Dr. Zhicheng Lin: AI for psychology, psychology for AI
Dr. Zhicheng Lin: AI for psychology, psychology for AI
AI for psychology, psychology for AI
Date HKT 18 March 2024 (Monday)
Time HKT 10:00 am – 11:30 am
Venue Room ACC 101A, SCE
Abstract:
The recent emergence of generative AI (GenAI), particularly large language models (LLMs), has sparked both excitement and concern. What is it capable of, and what is it not capable of? Is it just hype, or is it genuinely heralding a “paradigm shift”? Most importantly, is our profession as psychologists “safe”? In this talk, I propose that the relationship between AI and psychology is fundamentally symbiotic: GenAI is reshaping how psychological research is conducted (“AI for psychology”) while it stands to gain from the insights offered by psychology (“psychology for AI”). Drawing from recent cognitive and metascience research, I illustrate how GenAI emerges as a groundbreaking tool for facilitating various aspects of the research process, including academic writing and software programming. It also serves as a powerful framework for revisiting enduring debates and exploring novel questions within psychology, such as the mechanisms of face perception. Conversely, psychology is indispensable in contributing to GenAI, addressing latent psychology (e.g., bias) in training data, cognitive mechanisms in its functioning (e.g., explainable AI), human perception of and interaction with AI (e.g., algorithm aversion), and the development of more intelligent AI systems (e.g., learning from real-world interactions). Despite potential ethical concerns, I argue that psychologists have much to gain from and much to contribute to this AI–psychology symbiosis.
About the speaker:
Zhicheng Lin received his Ph.D. in Psychology from the University of Minnesota and his B.S. in Psychology from Peking University. He is currently a Hundred Talents Program Investigator at the University of Science and Technology of China. His research interests include how humans perceive and attend to visual information (e.g., food images) and, more recently, the integration of AI into scientific inquiry, particularly in research practices (e.g., academic writing and software programming) and social/behavioral science research. His empirical research has been published in leading psychology journals, including Psychological Science, Journal of Experimental Psychology: General, Psychological Bulletin, American Psychologist, Perspectives on Psychological Science, and Advances in Methods and Practices in Psychological Science. His opinion and conceptual work have appeared in various top journals such as Trends in Cognitive Sciences, Nature Human Behaviour, and Nature Biomedical Engineering. He is currently an Associate Editor for Psychological Science as well as Behavior Research Methods.
