The Dark Side of Augmented Reality: Exploring Manipulative Designs in AR
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Abstract (arXiv)
Augmented Reality (AR) applications are becoming more mainstream, with successful examples in the mobile environment like Pokemon GO. Current malicious techniques can exploit these environments' immersive and mixed nature (physical-virtual) to trick users into providing more personal information, i.e., dark patterns. Dark patterns are deceiving techniques (e.g., interface tricks) designed to influence individuals' behavioural decisions. However, there are few studies regarding dark patterns' potential issues in AR environments. In this work, using scenario construction to build our prototypes, we investigate the potential future approaches that dark patterns can have. We use VR mockups in our user study to analyze the effects of dark patterns in AR. Our study indicates that dark patterns are effective in immersive scenarios, and the use of novel techniques such as `haptic grabbing' to drag participants' attention can influence their movements. Finally, we discuss the impact of such malicious techniques and what techniques can mitigate them.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Mar 2023.
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Citing papers per year: 2024: 1; 2025: 2; 2026: 1.
4 papers.
- 2024Sora as a World Model? A Complete Survey on Text-to-Video Generationcited by 53
- 2025ViDDAR: Vision Language Model-Based Task-Detrimental Content Detection for Augmented Realitycited by 16
- 2025Do We Need Responsible XR? Drawing on Responsible AI to Inform Ethical Research and Practice into XRAI / the Metaversecited by 0
- 2026The Shadow Boss: Identifying Atomized Manipulations in Agentic Employment of XR Users using Scenario Constructionscited by 0
- 2026The Shadow Boss: Identifying Atomized Manipulations in Agentic Employment of XR Users using Scenario Constructions14 Feb 2026
- 2025Do We Need Responsible XR? Drawing on Responsible AI to Inform Ethical Research and Practice into XRAI / the Metaverse6 Apr 2025
- 2025ViDDAR: Vision Language Model-Based Task-Detrimental Content Detection for Augmented Reality22 Jan 2025
- 2024Sora as a World Model? A Complete Survey on Text-to-Video Generation8 Mar 2024