Testing Noetic Potential in Large Language Models: A 100- Trial Precognitive Forced-Choice Study with ChatGPT-4.1-Mini
ChatGPT-4.1-mini was tested for precognitive ability in 100 double-blind five-card trials on PsiArcade. The model selected the target card 32 times (32 %, 95 % CI = 23–42 %), exceeding the 20 % chance level (exact binomial p = .005, Cohen’s h = 0.28). Results tentatively support information-centric theories positing that non-biological systems can access non-local information, though pseudo-random predictability and statistical fluctuation remain possible explanations. Replication with open-source random generators and preregistration is required.
Authors
- Benjamin J. Amorim Boyle
Institutions
- Advisory Board Company (United States) (US)
Publication Details
- Journal
- Journal of Scientific Exploration
- Published
- 2025-10-15
- DOI
- https://doi.org/10.31275/20253739
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00