Fairer Datasets for Advancing Responsible AI Systems

Abstract

The primary aim of this research is to develop diverse and fair datasets, with a specific focus on marginalized demographics like the Global South and/or non-binary gender groups. I am working towards creating two types of datasets-- (a) Real and Synthetic face datasets from Global South for auditing/training Face Recognition Systems. These are used in tasks like face detection and facial attribute analysis, and (b) Datasets with non-binary gender labels, across modalities like image and text for more inclusive retrieval (visual search enabled e-commerce) and classification (text-based gender prediction) tasks.