Conversational Informatics Research Articles

Conversational Informatics: Toward Cultivating Wisdom from Conversational Interaction

Abstract In this paper, I present a data-intensive approach to conversational informatics. It not only brings about quantitative understanding, permitting us to turn a great accumulation of keen observations into a pile of computational models, but also helps to build conversational agents by virtue of recent progress in machine learning and data mining. The topics include a smart conversation space for allowing people to engage in conversation in a cyber-physical space, conversational interaction capture for conversation modeling and content production, learning by imitation for producing conversational interactions, cognitive design for understanding mental processes of conversational actors, and synthetic evidential study for collaborative study on understanding social processes.

Augmenting Conversational Environment

People are proficient in collaboratively forming and maintaining gatherings thereby shaping and cultivating collective thoughts through fluent conversational interactions. A big challenge is to develop a technology for augmenting the conversational environment so that people can conduct even better conversational interactions for collective intelligence and creation. Conversational informatics is a field of research that focuses on investigating conversational interactions and designing intelligent artifacts that can augment conversational interactions. The field draws on a foundation provided by artificial intelligence, natural language processing, speech and image processing, cognitive science, and conversation analysis. In this article, the author overviews a methodology for developing augmented conversational environment and major achievements. The author also discusses issues for making agents empathic so that they can induce sustained and constructive engagement with people.

Toward Robots as Embodied Knowledge Media

We describe attempts to have robots behave as embodied knowledge media that will permit knowledge to be communicated through embodied interactions in the real world. The key issue here is to give robots the ability to associate interactions with information content while interacting with a communication partner. Toward this end, we present two contributions in this paper. The first concerns the formation and maintenance of joint intention, which is needed to sustain the communication of knowledge between humans and robots. We describe an architecture consisting of multiple layers that enables interaction with people at different speeds. We propose the use of an affordance-based method for fast interactions. For medium-speed interactions, we propose basing control on an entrainment mechanism. For slow interactions, we propose employing defeasible interaction patterns based on probabilistic reasoning. The second contribution is concerned with the design and implementation of a robot that can listen to a human instructor to elicit knowledge, and present the content of this knowledge to a person who needs it in an appropriate situation. In addition, we discuss future research agenda toward achieving robots serving as embodied knowledge media, and fit the robots-as-embodied-knowledge-media view in a larger perspective of Conversational Informatics.