Collaborative Systems for Design Inspiration

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Journal Title
Journal ISSN
Volume Title
School of Electrical Engineering | Doctoral thesis (article-based) | Defence date: 2020-10-30
Date
2020
Major/Subject
Mcode
Degree programme
Language
en
Pages
168 + app. 104
Series
Aalto University publication series DOCTORAL DISSERTATIONS, 153/2020
Abstract
Inspiration is a crucial activity in design and innovation, in which potential desirable solutions are explored and refined to later provide directions and inspiration in later stages of design. Designers use a plethora of inspirational methods and tools. Among them are mood boards, a visual collage of pictures, text, and objects, that is usually created collaboratively in e.g. fashion design, architecture, and marketing. Mood boards help designers identify, select, and curate visually inspiring content, to express their existing ideas but also to inspire new ideas through their combination. As mood board design becomes increasingly digital, the availability and variety of online material presents ever greater opportunities to assist designers. However, it also poses new challenges. Through interviews with professional designers we identified three of them in particular: 1) turning tacit ideas into expressible search terms, 2) synthesizing and reflecting on visual material, and 3) finding external inspiration. While existing methods for visual inspiration hint at a great potential to support conceptual innovations, the computational support to address these challenges remains lacking. My work contributes knowledge, interaction techniques, and co-creative algorithms to assist users with these challenges. First, it introduces collaborative systems that enrich images with semantic information, to help designers express vague, visual ideas and translate them into usable search terms. Second, to support visual reflection, this thesis introduces multiple levels of semantic abstraction of visual material, to inspire designers to find higher-level concepts in their own work. Third, collaboration is an integral part of physical mood board practice, yet digital mood boards are often crafted at an individual level, which deprives designers of many opportunities to challenge and expand their ideas. An artificial agent was developed that creates mood boards jointly with a designer, based on a cooperative contextual bandit algorithm. This approach conferred it the ability to make its own decisions about whether to explore or exploit the visual contents of the current mood board, and our participants, all professional designers, genuinely valued its contributions. Thanks to a grounding-based interaction approach, it had the ability to justify its contributions and to inquire about sudden changes in the designer's choices. That resulted in a system that was perceived as a contributing agent, rather than merely a tool. Finally, beyond mood board creation with individual designers, the developed collaborative systems also contributed to creative collaborations between human designers. Within these collaborations, artificial agents played a role complementary to that of designers, and were appreciated in particular when ideas were sparse, when designers felt ''stuck',' or had trouble expressing their ideas. My work highlights the immense potential of intelligent collaborative systems for inspiration-seeking and creative processes, and opens new ways to assist designers in the era of digital ideation.
Description
A doctoral dissertation completed for the degree of Doctor of Science (Technology) to be defended, with the permission of the Aalto University School of Electrical Engineering, Remote connection link: https://aalto.zoom.us/j/67874841474, on the 30th of October 2020 at 2 pm.
Supervising professor
Oulasvirta, Antti, Prof., Aalto University, Department of Communications and Networking, Finland
Keywords
design, innovations, inspiration, collaborative systems, human-computer partnership
Other note
Parts
  • [Publication 1]: Janin Koch. Design Implications for Designing with a Collaborative AI. In AAAI 2017 Spring Symposium: Symposium on Designing the User Experience of Machine Learning Systems, Technical Report, p. 143-148, 04 2017
  • [Publication 2]: Janin Koch, Magda Laszlo, Andrés Lucero, and Antti Oulasvirta. Surfing for Inspiration: Digital Inspirational Material in Design Practice. In Proceedings of Design Research (DRS), p. 149-164, 06 2018. Full text I Acris/Aaltodoc: http://urn.fi/URN:ISBN:978-1-912294-18-3.
  • [Publication 3]: Janin Koch and Antti Oulasvirta. Group Cognition and Collaborative AI. Springer Book Chapter, In: Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent, p. 165-188, 06 2018.
    DOI: 10.1007/978-3-319-90403-0_15 View at publisher
  • [Publication 4]: Janin Koch, Andrés Lucero, Lena Hegemann, and Antti Oulasvirta. May AI? Design Ideation with Cooperative Contextual Bandits. Conference on Human Factors in Computing Systems, p. 187-200, 05 2019.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201908154654
    DOI: 10.1145/3290605.3300863 View at publisher
  • [Publication 5]: Janin Koch, Nicolas Taffin, Andrés Lucero, and Wendy Mackay. SemanticCollage: Enriching Digital Mood Board Design with Semantic Labels. DIS ’20: Proceedings of the Designing Interactive Systems Conference, p. 201-214, 07 2020.
    DOI: 10.1145/3357236.3395494 View at publisher
  • [Publication 6]: Janin Koch, Nicolas Taffin, Michel Beaudouin-Lafon, Markku Laine, Andrés Lucero, and Wendy Mackay. ImageSense: An Intelligent Collaborative Ideation Tool to Support Diverse Human-Computer Partnerships. Proceedings of the ACM on Human-Computer Interaction (CSCW), p. 215-243, 05 2020.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-202008064453
    DOI: 10.1145/3392850 View at publisher
Citation