- 2024The Voice: Lessons on Trustworthy Conversational Agents from "Dune"10 Jul 2024
- 2023Designing Fiduciary Artificial Intelligence27 Jul 2023
- 2022Automated detection of dark patterns in cookie banners: how to do it poorly and why it is hard to do it any other way21 Apr 2022