Today’s eco-question: Can algorithms and artificial intelligence serve a more responsible fashion? The - Première Vision Paris - Denim Première Vision - Première Vision New York
At first glance, linking collections to algorithms means letting the consumer dictate the trend, whereas the primary role of creative fashion brands is to infuse creation into everyday life. However, after two decades of constantly increasing consumption, and overproduction generating numerous unsold items that become economic and environmental waste, wouldn’t the genius hidden in the heart of the data provide convincing solutions to this war on waste?
Knowing how to precisely target consumers and their expectations is a major challenge for brands positioned on generations Z and Alpha, who are constantly connected to social networks. Learning how a trend emerges and when a disenchantment, sometimes rapid, can occur, is crucial. On a daily basis, hundreds of millions of images displayed and shared on social networks fuel consumer desire and make their expectations and needs evolve.
With so much data coming in, it’s hard for brands to distinguish between weak and strong signals, between what tends to last and what is purely ephemeral. This is where data analysis platforms and artificial intelligence technologies come into play. Livetrend, Heuritech, Lyst, thus bring a solution to brands willing to be connected to the market in real time.
Based on data analysis and artificial intelligence, these start-ups go beyond classical algorithms.
Where these analyze a result coldly, artificial intelligence by continuous ‘machine learning’ allows to connect the force of accumulation of data of a machine to the interpretation of a virtual brain, feeding and refining its codifications daily, to find the most adapted answer.
Volumes, colors, patterns, sizes, it is through these millions of images and requests posted on the web that these virtual brains will make their analysis. It is clear that with the exponential evolution of artificial intelligence, these solutions are only at the beginning of their history and of their full capacities.
The meeting of ‘data scientists’ and designers to conceive the fashion of tomorrow is taking shape today. So that collections do not become only a basic response to customer demands, the strength will lie in the alliance of these categorized inventories of data at the service of designers who will know how to transmit their vision and 6th sense so crucial to differentiate themselves and make fashion evolve.
However, at a time when one trend chases another as quickly as possible, don’t these tools maintain a logic of consumerism and shopping frenzy?
As is often the case, a powerful tool must be used for a noble purpose. Used to rationalize a production launch, detecting which product might end up unsold can allow objective choices for collection launches. On the other hand, serving an incessant product push, responding in real time to the latest excitement relayed in digital, only feeds a deleterious industry.