Special Session: Corporate Social Responsibility and AI: The Case of Fashion: An Abstract

Abstract

This paper critically examines the ethical issues of current and predicted adoption of AI within fashion. AI is a branch of computer science that combines machine learning, logic and natural language processing to emulate human intelligence. By processing vast amounts of data and recognising patterns in the data, AI produces insights and analytics at or above human capability (IEEE 2017). It has been applied to fashion in trend forecasting, personalisation, customer interaction and the use of CGI models. For example, Amazon developed “Echo Look” which combines computer vision with predictive AI and human analysis to assess a consumer’s current wardrobe choices and provide recommendations of what to wear. Users can ask the machine to rate two different possible outfits in terms of current trends and actual appearance (Gibbs 2017). Online styling subscription Stitch Fix uses machine learning algorithms to determine its customers’ preferred styles and offer personalised recommendations. AI has also been developed to mimic the role of social media influencers and models. CGI character “Miquela” has 1.6 million Instagram followers, collaborates with luxury brands and launched her own clothing brand, but is not a real person. There is a dedicated digital modelling agency (Davis 2018). Such innovations are likely to further inflame the ongoing ethical debate about using digital technologies and virtual reality at the risk of opportunities for real people, for example diminishing already scarce opportunities for black models (Graham 2018), or introducing norms of artificial appearance and personal aesthetics impossible for ‘real’ people to achieve. AI has the potential to revolutionise fashion through greater precision, accuracy and effectiveness in decision-making, but at what cost? To what extent can and should AI replicate and replace human creativity and presence in an industry sector founded on human input in creating new trends? Yet, AI that predicts garment suitability and offers greater customisation for consumers may reduce waste and over-consumption (Snow 2017). Producing items which have greater relevance could reduce returns, markdowns and warehouse space, plus increase customer satisfaction and experience. Automating repetitive tasks could save money and time for greater value-added activities, for example through the use of chatbots for online customer service. This paper applies the lens of CSR to inform the debate on whether core fashion retailing functions can and should be replaced by AI. A CSR approach argues for businesses assuming social responsibilities beyond any economic, technical and legal obligations which constitute its existence, with the objective of reconciling economic, social and environmental objectives (Davis 1973).