Comparing the Use of Scientific Software and Generative AI Art Tools: Exploratory research and future agenda
The introduction of Generative Artificial Intelligence (GenAI) image and text generators has brought a renewed and significant amount of attention to textual user interfaces. Platforms such as ChatGPT and Midjourney generate, respectively, text and images from verbal instructions typed by users in...
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| Format: | Article |
| Language: | Catalan |
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Bau, Centro Universitario de Diseño
2025-06-01
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| Series: | Inmaterial |
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| Online Access: | https://www.inmaterialdesign.com/INM/article/view/240 |
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| Summary: | The introduction of Generative Artificial Intelligence (GenAI) image and text generators has brought a renewed and significant amount of attention to textual user interfaces. Platforms such as ChatGPT and Midjourney generate, respectively, text and images from verbal instructions typed by users in natural language and processed by Machine Learning models. The use of natural language in GenAI differs from scientific software use interfaces, usually operated through programming and scripting languages. Still, both computational science and generative art, in their own ways, replace traditional ‘wet’ processes with abstract, dematerialised ones.
Through an examination of existing literature and preliminary research on those practices, this paper discusses the potential in cross-pollinating principles and concepts from scientific software and generative art and design. It aims to propose new approaches to developing and using those tools, having in mind not only user interface paradigms in those systems, but similarities and differences between scientific, and art and design domains. It will explore the tensions between open and closed models, objectivity and subjectivity, and reproducibility and uniqueness, which are respectively associated with scientific and creative practices. Preliminary results suggest the need for policies and practices in Generative AI development that involve art and design professionals and ways to acknowledge and reward their domain expertise.
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| ISSN: | 2462-5884 2462-5892 |