Full project title: Benchmarking Large Language Models for Self-Diagnosis
Our work investigates applications of large language models (LLMs) in healthcare settings, with a particular focus on interactions between LLMs and human users. It is a multi-phase project led by Dr Adam Mahdi (Principal Investigator), along with a team of AI researchers and clinical experts.
The Project focuses on LLMs for medical self-diagnosis and identifies factors leading to collaboration failure. We are recruiting 1,000 individuals to better understand these human-machine interactions. This is one of the first large scale projects to study how members of the general public attempt to use LLMs for information-seeking purposes, and adds an important lens in focusing on the risks arising from the interactions.
Departmental Research Lecturer
Project role: Principal Investigator
Adam Mahdi’s research focuses on digital health and application of machine learning in social sciences. He is the director of the UKRI-funded OxCOVID19 Project and a fellow at Wolfson College, University of Oxford.
DPhil Student
Project role: Co-Investigator
Andrew holds a B.S. in Applied Mathematics from Yale University and an MSc in Social Data Science from the OII. He is a Clarendon Scholar and was previously a Thouron Prize winner at the University of Cambridge (Pembroke College).
DPhil Student
Project role: Co-Investigator
Guy is a Shirley Scholar at the OII, an Intensive Care doctor, and the Clinical Lead for a Health AI business at Deloitte. He researches AI-enabled healthcare systems.
