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As Extended Reality (XR) devices become increasingly prevalent in everyday settings, they raise significant privacy concerns for bystanders: individuals in the vicinity of an XR device during its use, whom the device sensors may accidentally capture. Current privacy indicators, such as small LEDs, often presume that bystanders are attentive enough to interpret the privacy signals. However, these cues can be easily overlooked when bystanders are distracted or have limited vision. We define such individuals as situationally impaired bystanders. This study explores XR privacy indicator designs that are effective for situationally impaired bystanders. A focus group with eight participants was conducted to design five novel privacy indicators. We evaluated these designs through a user study with seven additional participants. Our results show that visual-only indicators, typical in commercial XR devices, received low ratings for perceived usefulness in impairment scenarios. In contrast, multimodal indicators were preferred in privacy-sensitive scenarios with situationally impaired bystanders. Ultimately, our results highlight the need to move toward adaptable, multimodal, and situationally aware designs that effectively support bystander privacy in everyday XR environments.
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Rethinking Privacy Indicators in Extended Reality: Multimodal Design for Situationally Impaired Bystanders (Dataset)
URL: https://zenodo.org/records/18612884 This dataset accompanies the paper: “Rethinking Privacy Indicators in Extended Reality: Multimodal Design for Situationally Impaired Bystanders” (DOI: 10.1109/ISMAR-Adjunct68609.2025.00059). The dataset includes: 1- Focus Group Responses: Anonymized qualitative responses from four focus groups exploring bystander privacy indicators for mixed reality (MR) head-mounted displays. The document includes raw participant feedback and the finalized indicator concepts derived from these discussions. 2- User Study Responses: Anonymized quantitative and qualitative responses collected during the user study evaluating the proposed privacy indicators. All responses have been anonymized to remove personally identifiable information.
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- Award ID(s):
- 2350116
- PAR ID:
- 10665113
- Publisher / Repository:
- Zenodo
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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