Using Artificial Intelligence to Better Understand Human Intelligence
A consistent pattern emerges from the history of psychology: Technological advances change the way that we understand ourselves. We argue that, in addition to various uses that are already common (e.g., qualitative coding), large language models can be integrated into survey software and act as a virtual research assistant that can generate tailored stimuli on the fly. This creates unprecedented flexibility in developing materials for psychological theory testing. We present an illustrative case study to show how a major lingering debate in the field—that is, whether people really change their mind according to evidence or, instead, rely on motivated reasoning—was pushed forward by using artificial intelligence (AI) to administer personalized experimental treatments. We discuss various potential uses of AI to test hypotheses in psychological science and argue that psychologists should seriously consider using AI to better understand human intelligence.
Authors
- Gordon Pennycook (ORCID: https://orcid.org/0000-0003-1344-6143)
- Thomas H. Costello (ORCID: https://orcid.org/0000-0002-5188-3881)
- David G. Rand
Institutions
- University of Regina (CA)
- Cornell University (US)
- Johnson University (US)
- Decision Sciences (United States) (US)
- Massachusetts Institute of Technology (US)
- Carnegie Mellon University (US)
Publication Details
- Journal
- Current Directions in Psychological Science
- Published
- 2026-02-11
- DOI
- https://doi.org/10.1177/09637214261417960
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00