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Research Projects
Collaboration
| Deception & Intent
| Ongoing Projects
Collaboration
The Center for the Management of Information was founded on the idea that people do their most important work within and for groups. Yet, while there were many technologies for helping out individuals there were very few supporting tools for teams. CMI's research projects into collaboration are aimed at making organizations more effective and efficient.
Research innovations from the CMI have been applied in hundreds of organizations, demonstrating the benefits of improved group performance. Seeing a need for focused group support systems, key University of Arizona researchers developed a suite of team-based decision software tools known as GroupSystems. The successful use of GroupSystems in the research arena led to its release as a commercial product in 1989. These tools provide users with the power and flexibility to help groups reach decisions and perform complex tasks such as brainstorming, list building, information gathering, voting, organizing, prioritizing, and consensus building.
CMI continues to build on this legacy of group support systems while expanding into new areas such as visualization, knowledge management and situation awareness.
Deception & Intent
Deception and its detection have been a source of fascination for centuries, with literally thousands of publications on the topic testifying to its importance in the conduct of human affairs. Researchers and practitioners have pursued a host of detection techniques, from divining trustworthiness from the shape of one's head and ears, to the use of physiologically-based instruments such as the polygraph and vocal stress analyzer, to reliance on behavioral cues as potentially telltale cues to deception. However, no single linguistic, visual, vocal or other nonverbal behavior has proven to be accurate indicators 100% of the time.
All these efforts notwithstanding, deception detection accuracy has typically hovered around 50-50, or chance, even among trained professionals. The most promising avenues for distinguishing deceit from truth lie in tools and techniques that utilize configurations of cues. Moreover, because deception indicators are subtle, dynamic, and transitory, they often elude humans' conscious awareness. If computer-assisted detection tools can be developed to augment human detection capabilities by discerning micro-momentary features of language and nonverbal behavior and by tracking these highly elusive and fleeting cues over a course of time, accuracy in discerning both truthful and deceptive information and communications should be vastly improved. Coupled with improved human interviewing and interrogation techniques that are aided by multimedia training and real-time feedback, these tools can greatly enhance deception detection.
Ongoing Projects
CMI possesses expertise on and has performed research into a myriad of areas, including human communication, health informatics, strategic planning, E-commerce, knowledge management, and artificial intelligence (AI).
