Inclusion Ethics in AI: Use Cases in African Fashion

Abstract

This paper addresses the ethics of inclusion in artificial in-telligence in the context of African fashion. Despite the proliferation of fashion-related AI applications and da-tasets global diversity remains limited, and African fash-ion is significantly underrepresented. This paper docu-ments two use-cases that enhance AI's inclusivity by in-corporating sub-Saharan fashion elements. The first case details the creation of a Senegalese fashion dataset and a model for classifying traditional apparel using transfer learning. The second case investigates African wax textile patterns generated through generative adversarial net-works (GANs), specifically StyleGAN architectures, and machine learning diffusion models. Alongside the practi-cal, technological advances, theoretical ethical progress is made in two directions. First, the cases are used to elabo-rate and define the ethics of inclusion, while also contrib-uting to current debates about how inclusion differs from ethical fairness. Second, the cases engage with the ethical debate on whether AI innovation should be slowed to prevent ethical imbalances or accelerated to solve them.