In my last post I discussed whether AI tools are usefull in creating art related to fashion. After receiving some criticism I continued my research and found the urge to write about it again. Today I take my stance between two topics: operational transformation (as Luce presents) and the sustainability imperative (as Ramos et al. emphasize). Merging them offers a more balanced view. Yes, AI is likely to shape the future of fashion, but its promise will only be fulfilled if it is executed responsibly and in service of environmental and social goals.
Leanne Luce’s book guides the reader down a roadmap of how AI is involved in every layer of fashion. She argues that AI tools like generative models, help designers create ideas faster, iterate better and provide validation quicker. Still, the human remains central while AI only accelerates and refines. AI is also used for inventory optimization to reduce overproduction and mismatches in supply and demand. Which seems to work quite well for the fashion brands. With the help of a chatbot, search systems make the customer experience more tailored and personalized. These tools are at the same time becoming more accesible for smaller brands. This will lower the barriers of entry and creates more space for experimentation and variety in fashion. Luce did not ignore the risks, but places AI in the position of a colllaborator and not a replacement for human creativity. From Luce’s point of view, the future of fashion is a duality between humans and AI. Where AI serves as a amplification for human intelligence.
The 2023 review by Ramos, Rivas-Echeverria, Perez, and Casas changes the perspective. This review asks how AI can help the fashion industry become more sustainable. These other findings question the optimism from Luce’s book. Ramos et al. provide multiple areas where AI contributes to a more sustainable industry. AI is used for supply chian optimization. This creates better demand forecasting, logistics optimization and better resource allocation. Together this can minimize waste and energy use. AI can also assist in designing eco-friendly materials. AI can detect defects and advice materials for recycling. With this infromation brands can make more informed and sustainable decisions. Artificial neural networks are the backbone in many AI applications in fashion. Usage of this demands massive high-quality datasets, which a lot of fashion brands lack. There’s an imbalance between economic sustainability and social environmental impact. AI is a crucial partner but isn’t a silver bullet.
AI has been forecasted to become a big driver of the fashion future, but not in a deterministic way. The functionality of AI depends on how it is adopted ( ethically, sustainably etc.) The succes of AI in fashion will come from scaffolding human judgment and artisanship, helping humans make better choices. To come back to my previous statement from my previous blog, this does partially agree with my first statement, but now has more backbone in explanation.
References:
Ramos, L., Rivas-Echeverría, F., Pérez, A. G., & Casas, E. (2023). Artificial intelligence and sustainability in the fashion industry: a review from 2010 to 2022. SN Applied Sciences, 5(12). https://doi.org/10.1007/s42452-023-05587-2
Artificial Intelligence for Fashion. (z.d.). Google Books. https://books.google.nl/books?hl=nl&lr=&id=ZRF-DwAAQBAJ&oi=fnd&pg=PR5&dq=AI+tool+in+fashion+industry+&ots=rLumX1HZh3&sig=brjEPXZArXcNcyZGRhCLbn4tods&redir_esc=y#v=onepage&q=AI%20tool%20in%20fashion%20industry&f=false
