This paper investigates how AI infrastructure inherently disadvantages speakers of underrepresented languages, using Bengali as a case study. It identifies four key structural failures—web presence, training token deficit, tokenization penalty, and connectivity exclusion—that lead to systematic exclusion and reduced access to AI-assisted educational tools.

This paper investigates the potential of reasoning language models for digital forensics by assessing the usability of the chain of thought mechanism in supporting result explainability.