Imago Obscura: An Image Privacy AI Co-pilot to Enable Identification and Mitigation of Risks

DOI

Users often struggle to navigate the privacy / publicity boundary in sharing images online: they may lack awareness of image privacy risks or the ability to apply effective mitigation strategies. To address this challenge, we introduce and evaluate Imago Obscura, an intent-aware AI-powered image-editing copilot that enables users to identify and mitigate privacy risks in images they intend to share. Driven by design requirements from a formative user study with 7 image-editing 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 improved users' awareness of image privacy risks and their ability to address them, enabling more informed sharing decisions.