*Please note this event will take place from 12-1pm Pacific*
Join us on Wednesday, May 10th 12-1pm (Pacific) to hear from Dr Johannes Eichstaedt and Dr Lyle Ungar, of the World Well-Being Project, as they share their work in assessing and promoting mental health using AI and natural language processing.
The content shared on social media makes up one of the largest datasets on human behavior in history. Dr Eichstaedt, PhD (Stanford) and Dr Ungar, PhD (University of Pennsylvania) have developed methods to leverage this data to unobtrusively measure the mental and physical health and well-being of individuals and populations using machine learning, AI and Natural Language Processing (NLP). On the individual level, machine learning models applied to patients’ Facebook statuses can predict their future depression status before it appears in their medical records. On the population level, when language-based prediction models for depression are applied to 1.2 billion geo-tagged Tweets, they allow for the estimation of county well-being with higher external validity than surveys. With regards to the treatment of mental health conditions, recent advances in generative AI models such as GPT4 offer opportunities and risks in supporting mental health treatment – and such developments require careful involvement of clinicians. Drs Eichstaedt and Ungar argue that psychologically-informed NLP and responsible use of AI can augment clinical practice, guide prevention, and inform public policy. Their presentation will be followed by an opportunity for Q&A.
Johannes Eichstaedt is an Assistant Professor (Research) in Psychology at Stanford and a Shriram Faculty Fellow at the Institute for Human-Centered A.I. He is a computational psychologist and interdisciplinary data scientist studying the mechanisms that give rise to mental and physical health by applying NLP to digital text. His research also explores the use of Large Language Models to promote well-being and mental health. Johannes received his Ph.D. at the University of Pennsylvania in 2017 and was elected a Rising Star by the Association of Psychological Science in 2022.
Lyle Ungar is a Professor of Computer and Information Science at the University of Pennsylvania, where he also holds appointments in Psychology, Bioengineering, Genomics and Computational Biology, and Operations, Information and Decisions. He has published over 400 articles, supervised two dozen Ph.D. students, and is co-inventor on ten patents. His current research focuses on using natural language processing and explainable AI for psychological research, including analyzing social media and cell phone sensor data to better understand the drivers of physical and mental well-being.
In 2011, Eichstaedt and Ungar co-founded the World Well-Being Project (together with Andy Schwartz), with this inter-institutional consortium, they have since attracted $4.9m+ in funding and published 60+ articles.
CME Credits: You may be eligible to receive CME credits for attending this Hubinar. More information will be provided at the start of the event. If you have questions, please reach out to Pippa Kennard (pippa@stanford.edu).
Zoom link: https://stanford.zoom.us/j/98370833434?pwd=c3NadnhLWWtSMWVFSXRiOExRL0cyZz09