Exploiting generative AI as a collaborator to enhance creators’ dissertations
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Abstract
The concept dissertation is a critical and analytical text the author communicates to the public. However, creators may be too subjective and associative in their descriptions, thus losing the ability to effectively communicate with the public. The study aims to enhance public understanding by incorporating moderately objective descriptions to foster a wider acceptance of art and design. Utilizing the text-to-image function of Artificial Intelligence-Generated Content (AIGC), this study explores a method for creators, as artificial intelligence (AI) collaborative partners, to improve the concept dissertation promptly and with faithful simulation feedback based on data. The researcher conducted a practical experiment involving 22 experienced creators in a master’s program, well-versed in the art and design field, collecting data on text, generative images, and observational notes, which were then cross analyzed using content analysis and the general inductive approach. The results indicated that the participants practiced writing objectively by generating AI images and providing immediate feedback, fostering reflection and awareness, and encouraging participants to remain objective and explore ways to improve the text. This study reveals that AI is a tool for content generation and a collaborative partner that respects and responds to the participants’ creative intent in the learning environment. In the AI collaborative method, the creators controlled the subjective–objective balance with the public by emphasizing the complexities of thinking and inspired expressions. This study enhances the collaborative potential between participants and AI, facilitating rapid exploration and transformation and improving communication between artists and the public.
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