HCI Design for Trustworthy Organic Computing

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A core feature of OC-systems is their ability to automatically adjust to dynamically changing usage and context conditions. OC-systems confront developers of user Interface concepts with a rather challenging task since it cannot always be assumed that sudden and often unexpected adjustments are automatically self-explanatory. Rather, there is the risk that users do not understand the rationale behind the system's behavior and wonder why a system has adapted in a specific manner. This in turn may lead to a loss of trust and in the worst case a rejection of the system. The objective of the project is the development of trustworthy user interfaces that are able to cope with these challenges.To achieve this objective, we developed a decision-theoretic approach to trust management on the basis of Bayesian Networks. The resulting User Trust Model (UTM) assesses the user's trust in a system, monitors it over time and applies appropriate system actions to maintain trust in critical situations, such as the generation of explanations to increase a system's transparency. To implement system actions, we rely on a constraint solver which allows us to define hard and soft behavioral corridors at design time which are automatically checked at run time. The developed methods and techniques are evaluated using demonstrators consisting of heterogeneous flexibly combinable interaction devices and displays. The demonstrators under investigation integrate public displays (called public screen), private and mobile displays (smart phones, tablets) and semi-public displays, such as interactive tables (Microsoft Surface). The resulting system class is called Trusted Display Grid, in short TDG.To ensure broad applicability of the methods and techniques in the project, we gradually increased the heterogeneity and complexity of the user interfaces under investigation. For phase 3, we will focus on the following objectives:(1) modeling Interaction and presentation concepts for highly dynamic TDG environments(2) generalization of the User Trust Modela. prediction of user trust on the basis of uncertain context informationb. optimization of measures to enhance trust for multiple users interacting in parallel(3) further development of a demonstrator using the TEMAS (Trust-Enabling Multi Agent System) and moTEM (a mobile version of the Trust-Enabling Middleware) platforms to validate the User Trust Model