Abstract: Even though adaptive (trainable) spam filters are a common example of systems that make (semi-)autonomous decisions on behalf of the user, trust in these filters has been underexplored. This paper reports a study of usage of spam filters in the daily workplace and user behaviour in training these filters (N=43). User observation, interview and survey techniques were applied to investigate attitudes towards two types of filters: a user-adaptive (trainable) and a rule-based filter. While many of our participants invested extensive effort in training their filters, training did not influence filter trust. Instead, the findings indicate that users' filter awareness and understanding seriously impacts attitudes and behaviour. Specific examples of difficulties related to awareness of filter activity and adaptivity are described showing concerns relevant to all adaptive and (semi-)autonomous systems that rely on explicit user feedback.
Abstract: The investigations presented in this thesis are part of the 'Integrated Collaborative Information Systems' (ICIS) project, focussing on the 'Enhanced Situation Awareness' (ESA). As a partner in ths project, we investigated the feasibility of using morphologicallt elaborate model neurons to enhance robustness and adaptivity in robotic systems.