http://dl.gi.de/handle/20.500.12116/11098 2026-09-06T19:57:13Z http://dl.gi.de/handle/20.500.12116/11456 Is it Research or is it Spying? Thinking-Through Ethics in Big Data AI and Other Knowledge Sciences Berendt, Bettina; Büchler, Marco; Rockwell, Geoffrey “How to be a knowledge scientist after the Snowden revelations?” is a question we all have to ask as it becomes clear that our work and our students could be involved in the building of an unprecedented surveillance society. In this essay, we argue that this affects all the knowledge sciences such as AI, computational linguistics and the digital humanities. Asking the question calls for dialogue within and across the disciplines. In this article, we will position ourselves with respect to typical stances towards the relationship between (computer) technology and its uses in a surveillance society, and we will look at what we can learn from other fields. We will propose ways of addressing the question in teaching and in research, and conclude with a call to action. 2015-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/11463 A Paradigm Shift in Healthcare Provision Sonntag, Daniel; Gelissen, Jean 2015-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/11453 Personalized Stress Management: Enabling Stress Monitoring with LifelogExplorer Kocielnik, Rafal; Sidorova, Natalia Stress is one of the major triggers for many diseases. Improving stress balance is therefore an important prevention step. With advances in wearable sensors, it becomes possible to continuously monitor and analyse user’s behavior and arousal in an unobtrusive way. In this paper, we report on a case study in which users (21 teachers of a vocational school) were provided with wearable sensors and could view their arousal information put in the context of their life events during the period of four weeks using our software tool in an unsupervised setting. The goal was to evaluate user engagement and enabling of self-coaching abilities. Our results show that users actively explored their arousal data during the study. Further qualitative evaluation conducted with 15 of 21 users indicated that 12 of 15 users were able to learn about their stress patterns based on the information they obtained, but only 5 of them were able to come up with practical interventions for improving their stress balance on their own, while other users were of opinion that nothing can be done to reduce their stress, which suggests that self-coaching has some potential but there is need in further coaching support. 2015-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/11467 Towards Configuration Planning with Partially Ordered Preferences: Representation and Results Silva-Lopez, Lia Susana d. C.; Broxvall, Mathias; Loutfi, Amy; Karlsson, Lars Configuration planning for a distributed robotic system is the problem of how to configure the system over time in order to achieve some causal and/or information goals. A configuration plan specifies what components (sensor, actuator and computational devices), should be active at different times and how they should exchange information. However, not all plans that solve a given problem need to be equally good, and for that purpose it may be important to take preferences into account. In this paper we present an algorithm for configuration planning that incorporates general partially ordered preferences. The planner supports multiple preference categories, and hence it solves a multiple-objective optimization problem: for a given problem, it finds all possible valid, non-dominated configuration plans. The planner has been able to successfully cope with partial ordering relations between quantitative preferences in practically acceptable times, as shown in the empirical results. Preferences here are represented as c-semirings, and are used for establishing dominance of a solution over another in order to obtain a set of configuration plans that will constitute the solution of a configuration planning problem with partially ordered preferences. The dominance operators tested in this paper are Pareto and Lorenz dominance. Our solver considers one guiding heuristic for obtaining the first solution, and then switches to a dominance based monotonically decreasing heuristic used for pruning dominated partial configuration plans. In our empirical results, we perform a statistical study in the space of problem instances and establish families of problems for which our approach is computationally feasible. 2015-01-01T00:00:00Z