I'm interested in the intersection between psychology and AI. My recent work has looked at the potential that LLMs could persuade or manipulate people, as well as evaluating LLMs at the False Belief task, other theory of mind tasks, and the Turing test.
For more information about my research, see the publications page and my lab website.
Jones, C. R. & Bergen, B. K. (2026). Large language models pass a standard three-party Turing test. Proceedings of the National Academy of Sciences, 123(21). [paper]
Jones, C. R. & Bergen, B. K. (2026). Lies, damned lies, and language statistics: A comprehensive review of risks from manipulation, persuasion, and deception with large language models. Artificial Intelligence Review, 59(4). [paper]
Moore, J., Overmark, R., Cooper, N., Cibralic, B., Haber, N., & Jones, C. R. (2026). Large language models persuade without planning theory of mind. Cognitive Science (accepted). [preprint]
Jones, C. R., Lombardi, A., Mahowald, K., & Bergen, B. K. (2026). LLMs and people both learn to form conventions — just not with each other. Proceedings of the Annual Meeting of the Cognitive Science Society, 48. [paper]
Trott, S.*, Jones, C. R.*, Michaelov, J. A., Chang, T. A., & Bergen, B. K. (2023). Do large language models know what humans know? Cognitive Science, 47(7). [*equal contribution] [paper]
AI can finally pass the Turing test better than a human, study warns. The Independent
ChatGPT just passed the Turing test. But that doesn't mean AI is now as smart as humans. The Conversation
AI passed the Turing Test -- And No One Noticed. Sabine Hossenfelder
Understanding, Grounding, and Reference in LLMs, with Sean Trott. The Gradient Podcast