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Can ChatGPT Wear Prada? When Generative A.I. Meets High Fashion

A.I. can rapidly expand the creative possibilities available to designers, but high fashion remains grounded in the distinctly human work of editing, making and understanding desire.

As New York Fashion Week descends, editors, buyers and industry watchers flock to the Big Apple amid the usual assortment of excitement and intrigue: which of the world’s premier designers will impress as they unveil their latest lines and sartorial creations? It is a sign of the times that even this glamorous event is not immune from questions about artificial intelligence: What happens when the synthetic enters an industry steeped in taste and tradition? Can a machine trained on the accumulated imagery of human culture help designers imagine the strange, alluring and occasionally irrational artifacts that constitute high fashion? Or, to borrow from a certain Miranda Priestly, will the outputs of generative systems forever remain an uninspiring “pile of stuff”? The answer may surprise you. 

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Traditional A.I. and fashion 

For the past decade, artificial intelligence functioned as a silent partner in the fashion industry, operating largely behind-the-scenes in inventory management, price optimization and predictive analytics. 

Until recently, it was inconceivable that A.I. would intrude on the creative process in an industry defined by the singular vision of its designers. Today, luxury brands are leveraging machine intelligence to amplify the very craftsmanship that distinguishes them from their peers. The role of generative A.I. in this process, and the extent to which it can meaningfully contribute to creativity in fashion, presents a complicated picture.  

Generative A.I. in the design workflow

To understand where generative A.I. enters the creative process in fashion design, it is helpful to consider the basic journey through which an idea becomes a finished garment:

Archival and trend research: Designers traditionally spend weeks or months assembling references from fashion archives, museums, photography, art and previous collections to establish the visual language of a new collection.

Concept and silhouette exploration: Those references begin taking physical form through sketching, mood boards and experiments with proportion, shape and drape on dress forms.

Material and colorway prototyping: Promising concepts are explored through fabric swatches, custom dyeing, material combinations, sample cutting and variations in color and texture.

Technical design hand-off: Once a design has matured, its creative vision must be translated into technical flats, patterns, measurements and specifications that patternmakers and ateliers can turn into an actual garment.

Within this workflow, the term “using A.I.” can describe dramatically different levels of creative agency. For example, a designer querying a public model for 20 imaginative jacket concepts is doing something quite different from a team that trains a proprietary system on an internal archive and then channels selected outputs into a development pipeline. For the purposes of this analysis, our interest lies in those areas where generative A.I. participates in the creative process itself; instances where the technology can augment, provoke and influence the imagination of the designer. 

In this context, a dividing line emerges between where generative A.I. is most useful and where it’s not. On one side lies the “divergent frontend”........

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