IN THE film "The Devil Wears Prada", the character of Miranda Priestly, whose role is based on a feared Vogue editor, scolds her new assistant for not understanding fashion. Fashion, she tells her, is whatever a select group of designers and critics says it is. What she does not say, however, is that their judgments are themselves often influenced by another group: fashion forecasters, who predict what will be "in". Might these seers of style in turn be undone by artificial intelligence (AI)? Fashion forecasting has always been a peculiar profession.

Analyzing fashion trends is essential in the fashion industry. Current fashion forecasting firms, such as WGSN, utilize the visual information from around the world to analyze and predict fashion trends. However, analyzing fashion trends is time-consuming and extremely labor intensive, requiring individual employees' manual editing and classification. To improve the efficiency of data analysis of such image-based information and lower the cost of analyzing fashion images, this study proposes a data-driven quantitative abstracting approach using an artificial intelligence (A.I.) algorithm. Specifically, an A.I. model was trained on fashion images from a large-scale dataset under different scenarios, for example in online stores and street snapshots. This model was used to detect garments and classify clothing attributes such as textures, garment style, and details for runway photos and videos. It was found that the A.I. model can generate rich attribute descriptions of detected regions and accurately bind the garments in the images. Adoption of A.I. algorithm demonstrated promising results and the potential to classify garment types and details automatically, which can make the process of trend forecasting more cost-effective and faster.

When Detroit-based luxury goods brand Shinola began working on its new Vinton watch, the team designed with a woman in mind, but testing the product through analytics platform MakerSights, which correlates consumer feedback with historical sales data, revealed the style appealed to all genders. As a result, the brand deepened its buy-in on those by about 70 per cent. "You never design by data," says Shinola CEO Tom Lewand, "but the data provides a compass as you're navigating a hunch." In other words, Shinola already had a great vision – and the data enhanced it. MakerSights is among a new class of data-driven analytics platforms that combine factors such as search queries, social media activity, e-commerce sell-throughs and consumer feedback to provide clues into what is most likely to become a trend.

The fashion industry is often gridlocked in a paradox that's rooted in the tension between its creative side and the bottom line. And in a retail environment undergoing extreme upheaval due to the demands of consumer centricity, this tension is being further strained. But new technologies may be able to help -- and some have knowledge greater than our own. Take Watson, IBM's new artificial intelligence solution with the ability to crunch more data faster than anything else. So, WWD wondered, what would Watson say about the latest collections shown during New York Fashion Week?

Paris, France - Highlighting the growth of fast fashion - at least in the form of increasing volumes of cheap and disposable clothing - TRAID's warehouse in London was receiving around 3,000 tonnes of donated clothes every year before coronavirus hit. "We're sorting through more volume and finding less that can go into our shops than a few years ago," said Leigh McAlea, head of communications at TRAID, the United Kingdom-based clothes charity that aims to reduce the environmental and social impact of the fashion industry by encouraging people to shop second-hand. "We're seeing a lot of fast fashion items, a lot of clothes that have been barely worn or still have tags on. Items that go into our 12 charity shops have to be good enough quality to resell, whether they're Primark or Prada. We want to encourage people to buy better quality and then donate items when they have finished with them," McAlea told Al Jazeera.