Friday, February 23, 2024

When fashion meets AI

Deepak Halan is an associate professor at School of Management Sciences, Apeejay Stya University

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AI programs are becoming an efficient assistant for human stylists. These can handle more attributes, process large amounts of data faster and learn users’ styles more accurately

Among all the domains of human creativity, human fashion behaviour modelling is one of the biggest challenges given its random nature due to erratic irrationality, individual uniqueness, craziness in selection and adoption, cultural dependence, and individual and cultural distinctiveness. According to a survey, 93 per cent senior business executives feel that selection and promotions of employees are affected by their fashion and clothing choices. To monitor and track the fashion sense, significant time and effort is required. Moreover, employing fashion experts and stylists is cost-intensive, and competent experts and professionals are difficult to get.

Artificial intelligence (AI) artist program AARON, created in 1937 by artist Harold Cohen, was the first profound connection between AI and the human creativity. There are many benefits of using AI programs for fashion designing. AI fashion program can process large amounts of data faster, learn users’ style more accurately, memorise and process users’ feedback, store descriptions of users’ items, and help users become more organised and efficient.

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Evolution of AI

AI is the science and engineering of making intelligent machines, more so intelligent computer programs. In layman’s language, if a computer performs a function that is deemed to be intelligent for humans, we can say the computer has intelligence—an amalgamation of knowledge and reasoning power.

AI has come a long way from the demo of the first running AI program, the Logic Theorist (LT) in 1956, to creation of ELIZA (an interactive program capable of participating in a discussion in English on any subject) in 1965, to the 1990s’ key advances in machine learning, intelligent tutoring, case-based reasoning, multi-agent planning, scheduling, uncertain reasoning, data mining, natural language understanding and translation, vision, virtual reality, games, etc.

ELIZA—an interactive program based on a very basic level of AI (Source:
Fig. 1: ELIZA—an interactive program based on a very basic level of AI (Source:

1997 saw The Deep Blue—an IBM supercomputer that beat the world chess champion Garry Kasparov. By the late 1990s, web crawlers and other AI-based information extraction programs became indispensable in widespread use of the worldwide web.

Convergence of AI and fashion

Applying AI in the field of human creativity has been one of the greatest challenges for software engineers. Fashion changes with culture and time. For instance, Asian fashion style is quite different from European. A complete styling task requires a large number of attributes, including event, clothes, shoes, accessories, makeup and hairstyling. A stylist is also very personal.

How fashion evolved through decades (Source:
Fig. 2: How fashion evolved through decades (Source:

AI stylist programs consider three major components:

1. Visual garment representation—a garment database that stores garment items by categories

2. Computational styling, which processes styling rules and assigns popularity to individual items and completed looks

3. Fashion trend tracking—a learning component that reads users’ feedback and adjusts weight in the style engine based on the popularity rank of a completed look and user opinions on styling looks

Computer vision techniques can extract attribute information from an image and AI techniques such as semantic mapping enable the program to deal with tricky attributes such as fabric. AI programs have the ability to execute a fashion styling task with a simplified model.

AI programs have the ability to execute a fashion styling task with a simplified model
Fig. 3: AI programs have the ability to execute a fashion styling task with a simplified model (Source:

AI-based stylist program

Conceptually, fashion can be defined as a two-dimensional concept, an object and a process. The fashion object can be thought of as a specific product or innovative design. In 2000, fashion design assistant system used genetic algorithms. Later, decision trees with genetic algorithms came into use to model individuals’ clothing. In 2008, stylists started implementing category learning and neural networks in an intelligent clothing shopping assistant system and computer vision techniques with support vector machine classifiers to discover the semantic correlations between attributes.

In the past, studies have been conducted to understand, detect and predict fashion trends and fashion cycles from the perspectives of both the theory and the application. These studies generally focused on predicting trends in colour fashion of clothing. Later, an expert system was developed to assist stylists with information on new colour trends. AI models were also used to predict fashion colour trends with the help of an expert system.

AI programs are becoming an efficient assistant for human stylists. Earlier, stylists used colour harmony evaluation between garment pieces to consider the four basic attributes—colour, outline, print and fabric. An AI-based program is capable of handling more attributes such as event, clothes, shoes, accessories, makeup and hairstyling. Complete fashion design usually includes details such as a top with a bottom or dress, shoes, accessories, bags, hairstyles and makeup.

There are four popular applications of an AI-based stylist program:

1. Internet-based human stylist consultant services for putting communication between clients and stylists on the Internet. It helps to improve the flexibility and accessibility of styling work.


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