From Awareness to Action: Exploring End-User Empowerment Interventions for Dark Patterns in UX
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Abstract (arXiv)
The study of UX dark patterns, i.e., UI designs that seek to manipulate user behaviors, often for the benefit of online services, has drawn significant attention in the CHI and CSCW communities in recent years. To complement previous studies in addressing dark patterns from (1) the designer's perspective on education and advocacy for ethical designs; and (2) the policymaker's perspective on new regulations, we propose an end-user-empowerment intervention approach that helps users (1) raise the awareness of dark patterns and understand their underlying design intents; (2) take actions to counter the effects of dark patterns using a web augmentation approach. Through a two-phase co-design study, including 5 co-design workshops (N=12) and a 2-week technology probe study (N=15), we reported findings on the understanding of users' needs, preferences, and challenges in handling dark patterns and investigated the feedback and reactions to users' awareness of and action on dark patterns being empowered in a realistic in-situ setting.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Oct 2023.
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Citing papers per year: 2024: 1; 2025: 2; 2026: 2.
5 papers.
- 2025Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversightcited by 15
- 2025Measuring and mitigating overreliance to build human-compatible AIcited by 9
- 2024How Do Users Negotiate Harmful Value Conflicts with AI Companions? A Study with Minion, a Technology Probe for In-Situ Human-AI Conflict Responsecited by 1
- 2026Designing Proactive Thought Partners for Writingcited by 1
- 2026AI Watchdog: Agent Interfaces for Detecting and Defending Against Manipulative Dark Patterns in AI Conversationscited by 0
- 2026Designing Proactive Thought Partners for Writing1 Sep 2026
- 2026AI Watchdog: Agent Interfaces for Detecting and Defending Against Manipulative Dark Patterns in AI Conversations22 Aug 2026
- 2025Dark Patterns Meet GUI Agents: LLM Agent Susceptibility to Manipulative Interfaces and the Role of Human Oversight12 Sep 2025
- 2025Measuring and mitigating overreliance to build human-compatible AI8 Sep 2025
- 2024How Do Users Negotiate Harmful Value Conflicts with AI Companions? A Study with Minion, a Technology Probe for In-Situ Human-AI Conflict Response11 Nov 2024