with Chris Schunn (Pitt psych), Steven Dow (UCSD Cognitive Science), Niki Kittur (CMU HCII), Lisa Yu (Bosch Pittsburgh), Steven Dang (CMU HCII), Pao Siangliulue (Harvard SEAS), Krzysztof Gajos (Harvard SEAS)
People build new ideas on what they know and have seen. Sometimes this a good thing; sometimes it kills creativity. In online innovation communities (e.g., Quirky, Dribble, OpenIDEO) one can be exposed to many, many potential sources of inspiration for your creativity: are there scientific principles that can guide your interactions so that you are inspired and not hindered in your creativity? How can we better take advantage of the collective creativity in these communities and in the artifacts and knowledge the produce?
We are exploring how the conceptual distance and diversity of inspiration sources influences innovation outcomes in networks of collaboration inspiration. More recently, we have been exploring ways to embody and test these principles in social computing systems that support collaborative ideation, including a social electronic brainstorming system, a system for mining analogies from online repositories with crowds and computations, and a personalized inspiration system for idea generation.
Recent findings:
- Access to simple, off-the-shelf machine sensemaking (e.g., Latent Semantic Analysis and k-means clustering) over a solution space can increase quantity and diversity of ideas.
- We are able to improve crowd workers' creativity by enabling lightweight real-time guidance from a facilitator.
- Providing examples to people at regular intervals harms productivity, while allowing people to access examples on-demand improves creativity of ideas.
- Contrary to popular theory, ideas that build more on far sources of inspiration are less creative than ideas that build mainly on near sources.
- Building directly on diverse sources doesn't yield immediately creative ideas; but, iterating on these ideas results in highly creative ideas.
Pubs:
Chan, Dang, S. C., & Dow, S. P. (2016). Comparing different sensemaking approaches for large-scale ideation. Proceedings of 2016 ACM Conference on Human Factors in Computing Systems (CHI 2016). [PDF]
Chan, Dang, S. C., & Dow, S. P. (2016). Improving crowd innovation with expert facilitation. Proceedings of the ACM Conference on Computer-Supported Cooperative Work, 2016. [PDF]
Chan, J., & Schunn, C. (2015). The importance of iteration in creative conceptual combination. Cognition, 145, 104-115. [PDF]
Siangliulue, K, Chan, Gajos, K., & Dow, S. P. (2015). Providing timely examples improves the quantity and quality of generated ideas. Proceedings of the ACM Conference on Creativity and Cognition, 2015. [PDF]
Chan, J., Dang, S., Kremer, P., Guo, L., & Dow, S. (2014). IdeaGens: A social ideation system for guided crowd brainstorming. Demo presented at the 2nd AAAI Conference on Human Computation and Crowdsourcing, Pittsburgh, PA. [PDF]
Chan, J., Dow, S. P., & Schunn, C. (in press). Do the best design ideas (really) come from conceptually distant sources of inspiration? Design Studies. [PDF]
Chan, J., Schunn, C., & Dow, S. (2014). Overreliance on conceptually far sources decreases the creativity of ideas. Paper presented at the 36th Annual Meeting of the Cognitive Science Society, Quebec City, Canada. [PDF]
Chan, J., Dow, S., & Schunn, C. (2014). Conceptual distance matters when building on others' ideas in crowd-collaborative innovation platforms. Poster presented at the 17th ACM Conference on Computer Supported Cooperative Work and Social Computing, Baltimore, MD. http://dx.doi.org/10.1145/2556420.2556500. [PDF][Poster]
with Chris Schunn (Pitt psych), Susannah Paletz (CASL)
How do multidisciplinary teams work together to produce innovations? We have collected thousands of hours of video of naturalistic problem-solving by student design teams across 8 semesters, solving real problems for industry clients, and among multidisciplinary teams of scientists who worked on the successful NASA Mars Exploration Rover mission (in ~2004-2005) that found evidence for water in Mars.
We are using detailed process analyses to understand the temporal interplay between important social and cognitive processes (like analogy, uncertainty, and conflict) and how they relate to team innovation.
Recent findings:
- Science teams use within-domain/discipline analogies to help reduce uncertainty during problem solving.
- Brief disagreements reduce uncertainty in successful engineering teams, but increase uncertainty in unsuccessful teams.
Pubs:
Paletz, S., Chan, J., & Schunn, C. (accepted). Uncovering uncertainty through disagreement. Applied Cognitive Psychology. [PDF]
Paletz, S. B. F., Chan, J., & Schunn, C. (2014, July). Making conflicts work: Team success moderates the relationship between micro-conflicts and uncertainty. Paper to be presented at the Interdisciplinary Network for Group Research (INGRoup) Conference, Raleigh, NC.
Luo, W,* Litman, D., & Chan, J. (2013). Reducing annotation effort on unbalanced corpus based on cost matrix. Paper presented at the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL HLT 2013) Student Research Workshop, Atlanta, GA. [PDF]
Chan, J., Paletz, S., & Schunn, C. (2012). Analogy as a strategy for supporting complex problem solving under uncertainty. Memory and Cognition, 40, 1352-1365. [PDF]
with Chris Schunn (Pitt psych)
For my master's thesis I did a deep-dive analysis of a multidisciplinary expert design team's brainstorming conversations for a new product. I tried to characterize the impact of analogy use on idea generation, looking in particular for evidence of using far analogies to "jump" into very different parts of the idea space.
Recent findings:
- Far analogies tended to be sparked when the designers were exploring variations on a theme for particular solution approaches, and helped them come up with more ideas along the same lines, rather than using them to jump into very different idea spaces.
Pubs:
Chan, J., & Schunn, C. (2015). The impact of analogies on creative concept generation: Lessons from an in vivo study in engineering design. Cognitive Science, 39, 126-155. [PDF]
with Chris Schunn (Pitt psych), Kate Fu (CMU MechE, now GA Tech Design/MechE), Jon Cagan (CMU MechE), Ken Kotovsky (CMU Psych), Kris Wood (MIT-SUTD EPD)
In this project we explored computational approaches for finding and delivering analogous example designs to designers to inspire creativity. We used a combination of text mining algorithms and Bayesian structure learning to build structured representations of large repositories of design examples to support searching for potentially inspiring examples. We also ran behavioral experiments to explore and test cognitive science principles for finding and presenting analogous examples for maximal ideation benefit.
Recent findings:
- Our computationally constructed structures were able to capture common structure from experts' representations of collections of design examples, and also support surprising but sensible novel insights into the relationships between design examples
- Some (conceptually close) between-domain analogous examples were helpful for ideation, but analogies that were too conceptually distant harmed ideation
- Analogical distance and commonness of examples had statistically distinct effects on ideation process and outcomes
Pubs:
Fu, K.*, Chan, J., Schunn, C., Cagan, J., & Kotovsky, K (2013). Expert representation of design repository space: A comparison to and validation of algorithmic output. Design Studies, 34, 729-762. [PDF]
Fu, K.*, Chan, J., Cagan, J., Kotovsky, K., Schunn, C., & Wood, K . (2013). The meaning of "near" and "far": The impact of structuring design databases and the effect of distance of analogy on design output. Journal of Mechanical Design, 135, 021007. [PDF]
Chan, J., Fu, K.*, Schunn, C., Cagan, J., Wood, K., & Kotovsky, K. (2011). On the benefits and pitfalls of analogies for innovative design: Ideation performance based on analogical distance, commonness, and modality of examples. Journal of Mechanical Design, 133, 081004. [PDF]