Teaching practices and reflections on AIGC in brand advertising design

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Date
2024-06-08
Authors
Wei, Dong
Li, Lingxuan
You, Zongyuan
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Springer Nature
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https://doi.org/10.1007/978-3-031-61963-2_12
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Abstract
Generative Artificial Intelligence (AIGC) technology has been quickly evolving since 2022, with advertising becoming one of its most popular applications. This opens up new potential and difficulties for current and future brand advertising design education. This article investigates AIGC's design thinking transformation in brand advertising design using the course “AIGC: Machine-Assisted Innovative Design for Brand Advertising” offered at Communication University of China (CUC) during the summer semester of 2023. The goal is to help students comprehend AI art and machine learning, to break down the homogenization of AIGC-generated outcomes from an art and design standpoint, and to develop students’ critical thinking skills so that they can reconsider the creative value of the human brain. The course is structured into two parts: the first part focuses on learning and experiencing AIGC technologies such as ChatGPT, Midjourney, Runway, and others, and applying them thoroughly in design practice. The second half of the course focuses on China Chic brand advertisements and uses hand-drawing, computer-aided design, and AICG to create a whole case design. The course findings demonstrate that AIGC tools have a high level of innovation in the creative process, but there are some issues such as uncontrollability and homogeneity that require humans to spend more time and energy adapting. Students agreed that generative AI can be an effective technique to inspire human creativity, and that when employing AIGC tools, designers should look for ways to collaborate with AI rather than viewing it as a total replacement for humans.
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Keywords
AIGC , “Experience, Process and Reflection” , Teaching practice
Citation
Wei, D., Li, L. and You, Z. (2024). 'Teaching practices and reflections on AIGC in brand advertising design', in: Stephanidis, C., Antona, M., Ntoa, S. and Salvendy, G. (eds) HCI International 2024 Posters. HCII 2024. Communications in Computer and Information Science, vol 2118, pp. 113-124. Springer, Cham. https://doi.org/10.1007/978-3-031-61963-2_12
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https://hdl.handle.net/10468/16123
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Applied Social Studies - Conference Items
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© The Authors (2024), under exclusive license to Springer Nature Switzerland AG. This version of the paper has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1007/978-3-031-61963-2_12