Abstract. Explanations play an important part in the interaction with any intelligent system. This is particular important in context-aware and social awareness systems that regularly assume responsibility for a user and act proactively. Explanations are often generated using all available information. However, privacy issues in context-aware systems might dictate a limited distribution of information. The work presented here demonstrates how personal awareness-systems can fulfil different goals a user can have towards explanations, yet maintain a sensible level of privacy. 1

Abstract. The ability to give explanations for its reasoning and behaviour is a core capability of an intelligent system. There are a number of different goals a user can have towards such explanations. This paper presents how the knowledge intensive case-based reasoning framework CREEK can support some of these different goals in an ambient intelligence setting. Keywords. Case-based reasoning, ambient intelligence, explanation

Abstract. Bayesian Networks are useful for solving a wide range of problems in many domains. Yet, they are exposed to one important challenge when structural and parametrical changes occur. As Bayesian networks lack memory regarding changes over time, there is currently no good way of maintaining a history of changes and their provenance. Thus, any variance in the network’s problem solving behaviour will not be explainable to a user. Within the context of systems that integrate case-based reasoning and Bayesian networks, we suggest to add a casebased reasoning functionality that will retain changes and their provenance, as well as approaches to explain any unexpected problem solving behaviour. 1

Abstract. In this paper, we describe our current research concerning users ’ mental models of what can be called “disappearing computer systems”. This notion comprises computer systems, applications, and appliances related to ubiquitous, pervasive, or ambient computing which blend more or less seamlessly into the users ’ natural environment. Mental models enable users to formulate expectations about which interactions with the system are possible and how the system will react to certain interactions. Disappearing computers lack certain cues regarding the inner workings of the system. We thus hypothesize that the mental models users build of such a system will show defects and inaccuracies that are directly related to the distributed character of interface and interaction. Our current research aims at identifying the nature of these defects, understanding their effects on human computer interaction, and developing means of avoiding them through appropriate design of both user interface and underlying system. For this purpose, we are developing an ambient, context aware computing framework with which we generate and test hypotheses in an action research paradigm. One of its components will be described along with possible future additions. The theoretical foundation of our work lies in such diverse fields as systemic functional theory of language, activity theory, and cognitive science approaches to mental models. 1