CMS : EAS Trailblazers Department Seminar

Every month, more than a billion people interact with conversational AI. Large language models (LLMs) influence people's beliefs and decisions; social interactions and relationships; and our collective societal well-being. I develop computational approaches to account for these broader human and societal outcomes in LLM development. I identified the widespread issues of AI sycophancy and overreliance, and developed technical interventions to address these issues, such as algorithms to optimize LLMs for outcomes beyond immediate user satisfaction, and representation-level methods to control the implicit assumptions encoded in model internals. My work shows how we can develop AI that promotes human agency and long-term well-being.