Evidence-based chatbot interaction aimed at reducing sedentary behavior

Interaction between chatbots and humans is often based on frequently occurring interaction patterns, e.g. question – answer. Those patterns usually describe a very brief phase in the interaction. In this micro project, we want to investigate whether we can design a chatbot for behavior change by including higher level patterns, which are adapted from the taxonomy of behavior change techniques (BCT’s) [1]. These patterns should describe the components of the interaction during a longer period of time. In addition, we will investigate how to design a user interface in such a way that it sustains the interest of the users.

We will focus on reducing sedentary behavior [2], and especially sitting behavior, which can have negative health consequences. The interaction patterns and user interface will be implemented in a prototype. An user study will be done to evaluation the different components on effectiveness and engagement.

Output

Scientific paper

Prototype for consortium

Presentations

Project Partners:

• Stichting VU, Koen Hindriks, Michel Klein
• University College London í(UCL), Yvonne Rogers

Primary Contact: Michel Klein, Vrije Universiteit Amsterdam

Main results of micro project:

Interaction between chatbots and humans is often based on frequently occurring interaction patterns, e.g. question – answer. Those patterns usually describe a very brief phase in the interaction. In this micro project, we want to investigate whether we can design a chatbot for behavior change by including higher level patterns, which are adapted from the taxonomy of behavior change techniques (BCT’s). These patterns should describe the components of the interaction during a longer period of time. In addition, we will investigate how to design a user interface in such a way that it sustains the interest of the users.

A prototype has been developed is currently being evaluated.

Contribution to the objectives of HumaneAI-net WPs

We investigate how AI systems can collaborate with humans, specifically focussing on changing a specific behavior. We increase our understanding of how specific interaction forms between an AI system and a human are effective in achieving behavior change. We also investigate to what extent knowledge about health behavior can contribute to desiging realistic and effective communication.

Tangible outputs

• Publication: Bachelor thesis – Michel Klein

Attachments

Klein M_March17.mkv