Internal Presentation | Making Sense or Not? Identifying the Representation Gap in Human-GenAI Collaboration for Visual Content Creation

Title:  Making Sense or Not? Identifying the Representation Gap in Human-GenAI Collaboration for Visual Content Creation

Abstract: The increasing reliance on GenAI to produce visual advertising materials raises questions about what kinds of content it can represent effectively. We argue that human-GenAI content generation is shaped by a representational gap arising from a cognitive asymmetry between humans’ embodied knowledge and GenAI’s codified knowledge. We conceptualize imageability as a key manifestation of this gap. Drawing on data from a major Chinese AI art platform, we show that prompt imageability produces two competing effects. Highly imageable prompts reduce semantic fit while enhancing affective visual representation through warmer color temperature. Both factors are positively associated with consumers’ emotional responses. These findings contribute to information systems and digital marketing research by identifying the representation gap as a key mechanism linking prompt characteristics, GenAI-generated visual content, and consumer emotional response.

Bio of the Presenter: Dr Miaomiao Liu is an assistant professor of Marketing at International Business School Suzhou, Xi’an Jiaotong-Liverpool University. She holds a PhD in Business Administration (Marketing) from Fudan University. Her research focuses on smart mobility, sharing economy, service refusal, and UGC. Her work has been published in peer-reviewed journals such as Decision Support Systems, Journal of Business Research, Transportation Research Part D, Technology in Society, IEEE Transactions on Professional Communication, among others.