Speaker: Prof. Ekaterina Jussupow

Abstract: Generative text-to-image artificial intelligence (GenAI) tools, such as Midjourney and Dall-E, are enabling the rapid production of synthetic visual artifacts and thereby reshaping creative processes. However, as regulatory and organizational mandates for disclosing GenAI use gain traction, understanding their downstream implications for creators and consumers becomes critical. While prior research has focused on the direct effects of GenAI disclosure on perceived creativity, this paper explores an overlooked dynamic: the indirect effects of anticipated disclosure on creators’ use of GenAI. Using a nested mixed-methods approach, we conducted two experiments to investigate how creators adapt their effort and reliance on GenAI when anticipating disclosure. The results reveal that creators reduce their effort and delegate more creative agency to GenAI, leading to the production of images perceived as more novel but less visually appealing and of lower clarity. These behavioral shifts are driven by changing second-order effort beliefs--creators’ expectations about how others would recognize the human effort that went into the creative process. Our findings underscore the socio-technical dynamics of GenAI adoption and highlight how disclosure policies influence creative practices and redefine humans’ role therein. We discuss the practical implications of our results for platforms considering the implementation of disclosure policies, emphasizing the importance of balancing transparency about GenAI use with highlighting invested human effort.

Short Bio: Ekaterina Jussupow is an Assistant Professor (W2, tenure track) of Information Systems at the Technical University of Darmstadt. With a foundation in psychology, her research explores how individuals collaborate with AI systems, emphasizing the cognitive and metacognitive processes that shape these interactions. Her work has been recognized with a Best Paper Runner-Up Award from Information Systems Research (ISR), and her dissertation earned the prestigious TARGION Award. Her research has been published in leading outlets, including Information Systems Research and MIS Quarterly.