Akal Badi ya Bias: An Exploratory Study of Gender Bias in Hindi Language Technology
Rishav Hada, Safiya Husain, Varun Gumma, Harshita Diddee, Aditya, Yadavalli, Agrima Seth, Nidhi Kulkarni, Ujwal Gadiraju, Aditya Vashistha,, Vivek Seshadri, Kalika Bali

TL;DR
This study explores gender bias in Hindi language technology, highlighting the limitations of current methods and emphasizing the importance of community-specific approaches to understand and address bias in underrepresented linguistic contexts.
Contribution
It is the first comprehensive analysis of gender bias in Hindi, employing diverse techniques and field studies to reveal limitations of existing methods and advocate for community-centric research.
Findings
Current methods are limited in mining Hindi gender bias.
Field studies reveal diverse perceptions of bias among rural women.
Community-specific approaches are essential for effective bias mitigation.
Abstract
Existing research in measuring and mitigating gender bias predominantly centers on English, overlooking the intricate challenges posed by non-English languages and the Global South. This paper presents the first comprehensive study delving into the nuanced landscape of gender bias in Hindi, the third most spoken language globally. Our study employs diverse mining techniques, computational models, field studies and sheds light on the limitations of current methodologies. Given the challenges faced with mining gender biased statements in Hindi using existing methods, we conducted field studies to bootstrap the collection of such sentences. Through field studies involving rural and low-income community women, we uncover diverse perceptions of gender bias, underscoring the necessity for context-specific approaches. This paper advocates for a community-centric research design, amplifying…
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Taxonomy
TopicsSouth Asian Cinema and Culture · Labor market dynamics and wage inequality
