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With the growing use of artificial intelligence (AI) in creative field, it is essential to understand the role of AI in generating creative outputs. Design education also aims to prepare students to conceive creative outputs for society with responsibility towards the future. The literature review reveals that there are multiple text-to-image-based generative artificial intelligence popularly known as AI image generators. A few notable ones are ImagineArt, Fotor, Stable Diffusion, Midjourney and Starryai, which are used for generating an image-based output by providing them with a word prompt to design a product from natural language description, instantly. It is established that designers start the process of design from design brief articulation akin to word prompt provided to AI, design brief also consists of word prompts, leading to creative process to generate design solutions. However, there is limited research on comparing the creativity of the outcome received from designers and AI image generators. Therefore, this research focuses on comparing the outcomes from 3rd-year apparel design students and AI image generators on creativity quotient. The research is done by using elicitation techniques in the form of word prompts. The research was conducted in a workshop setting with the design students. The process was repeated with an AI image generator. The assessment of the solutions was done by design experts, based on an adaptation of creativity-relevant skills from Amabile’s Componential Model of Creativity. The received data was modelled with statistical tools. The results provide an insight into the unique human capabilities to arrive at solutions by perceiving multiple scenarios along with emotive values. It throws light on the strengths and weaknesses of solutions generated by designers and AI. Insights gained can be used to effectively integrate AI into design education. This will help in leveraging the humane approach and efficacy of the AI tools to arrive at contextually appropriate outcomes, characterizing responsible design and creativity.

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Responsible Design Solutions: A Comparative Study of Creativity Between AI Image Generators and Designers

  • 会议论文

  • 发表日期：

    2025年

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  • V. K. Mohankumar,
  • Shipra Roy

摘要

With the growing use of artificial intelligence (AI) in creative field, it is essential to understand the role of AI in generating creative outputs. Design education also aims to prepare students to conceive creative outputs for society with responsibility towards the future. The literature review reveals that there are multiple text-to-image-based generative artificial intelligence popularly known as AI image generators. A few notable ones are ImagineArt, Fotor, Stable Diffusion, Midjourney and Starryai, which are used for generating an image-based output by providing them with a word prompt to design a product from natural language description, instantly. It is established that designers start the process of design from design brief articulation akin to word prompt provided to AI, design brief also consists of word prompts, leading to creative process to generate design solutions. However, there is limited research on comparing the creativity of the outcome received from designers and AI image generators. Therefore, this research focuses on comparing the outcomes from 3rd-year apparel design students and AI image generators on creativity quotient. The research is done by using elicitation techniques in the form of word prompts. The research was conducted in a workshop setting with the design students. The process was repeated with an AI image generator. The assessment of the solutions was done by design experts, based on an adaptation of creativity-relevant skills from Amabile’s Componential Model of Creativity. The received data was modelled with statistical tools. The results provide an insight into the unique human capabilities to arrive at solutions by perceiving multiple scenarios along with emotive values. It throws light on the strengths and weaknesses of solutions generated by designers and AI. Insights gained can be used to effectively integrate AI into design education. This will help in leveraging the humane approach and efficacy of the AI tools to arrive at contextually appropriate outcomes, characterizing responsible design and creativity.