Public displays may adapt intelligently to the social context, tailoring information on the screen, for example, to the profiles of spectators, their gender or based on their mutual proximity. However, such adaptation decisions should on the one hand match user preferences and on the other maintain the user's trust in the system. A wrong decision can negatively influence the user's acceptance of a system, cause frustration and, as a result, make users abandon the system. In this paper, we propose a trust-based mechanism for automatic decision-making, which is based on Bayesian Networks. We present the process of network construction, initialization with empirical data, and validation. The validation demonstrates that the mechanism generates accurate decisions on adaptation which match user preferences and support user trust.

Ubiquitous computing systems can cause serious problems for user trust. In particular if the system is self-adaptive and situations appear which are poorly self-explanatory. In this paper we aim at the trust management of adaptive systems. We present a user study that covers the correlation of trust dimensions and user feelings on user trust. As results of this study, a Bayesian Network is introduced that, at the design time and runtime of the system, provides knowledge about the interplay between a truster's disposition, system events and actions, trust dimensions, user trust and user response.

While a lot of research has been devoted to improving the security and the reliability of ubiquitous display environments, work on the user experience factor of trust is still scarce. To ensure that ubiquitous environments find acceptance among users, the user experience factor of trust should, however, not be underestimated. In this paper, we present a decision-theoretic approach to trust management that we consider particularly appropriate when a system has to balance the benefits and risks of a decision carefully. In the paper, we define decision policies that help maintain trust in critical situations, such as the loss of sensor data or the presence of unknown people. The approach has been employed in three interactive applications that have been developed as part of a university-wide ubiquitous displays management system.