Enhancing User Interfaces to Support Privacy Mental Models

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A key aspect of privacy considers the human users who make critical decisions and interact with privacy mechanisms to protect their personal information. Users' perceptions and interactions with processes and technology are guided by their mental models. The long-term goal of my research program is to design, develop, and evaluate software tools and methods to support users' mental models of privacy and improve the usability, transparency, and control of privacy interfaces and mechanisms. My research program's first objective (O1) is to develop feedback systems to support decision-making as countermeasures for privacy-compromising manipulative interfaces (i.e., privacy dark patterns). We will develop just-in-time warning systems and educational games to help users recognize and avoid these patterns. The design of these tools will be informed by a research-driven design process, learning science, iterative prototyping, and user studies showing evidence of engagement and learning outcomes. The second objective (O2) will examine methodological approaches and tools for identifying conceptual and visual metaphors that support mental models of emerging technologies. We will develop visualization tools for collecting and analyzing privacy "stories", usage scenarios, and information flows. We will use the data to identify users' perceptions, mental models, and metaphors of privacy in the context of emerging technology, such as the Internet of Things (IoT) in smart home environments. The research activities will advance our understanding of the visual and conceptual metaphors of privacy in emerging technology, which can aid the design of new privacy interfaces and imagery. In the third and final objective (O3), we will develop tools to support users' mental models in specialized situations with distinct privacy requirements. We propose starting with parent-child caregiving situations when privacy preferences are delegated to a trusted proxy. We will develop a model that describes how these users should be supported and identify specialized privacy personas to cluster users based on their attitudes and behaviours towards privacy in these situations. Next, we will use participatory design techniques to develop and evaluate new tools designed to facilitate privacy interactions and build mental models, such as a privacy-preserving parental control system with educational feedback. Major outcomes of this research will include empirically validated tools, methods, and user interface design principles for supporting users' privacy decision-making processes. Trainees under the research program will gain evidence-based, multidisciplinary research skills in human-computer interaction (HCI), usable privacy, user experience (UX), and user interface (UI) design, which are critical for addressing future privacy challenges in Canada and worldwide.