Taste and temporality

This article critically examines the emerging role of artificial intelligence (AI) in the field of fashion trend forecasting, focusing on how machine-learning technologies reshape the aesthetic and commercial dimensions of predicting style. Drawing from fashion studies, philosophy and management studies, this article interrogates the shift from qualitative, expert-led trend forecasting to data-driven, predictive systems that claim to map and anticipate consumer taste at scale. It explores how these systems function not only as tools of prediction but also as producers of cultural meaning, taste hierarchies and aesthetic norms. The article offers a new perspective on AI forecasting in the academy, which has thus far focused on its technical aspects. By analysing AI fashion trend platforms, I explore a critical framework for understanding the implications of AI-driven trend forecasting in both commercial and cultural contexts

Consumer behaviour · Taste · Technology forecasting · Evolutionary Psychology and Human Behavior · Fashion and Cultural Textiles · Generative Adversarial Networks and Image Synthesis

• Perpetuum mobile

  Zygmunt Bauman•Critical Studies in Fashion &…•2010

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