This week, our speaker is our own Dr. Joel Chan. Dr. Chan is an assistant professor in the College of Information studies at the University of Maryland, College Park. His research and teaching focus on the intersection of people, information, and creativity. He will give a talk about “Back to the Future: How people construct new creative ideas from old knowledge, and how technology can help” in this week’s BBL.
Time: 05/10 (Thursday) from 12:30pm – 1:30pm
Place: HCIL, Room 2105, Hornbake Building, South Wing
Lunch: Please bring your own lunch!
Where do good ideas come from? One answer is that they come from prior knowledge: for example, Thomas Edison leveraged his knowledge of phonographs to “do for the eye what the phonograph does for the ear”. Yet, much research on human creativity demonstrates that prior knowledge often constrains creativity. How do people construct new creative ideas from old knowledge? And (how) can technology help? In the first part of my talk, I will summarize empirical work I have done that advances theories of the conditions under which people successfully construct new creative ideas from prior knowledge. This empirical work shows that prior knowledge can inspire creativity when it is analogically related to the current problem. This insight informs the ongoing work I will discuss in the second part of my talk: developing information technologies that combine human and machine intelligence to more effectively support analogical reasoning over prior knowledge.
Joel Chan is an Assistant Professor in the University of Maryland’s College of Information Studies (iSchool), and Human-Computer Interaction Lab (HCIL). His research and teaching focus on the intersection of people, information, and creativity. He wants to know how they (can best) combine to enable us to design the future(s) we want to live in. His work has been recognized with a Best Paper Award at the ASME Design Theory and Methodology conference, the Design Studies Award 2015, and supported by an NSF Doctoral Dissertation Improvement Grant. Previously, he was a Postdoctoral Research Fellow and Project Scientist in the Human-Computer Interaction Institute at Carnegie Mellon University. He received his PhD in Cognitive Psychology at the University of Pittsburgh.