Evaluating generative AI tools for visual communication design using the CoCoSo method under interval valued...

At the age of intelligent design, generative AI tools are leading to a revolution in visual communication as the creative process is shifting to being fully automated, ideation is augmented, and production pipelines are fast-tracked. This paper will present a robust multi-criteria decision-making (MCDM) approach to analyze the comparative efficiency of prevalent tools of generative AI based on the combined compromise solution (CoCoSo) approach in an interval-valued (IVSF) spherical fuzzy framework. The IVSF framework is used to faithfully reflect the differences in how much or how little an expert would like to assign a particular degree of membership, non-membership, or abstinence, for the interval-valued membership, non-membership, and abstinence of degrees. These IVSF values are summed up, defuzzified, and then combined in the CoCoSo algorithm to provide an overall rating of the alternatives. One of the key features of this writing is the creation of a practical case study based on seven assessment criteria, including creativity, cost, customization, integration capability, and others, as well as ten generative AI platforms. DeepArt is presented as the most relevant tool by the proposed IVSF-CoCoSo approach, as it achieves a higher rate of creativity improvement, yields the best results in terms of output quality, and offers customization. Through comparison with other MCDM approaches, as well as sensitivity analysis, the proposed model proves to be highly reliable and flexible. The proposed study will provide practical knowledge to designers, researchers, and other industry stakeholders who aim to implement generative AI in visual communication processes successfully.