Design Generative AI for Practitioners: Exploring Interaction Approaches Aligned with Creative Practice
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866910039341531136 |
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| author | Peng, Xiaohan Mackay, Wendy E. Koch, Janin |
| author_facet | Peng, Xiaohan Mackay, Wendy E. Koch, Janin |
| contents | Design is a non-linear, reflective process in which practitioners engage with visual, semantic, and other expressive materials to explore, iterate, and refine ideas. As Generative AI (GenAI) becomes integrated into professional design practice, traditional interaction approaches focusing on prompts or whole-image manipulation can misalign AI output with designers' intent, forcing visual thinkers into verbal reasoning or post-hoc adjustments. We present three interaction approaches from DesignPrompt, FusAIn, and DesignTrace that distribute control across intent, input, and process, enabling designers to guide AI alignment at different stages of interaction. We further argue that alignment is a dynamic negotiation, with AI adopting proactive or reactive roles according to designers' instrumental and inspirational needs and the creative stage. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_03074 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Design Generative AI for Practitioners: Exploring Interaction Approaches Aligned with Creative Practice Peng, Xiaohan Mackay, Wendy E. Koch, Janin Human-Computer Interaction Artificial Intelligence Design is a non-linear, reflective process in which practitioners engage with visual, semantic, and other expressive materials to explore, iterate, and refine ideas. As Generative AI (GenAI) becomes integrated into professional design practice, traditional interaction approaches focusing on prompts or whole-image manipulation can misalign AI output with designers' intent, forcing visual thinkers into verbal reasoning or post-hoc adjustments. We present three interaction approaches from DesignPrompt, FusAIn, and DesignTrace that distribute control across intent, input, and process, enabling designers to guide AI alignment at different stages of interaction. We further argue that alignment is a dynamic negotiation, with AI adopting proactive or reactive roles according to designers' instrumental and inspirational needs and the creative stage. |
| title | Design Generative AI for Practitioners: Exploring Interaction Approaches Aligned with Creative Practice |
| topic | Human-Computer Interaction Artificial Intelligence |
| url | https://arxiv.org/abs/2603.03074 |