Paper Type
ERF
Abstract
As generative AI increasingly diffuses into creative domains, scholarly discussions on generative art—artwork created autonomously or semi-autonomously by digital machines—often focus on limited perspectives. In contrast, public discourses present a multitude of perspectives regarding how generative art is being adopted and diffused into artistic domains, organizations, and societies. In response, this study uses a topic modeling approach to analyze the discourses in the public domain and highlight potential avenues of research for IS scholars. Specifically, we identified eight main topics in our dataset, which we then categorized into three main themes that underscore important directions for future inquiry. Our study provides new insights into the multifaceted emerging discourses around generative AI and art.
Paper Number
2120
Recommended Citation
Saeedi, Milad and Taleghani, Mohammad, "Uncovering the Discourses around the Diffusion of Generative Art: A Topic Modeling Approach" (2025). AMCIS 2025 Proceedings. 11.
https://aisel.aisnet.org/amcis2025/sigadit/sigadit/11
Uncovering the Discourses around the Diffusion of Generative Art: A Topic Modeling Approach
As generative AI increasingly diffuses into creative domains, scholarly discussions on generative art—artwork created autonomously or semi-autonomously by digital machines—often focus on limited perspectives. In contrast, public discourses present a multitude of perspectives regarding how generative art is being adopted and diffused into artistic domains, organizations, and societies. In response, this study uses a topic modeling approach to analyze the discourses in the public domain and highlight potential avenues of research for IS scholars. Specifically, we identified eight main topics in our dataset, which we then categorized into three main themes that underscore important directions for future inquiry. Our study provides new insights into the multifaceted emerging discourses around generative AI and art.
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