A Primer on Mitigating Gender Biases in LLMs: Insights from the Indian Context
Credits: Paūs
Report
/
Sep 2024

A Primer on Mitigating Gender Biases in LLMs: Insights from the Indian Context

Urvashi Aneja /Aarushi Gupta /Anushka Jain /Sasha John

This guidebook presents the core findings of research on gender bias in large language models (LLMs), offering key insights, practical recommendations, and tools in a structured and accessible format.

The infographic below illustrates the key steps in developing and deploying LLM-based chatbots in the Indian context, spotlighting the gender equity concerns that arise at each stage.

The primer takes a closer look at each stage, and offers practical recommendations for developers to embed gender equity in their applications, alongside broader system-level strategies for institutional actors shaping India’s LLM ecosystem.