Abstract

The rapid advancement of large language models (LLMs) has unlocked a myriad of possibilities for positive societal impact, ranging from enhancing accessibility and communication to supporting disaster response and public health initiatives. However, the deployment of these technologies also raises critical concerns regarding accountability, fairness, transparency, and ethical use. In this talk, I will discuss  our efforts for auditing models, detecting and mitigating biases, and understanding how LLMs make decisions. We hope to open the conversation to foster a community-wide effort towards more accountable and inclusive LLM practices.