Scott Lederer

Heuristic evaluation of ambient displays

We present a technique for evaluating the usability and effectiveness of ambient displays. Ambient displays are abstract and aesthetic peripheral displays portraying non-critical information on the periphery of a users attention. Although many innovative displays have been published, little existing work has focused on their evaluation, in part because evaluation of ambient displays is difficult and costly. We adapted a low-cost evaluation technique, heuristic evaluation, for use with ambient displays. With the help of ambient display designers, we defined a modified set of heuristics. We compared the performance of Nielsens heuristics and our heuristics on two ambient displays. Evaluators using our heuristics found more, severe problems than evaluators using Nielsens heuristics. Additionally, when using our heuristics, 3-5 evaluators were able to identify 40--60% of known usability issues. This implies that heuristic evaluation is an effective technique for identifying usability issues with ambient displays.

Personal privacy through understanding and action: five pitfalls for designers

To participate in meaningful privacy practice in the context of technical systems, people require opportunities to understand the extent of the systems’ alignment with relevant practice and to conduct discernible social action through intuitive or sensible engagement with the system. It is a significant challenge to design for such understanding and action through the feedback and control mechanisms of today’s devices. To help designers meet this challenge, we describe five pitfalls to beware when designing interactive systems—on or off the desktop—with personal privacy implications. These pitfalls are: (1) obscuring potential information flow, (2) obscuring actual information flow, (3) emphasizing configuration over action, (4) lacking coarse-grained control, and (5) inhibiting existing practice. They are based on a review of the literature, on analyses of existing privacy-affecting systems, and on our own experiences in designing a prototypical user interface for managing privacy in ubiquitous computing. We illustrate how some existing research and commercial systems—our prototype included—fall into these pitfalls and how some avoid them. We suggest that privacy-affecting systems that heed these pitfalls can help users appropriate and engage them in alignment with relevant privacy practice.

Who wants to know what when? privacy preference determinants in ubiquitous computing

We conducted a questionnaire-based study of the relative importance of two factors, inquirer and situation, in determining the preferred accuracy of personal information disclosed through a ubiquitous computing system. We found that privacy preferences varied by inquirer more than by situation. That is, individuals were more likely to apply the same privacy preferences to the same inquirer in different situations than to apply the same privacy preferences to different inquirers in the same situation. We are applying these results to the design of a user interface for managing everyday privacy in ubiquitous computing.

Privacy risk models for designing privacy-sensitive ubiquitous computing systems

Privacy is a difficult design issue that is becoming increasingly important as we push into ubiquitous computing environments. While there is a fair amount of theoretical work on designing for privacy, there are few practical methods for helping designers create applications that provide end-users with a reasonable level of privacy protection that is commensurate with the domain, with the community of users, and with the risks and benefits to all stakeholders in the intended system. Towards this end, we propose privacy risk models as a general method for refining privacy from an abstract concept into concrete issues for specific applications and prioritizing those issues. In this paper, we introduce a privacy risk model we have developed specifically for ubiquitous computing, and outline two case studies describing our use of this privacy risk model in the design of two ubiquitous computing applications.