Know Your Users: Towards Explainable AI in Bangladesh

When we are talking about explainable AI and trying to come out of the black box by going beyond algorithmic transparency, we are being ignorant about a big user community. Although XAI research has advanced over time, there hasn't been much study done on the development, evaluation, and application of explainability methodologies in the global south. In this paper, we focus on Bangladesh, which is a part of the South, to understand the AI user community of this region and show how the explainability needs are different for different users and who should XAI focus on. Our work reflects on the unique needs and constraints of the region and recommends potential directions for accessible and human-centered explainability research. We argue that before developing technology and systems, human requirements should be assessed and comprehended.