Modeling Communication for Better Understanding

By David Chong

Technology may have ushered in the age of Big Data, in which huge quantities of data drive the decision-making processes in commerce, academia, and science. But the discipline of design helps the public to understand and interpret this flood of information. Think of how infographics and interactive maps on the New York Times and other news sites transformed vast amounts of public data from the last presidential election into digestible and often-elegant visual models that illustrated how people voted based on their age, location, and other demographics.

While these kinds of visualizations may now be ubiquitous, much of the groundwork for their development was laid down years ago by researchers working in the fields of information design and communication design, including Associate Professor Stan Ruecker of IIT Institute of Design (ID). The focus of his research is to help people more readily interpret and digest complex information.

With multiple degrees in English, computer science, and design, Ruecker came to ID in 2011 from his native Canada to bring a more humanities-centric, semiotics-based approach to communication design. His research encompasses a variety of communication-design projects, from developing new visual models for humanities scholars to helping private companies improve their customer-service systems. Much of his current work involves using design and technology to improve human communication, which offers value to organizations of all types and sizes.

One of Ruecker’s groundbreaking research projects involves developing 3-D visual models of conversations. He calls conversations “untapped resources” because communication within organizations often involves short meetings where a large amount of important information is conveyed among multiple participants.

While text and transcripts may record what is said in a linear fashion, Ruecker says they cannot efficiently show the event as a conversation with different individuals engaged.

“Many times these texts fail to capture point of view,” he says. “What did each person say? What was important to each person? You’ve got to have multiple speakers juxtaposed or shown in relationship.”

His goal is to create a physical or virtual model of these high-value conversations that could be used to refresh a participant's memory, or be easily communicated to someone who is not involved in the conversation.

Ruecker is starting a research consortium at IIT to develop these conversation models, inviting partners from various industries. Several key areas of the economy were identified as potentially benefiting from these conversation models, including health care, education, and government. One potential situation in health care, for example, could arise when patients are discharged from the hospital.

“They’re going to be given a lot of information and printouts at a time when they are least likely to be in a condition to pay attention,” he says, noting that conversation models may be a way to help patients better review complicated information important for their recovery. As a result, hospitals may have lower re-admission rates.

Many private companies have already expressed strong interest in developing conversation-modeling systems because they recognize the benefits of capturing high-value conversations. While this concept is still relatively new, Ruecker believes the practice will be commonplace in 5 to 10 years.

The current challenge, he says, is to develop the technology and structures to efficiently create these visual models.

“How do you capture what’s said, as well as the important nonverbal factors? How much can be automated? How much must be done manually? We’ve got to get all those pieces in place,” Ruecker says.

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