Abstract
Crowdsourcing processes can be used for design concept creation and evaluation. They also provide opportunities to study and model quantitatively how humans deal with design problems. This paper explores the use of crowdsourcing to evaluate a perceptual design attribute and to create new design concepts using this attribute. As an example, we study how perceived automobile car safety can be modeled with respect to exterior car shape design using an efficient statistical learning algorithm. Experiments with subjects using Amazon's Mechanical Turk uncover several practical issues that must be addressed when applying machine learning methods to create safe-looking car designs using crowdsourced input.
Original language | English (US) |
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Title of host publication | Proceedings of the 19th International Conference on Engineering Design |
Subtitle of host publication | Design for Harmonies, ICED 2013 |
Pages | 139-148 |
Number of pages | 10 |
Volume | 6 DS75-06 |
State | Published - Dec 1 2013 |
Externally published | Yes |
Event | 19th International Conference on Engineering Design, ICED 2013 - Seoul, Korea, Republic of Duration: Aug 19 2013 → Aug 22 2013 |
Other
Other | 19th International Conference on Engineering Design, ICED 2013 |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 8/19/13 → 8/22/13 |
Keywords
- Design crowdsourcing
- Human-computer interaction
- Preference learning
ASJC Scopus subject areas
- Modeling and Simulation
- Engineering (miscellaneous)
- Industrial and Manufacturing Engineering