Data But Make It Sustainable Fashion
We see the intersection of data science and fashion being used to push fast fashion trends forward. Brands such as Gap and Rent the Runway predict trends and what customers will likely buy using advanced machine learning algorithms. New technology started off by only contributing to issues in the fashion industry.
What if data science and machine learning could be used to make fashion more sustainable?
Harvard graduate Madé Lapuerta took image recognition as a way to predict the hottest trends in fashion. She created her blog “Data But Make it Fashion” in order to recommend high quality items based on current trends. She suggests what’s “objectively” in style using Google’s image recognition API to identify what are in major collections displayed in Vogue. After gathering the data, she displays and links long lasting items that fit those trends.
The potential for revolutionizing sustainability is massive here. Lapuerta’s website is helping people buy less and of higher quality so that they can be fashionable without breaking the bank or the planet. It directly contrasts the traditional way the industry is run and the constant push for fast fashion. With influencers pushing new clothes they get for free everyday, “Data But Make it Fashion” is a refreshing, inclusive, eco-friendly, and affordable look at true fashion.
It is enough to even say that LaPuerta’s website is the current best solution to the overconsumption crisis. Whether trends are pushed quickly or the rise of thrifting and secondhand shopping, these solutions leave the onus on the fashion houses and sellers. LaPuerta’s solution gives the opportunity for consumers to have power in the way they buy.
