The Effects of Generative AI on Design Fixation and Divergent Thinking

Eduardo Velloso; Qiushi Zhou; Ryan M. Kelly; Samangi Wadinambiarachchi; Saumya Pareek

The Effects of Generative AI on Design Fixation and Divergent Thinking

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arxiv 2403.11164 v1 pith:JV3EVD5A submitted 2024-03-17 cs.HC

Samangi Wadinambiarachchi , Ryan M. Kelly , Saumya Pareek , Qiushi Zhou , Eduardo Velloso This is my paper · ORCID

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Generative AI systems have been heralded as tools for augmenting human creativity and inspiring divergent thinking, though with little empirical evidence for these claims. This paper explores the effects of exposure to AI-generated images on measures of design fixation and divergent thinking in a visual ideation task. Through a between-participants experiment (N=60), we found that support from an AI image generator during ideation leads to higher fixation on an initial example. Participants who used AI produced fewer ideas, with less variety and lower originality compared to a baseline. Our qualitative analysis suggests that the effectiveness of co-ideation with AI rests on participants' chosen approach to prompt creation and on the strategies used by participants to generate ideas in response to the AI's suggestions. We discuss opportunities for designing generative AI systems for ideation support and incorporating these AI tools into ideation workflows.

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