Human-AI Co-Creation Systems in Design and Art
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V5I1P111Keywords:
Co-Creation, AI in Art, Computational Creativity, GANs, Deep Learning, Creative AI SystemsAbstract
The development of artificial intelligence (AI) has radically changed the creative ecosystem, creating novel paradigms of human-computer interaction. Co-creation systems involving humans and AI are blurring the lines between design and art in such a way that machines cease being used as tools but become partners. This paper presents a study on Human-AI co-creative systems, drawing on the fields of design and art, with an analysis of technological drivers, Interaction paradigms, mechanisms, and subsequent implications for artistic expression and design innovations. The research methods include a general overview of the role of AI in generative art, participatory design, algorithmic ending, and intelligent design systems. The different frameworks covered in the paper utilise deep learning, generative adversarial networks (GANs), evolutionary algorithms, and reinforcement learning, presenting an understanding of the processes involved in mutually co-creative human and machine interrelations. The survey of the literature provides a description of the state-of-the-art tool and methods, and it is supplemented by a methodological overview of the common models, such as hybrid systems, adaptive interfaces, and collaborative agents. The paper has a comparative study of products of human-centric, AI-centric, and co-creative strategies using case studies and experimental techniques. Preliminary outcomes suggest that co-creative systems can enhance human creativity to a greater extent, particularly in ideation, prototyping, and stylistic exploration, while also raising philosophical and moral concerns. The final section of this article is the discussion of future research directions, where ethical aspects, authorship issues, and the necessity of transparent AI-driven creativity are underlined
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