ALT Re-contextualizing Fairness in NLP: The Case of India by Shaily Bhatt, Sunipa Dev, Partha Talukdar, Shachi Dave, Vinodkumar Prabhakaran from Google Research. Abstract: Recent research has revealed undesirable biases in NLP data & models. However, these efforts focus on social disparities in the West, & are not directly portable to other geo-cultural contexts. In this paper, we focus on NLP fairness in the context of India. We start with a brief account of the prominent axes of social disparities in India. We build resources for fairness evaluation in the Indian context and use them to demonstrate prediction biases along some of the axes. We then delve deeper into social stereotypes for Region & Religion, demonstrating its prevalence in corpora & models. Finally, we outline a holistic research agenda to recontextualize NLP fairness research for the Indian context, accounting for Indian context, bridging technological gaps in NLP capabilities and resources, and adapting to Indian values