Written by Svenja Tegtmeier
AI & data usage in all industries, including Fashion is in everyone's mouth. The discussions, especially in light of the impending EU regulations for AI, and the rate of adoption for the big players are eye-opening and impressive.
Some key aspects and development of AI and the Road Ahead for everyone, but especially in Fashion and how to get started:
A McKinsey study highlighted AI's potential economic impact. It's not just about the technology; it's about the seismic shift it could bring to global industries – Fashion being a key one for its application. For instance, AI could add a staggering €330 billion to Germany's GDP. This is the transformative power of generative AI we're talking about.
As some say, AI will have applications everywhere – in each industry, in each process.
There is an inherent challenge in regulation keeping pace with rapid technological advancements. The faster technology evolves, the harder it becomes for regulations to cover all bases.
This is where ethics come into play, if regulation won’t suffice, other frameworks will have to take its place. Ethics will become important in tech development. It was fascinating to learn how Google incorporates science fiction writers into their process to envision various futures and assess the potential human benefits of their solutions and educating data scientists on ethical machine learning applications with the paradigm to do good for society.
Two important terms to understand when looking at ethics in AI:
The concept of 'Trusted AI', first coined by the EU, sets criteria for how AI should be designed and deployed. It emphasizes responsibility in every development step, with a strong focus on privacy and data protection. Trying to incorporate accountability into the development cycle.
The goal isn't to replace humans but to augment their capabilities. Issues like bias, diversity, equity, and robustness testing for accuracy are crucial. Understanding the probabilities and accuracy of AI decisions is key in making decisions about a learning model but also tools or applications that use AI.
In industries like fashion, embracing AI is not just about competing with technology but competing with humans using AI. This is a game-changer in terms of mindset. Humans excel at long-term planning, and it's in this synergy with AI where the real potential lies. The data potential is enormous and not highly regulated, use cases can be low-hanging fruits in the beginning and can increase efficiencies in all arenas.
Google's foray into virtual try-on is a case in point. They've developed a tool where users can virtually try on shirts using one of 80 models. This tool, currently limited to shirts for women in the US without logos, is a glimpse into the future of shopping. The code is even available on GitHub, showcasing Google's approach to building this technology.
SAIZ tackles the soaring returns crisis faced by brands, leveraging existing data. With return rates in apparel reaching 40-70%, SAIZ empowers retailers to unlock insights from their data, addressing correlations between returns and product on different dimensions, e.g. sizing & fit, geography, pricing, and customer behavior. By helping brands access, blend, and analyze data effectively, we provide a comprehensive understanding of economic value, mitigating the impact of returns on profits and environmental sustainability.
In conclusion, as the fashion industry gears up for the transformative wave of generative AI, it's essential to recognize the synergistic power of combining human ingenuity with AI's capabilities.
The acceleration of tech and AI will undoubtedly shape customer expectations. Getting started with AI tools is no longer optional; it's essential to stay competitive.
At SAIZ, we're at the forefront of this revolution, utilizing advanced AI to revolutionize how clothing brands understand and cater to their customers. Our technology goes beyond mere size recommendations; we provide deep insights into customer preferences and sizing trends, enabling brands to make informed decisions that enhance design, fit, and overall customer satisfaction.
Sources: many of these ideas and impulses were taken from the event hosted by Google, Ben Zevenbergen and other experts like Ramak Molavi Vasse'i, Ernst-Cornelius Koch.
