Experience Research: a Methodology for Developing Human-centered Interfaces

At the turn of the century, a distinguished group of researchers identified the potential devastating effects of rapid technological developments, as described by the generalized Moore’s law, for the balanced relationship between humans and technology (Aarts et al., 2001). Whilst not ignoring the threads and risks of so called technology push, the Ambient Intelligence (AmI) vision was introduced to emphasize the positive contribution these technologies could bring to our daily lives. Within the AmI vision human needs are positioned centrally and technology is seen as a means to enrich our life. In course terms Ambient Intelligence refers to the embedding of technologies into electronic environments that are sensitive and responsive to the presence of people. In Ambient Intelligence, the term ambience refers to technology being embedded on a large scale in such a way that it becomes unobtrusively integrated into everyday life and environments. Hence, the ambient characteristic of AmI has both a physical and social meaning. The challenge for ambient technologies is to become invisible while still providing meaningful functionality to these end users (Weiser, 1991). Such challenge is not trivial to address and requires radical different approaches to human – system interaction (De Ruyter et al., 2005). The term intelligence reflects the situation in which the digital surroundings exhibit specific forms of cognition, i.e. the environments should be able to recognize the people that inhabit them, personalize according to individual preferences, adapt themselves to the users, learn from their behavior and possibly act upon their behalf. In AmI we distinguish between several levels of system intelligence: context aware, personalized, adaptive and anticipatory system intelligence: