英语报纸解读：Data may disrupt a peculiar business大纲

原本想做精致些，整理出一周阅读素材的处理方法，每日一篇，留日后反思。现在就跟着小编一起来了解一下《时尚玄学或遭数据瓦解》吧。

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)?

电影《穿普拉达的女王》中的米兰达取材于一位令人闻风丧胆的Vogue主编，影片中她训斥新来的助理不懂什么是时尚，并告诉助理，一群顶尖设计师和评论家凑到一起，说时尚是什么，时尚就是什么。但她未提及，这些人的判断还常常受到另一群人的影响:预言未来流行趋势的时尚预测师。那会不会有一天也轮到这些潮流先知们被人工智能(AI)取代呢?

Fashion forecasting has always been a peculiar profession. The business came into its own in Paris in the 1960s when agencies began releasing “trend books”, collections of fabrics and design ideas. Retailers use these books for inspiration as they put together designs.

时尚预测向来是个玄乎的行当。上世纪六十年代在巴黎，这一行自立门户，开始发行“流行趋势解读”，内容整合了各种流行面料和设计亮点，零售商在拼凑设计时读这些书以寻求灵感。

The biggest of these forecasting firms is WGSN, with a market share of 50%. It employs 150 forecasters who scour the world’s catwalks, bars and clubs to spot the next big thing. Their findings are then combined with other data, from economic indicators to political sentiment. Petah Marian, a senior editor at WGSN, is confident that the methodology works. She says her colleagues often exclaim “I forecast that!” when visiting clothing shops.

最大的时尚预测公司是WGSN，占有50%的市场份额。其麾下有150名时尚预测师，在全世界的秀场，酒吧，夜店里沙里淘金，寻找下一个时尚热点。继而他们的发现将与其他数据整合起来，从经济指标到政治情感，无一例外。WGSN高级编辑佩塔·玛丽安对这套方法信心满满。她说，她的同事们逛服装店的时候经常会兴奋地叫“我预测到了这个!”

Ms Marian’s confidence may seem surprising, given the lack of clear correlations between fashion and macroeconomic data. Not much evidence supports the theory of George Taylor, an economist, that hemlines rise with stocks, and Leonard Lauder’s suggestion that lipstick sales increase during a downturn. Even the cofounder of WGSN, Marc Worth, who sold the firm to set up a rival service, once stated: “Nobody can really predict or forecast trends.” If forecasters can claim accuracy rates of up to 80%, it is because their predictions are often self-fulfilling. Most major retailers buy trend books. For designers, they are a form of insurance: as long as they are widely used, the risk of being wildly out of step with the market is modest.

玛丽安女士的信心看上去有点不可思议，毕竟时尚和宏观经济数据之间并无明显的联系。经济学家乔治·泰勒的理论称裙子越短，股市越好，这一说法也没什么证据支持，莱纳德·劳德所说的'经济下滑时口红销量会上涨亦是如此。WSGN创始人之一的马克·沃斯，卖掉WSGN后成立了一家竞争机构，他曾说：“没有人能真正预测流行趋势。”如果预测师能确保准确率在80%以上，则是因为他们的预测通常可以自我实现。主要零售商是流行趋势预言的受众。对设计师们来说，这些预言提供了某种形式的保障：只要预言广而泛之，自己过分偏离市场的几率就微乎其微。

The business of forecasting is menaced by data-driven analysis, however. The clothing industry’s supply chain is becoming more digital and more flexible: Inditex and H&M, for example, aim to take an idea and turn it into a finished product ready for mass production in two weeks. In response, forecasting agencies are making use of data collated from retailers’ IT systems and have added short-term predictions to their portfolio of services. In 2013 WGSN launched INstock, a retail-analytics service, which uses past sales figures to predict upcoming bestsellers. EDITED, a competing service, provides “solid metrics” in fashion, claiming to use machine learning, an AI technique, in order to predict short-term sales trends.

然而，以数据为主的分析法对商业预测构成了威胁。在时装行业，供应链越发数字化，体系也更加灵活。像印地迪克和H&M两大经销商就打算一旦确定某个想法，就得在两周之内制出成品，用于大规模生产。相应地，预测机构对零售商信息系统中的数据整理利用，并由此在其服务项目中添加了短期预测这一项。2013年，WGSN发布了INstock软件，该软件运用以往的销售数据对未来畅销品进行预测，因此可用于零售分析。INstock的竞争对手EDITED号称运用人工智能中的机器学习法，能对短期销售走势进行预测，从而为时尚业提供“可靠准则”。

Such offerings notwithstanding, the marriage of AI and fashion is still in its infancy. A study in 2014 found that the best predictive models get it wrong nearly half the time. But forecasters are likely to face rising competition as technology firms enter the market. Google, an online giant, now has a “Trend spotting” division. It releases a regular “Fashion Trends Report” based on the firm’s vast trove of search data. So far the results are basic: in 2016 slim “mom jeans” were on the rise while baggier “boyfriend jeans” were on the way out. But Olivier Zimmer, the project’s data scientist, says that the goal is to produce more sophisticated combinations of search and other data.

人工智能和时尚的结合，虽说孕育了上述产品服务，却仍处于初级阶段。2014年的一项研究发现，即便最好的预测模型，出错率仍接近百分之五十。随着技术公司的介入，预测机构还可能面临更大的挑战。网络巨头“谷歌”现在建立了“潮流观测”部。该部门基于谷歌强大的搜索数据库，定期发布“时尚潮流报告”。目前来讲，报告得出的结论尚属浅显，比方说里面会给出“2016年，紧身的“妈妈牛仔裤”兴起而宽松的“男友牛仔裤”正逐渐落伍”这样的结论。但负责这些报告的数据学家奥利维·季默称，更加科学合理地结合搜索数据与其他数据才是目的所在。

【本文作者：徐州七中彭向梅。(公众号：草根英语行思教)】

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