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.
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May AI? Design Ideation with Cooperative Contextual Bandits.
CHI 2019.
@inproceedings{koch2019may,
author = {Koch, Janin and Lucero, Andrés and Lena, Hegemann and Antti, Oulasvirta},
booktitle = {CHI 2019},
title = {{May AI? Design Ideation with Cooperative Contextual Bandits.}},
year = {2019}
}
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Janin Koch
Email:
janin.koch (at) aalto.fi