Traditional side-by-side collaboration is on the basis that a person wants to relate to another person intimately on a comfortable level, but communications in this collaboration are not limited to speaking, writing, and interpreting words. The complex process involves factors such as content, language, grammar, experience, and non-verbal cues and adds richness to communications, increasing chances of accurate interpretation. Although humans are not confined to communicating face-to-face, they miss contextual information captured in computer-supported collaborative work based on the semiotic theory of Charles Sanders Peirce. Research in both linguistics and anthropology suggests that gesture, voice, expression, and context add richness to communications that increase chances of accurate interpretation. In this project, we continue to enrich communication in computer-supported collaboration by using artificial intelligence to increase the bandwidth of implicit interaction between human and machine through the augmentation of nontext-based activities and contextual information.
We plan to build hardware and software prototypes to study how a computer-supported collaborative system facilitates rich communications. What are the psychological, social, and technical factors and principles can be used to improve the usability of computer mediated communication. Students involved in this project will integrate multidisciplinary knowledge and perspectives, across diverse subject matters. Results from the project will be disseminated via demonstration and publications in related conferences.
Background about the project‘s motives can be found in Liu, Li, Shuo Niu, and Mauro Carassai. “The Impacts of Using Different Methods to Sense Emotion in Computer-Mediated Communication.” In 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 1214–19. Banff, AB: IEEE, 2017. https://doi.org/10.1109/SMC.2017.8122778.