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Fitness trackers are an increasingly popular tool for tracking one’s health and physical activity. While research has evaluated the potential benefits of these devices for health and well-being, few studies have empirically evaluated users’ behaviors when sharing personal fitness information (PFI) and the privacy concerns that stem from the collection, aggregation, and sharing of PFI. In this study, we present findings from a survey of Fitbit and Jawbone users (N=361) to understand how concerns about privacy in general and user- generated data in particular affect users’ mental models of PFI privacy, tracking, and sharing. Findings highlight the complex relationship between users’ demographics, sharing behaviors, privacy concerns, and internet skills with how valuable and sensitive they rate their PFI. We conclude with a discussion of opportunities to increase user awareness of privacy and PFI.
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This content will become publicly available on September 27, 2026
Imago Obscura: An Image Privacy AI Co-pilot to Enable Identification and Mitigation of Risks
Users often struggle to navigate the privacy / publicity boundary in sharing images online: they may lack awareness of image privacy risks and/or the ability to apply effective mitigation strategies. To address this challenge, we introduce and evaluate Imago Obscura, an AI-powered, image-editing copilot that enables users to identify and mitigate privacy risks with images they intend to share. Driven by design requirements from a formative user study with 7 imageediting experts, Imago Obscura enables users to articulate their image-sharing intent and privacy concerns. The system uses these inputs to surface contextually pertinent privacy risks, and then recommends and facilitates application of a suite of obfuscation techniques found to be effective in prior literature — e.g., inpainting, blurring, and generative content replacement. We evaluated Imago Obscura with 15 end-users in a lab study and found that it greatly improved users’ awareness of image privacy risks and their ability to address those risks, allowing them to make more informed sharing decisions.
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- Award ID(s):
- 2316294
- PAR ID:
- 10659351
- Publisher / Repository:
- ACM
- Date Published:
- Page Range / eLocation ID:
- 1 to 26
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Fitness trackers are an increasingly popular tool for tracking one’s health and physical activity. While research has evaluated the potential benefits of these devices for health and well-being, few studies have empirically evaluated users’ behaviors when sharing personal fitness information (PFI) and the privacy concerns that stem from the collection, aggregation, and sharing of PFI. In this study, we present findings from a survey of Fitbit and Jawbone users (N=361) to understand how concerns about privacy in general and user- generated data in particular affect users’ mental models of PFI privacy, tracking, and sharing. Findings highlight the complex relationship between users’ demographics, sharing behaviors, privacy concerns, and internet skills with how valuable and sensitive they rate their PFI. We conclude with a discussion of opportunities to increase user awareness of privacy and PFI.more » « less
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