May Ai? Design ideation with cooperative contextual bandits

Janin Koch, Andrés Lucero, Lena Hegemann, Antti Oulasvirta

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

41 Sitaatiot (Scopus)
196 Lataukset (Pure)


Design ideation is a prime creative activity in design. However, it is challenging to support computationally due to its quickly evolving and exploratory nature. The paper presents cooperative contextual bandits (CCB) as a machine-learning method for interactive ideation support. A CCB can learn to propose domain-relevant contributions and adapt their exploration/exploitation strategy. We developed a CCB for an interactive design ideation tool that 1) suggests inspirational and situationally relevant materials (“may AI?”); 2) explores and exploits inspirational materials with the designer; and 3) explains its suggestions to aid reflection. The application case of digital mood board design is presented, wherein visual inspirational materials are collected and curated in collages. In a controlled study, 14 of 16 professional designers preferred the CCB-augmented tool. The CCB approach holds promise for ideation activities wherein adaptive and steerable support is welcome but designers must retain full outcome control.

OtsikkoCHI 2019 - Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
ISBN (elektroninen)9781450359702
DOI - pysyväislinkit
TilaJulkaistu - 2 toukok. 2019
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaACM SIGCHI Annual Conference on Human Factors in Computing Systems - Glasgow, Iso-Britannia
Kesto: 4 toukok. 20199 toukok. 2019


ConferenceACM SIGCHI Annual Conference on Human Factors in Computing Systems
LyhennettäACM CHI


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