Precognition—the apparent acquisition of information about future events through means not explained by conventional inference—has been tested using controlled laboratory protocols since the early 20th century. This review examines the strongest supportive evidence from (a) meta-analyses of forced-choice and free-response precognition studies, (b) time-reversed physiological anticipation (“presentiment”) experiments, and (c) high-profile social priming-style experiments suggesting anomalous retroactive influence. While effect sizes are typically small, multiple meta-analyses report statistically significant results across independent labs.

Introduction

Precognition research seeks to eliminate normal sensory cues and probabilistic reasoning by using random event generators, computer-controlled stimulus presentation, and blind judging. A distinction is drawn between forced-choice precognition (e.g., guessing future targets from fixed alternatives) and presentiment paradigms (measuring physiological responses before unpredictable stimuli). The following sections summarize the most cited pro-precognition literature.

Key Lines of Evidence

1) Meta-Analyses of Precognition Studies

Honorton & Ferrari (1989) conducted a meta-analysis of 309 forced-choice precognition experiments published between 1935–1987, finding a small but highly significant mean hit rate above chance (overall Stouffer Z ≈ 6.02, p ≈ 1.2×10−9) [1]. This analysis included rigorous studies with automated randomization and feedback controls.

Storm & Ertel (2001) extended the analysis to include both forced-choice and free-response designs, confirming a small positive overall effect [2].

2) Presentiment Experiments

Mossbridge et al. (2012) meta-analyzed 26 psychophysiological studies where participants’ unconscious responses (e.g., skin conductance, heart rate, EEG) were measured before the random presentation of emotional vs. calm stimuli. They found a small but significant anticipatory effect (random-effects p < 0.01) [3]. These results persisted across labs and equipment types, with effects emerging 1–10 seconds before stimulus onset.

3) Retroactive Priming & Memory Studies

Bem (2011) published a series of nine experiments in Journal of Personality and Social Psychology using standard social psychology paradigms (e.g., priming, recall) but reversing the temporal order of stimulus and response. Across studies, results suggested that participants’ choices or recall performance were influenced by stimuli presented after their response (combined p < 0.01) [4]. Replications have produced mixed outcomes, but the original publication prompted widespread discussion of time-symmetric psychological processes.

4) High-Control Randomization Protocols

Several labs have implemented computer-based, hardware RNG-controlled target selection to ensure that future events are genuinely unpredictable at the time of the participant’s response [1–3]. Studies with pre-registered analysis plans and automated logging further reduce potential sensory leakage or experimenter bias.

Converging Patterns

  • Effect size: Typically small (e.g., hit rates 1–3% above chance, or d ≈ 0.1–0.2) but consistent enough to achieve statistical significance in large aggregated datasets [1–3].
  • Methodology: Randomization, feedback control, automation, and blinding are essential to rule out normal explanations.
  • Cross-paradigm evidence: Effects have been reported in cognitive, physiological, and forced-choice tasks, suggesting robustness across measurement domains.

Common Objections & Replies

  • Publication bias: Meta-analyses [1,3] include file-drawer estimates; effects remain statistically significant after conservative bias adjustments.
  • Replication: While some high-profile replications (e.g., Bem’s studies) have failed, others have succeeded; overall meta-analytic outcomes remain positive when pooling all replications [5].
  • Statistical artifacts: Critics argue that small effect sizes are susceptible to p-hacking; proponents counter with results from pre-registered, automated protocols that minimize researcher degrees of freedom [3,5].

Assessment

The strongest peer-reviewed evidence for precognition comes from large-scale meta-analyses of decades of experiments, which consistently find small but nonzero effects that cannot be easily explained by chance or bias alone. Presentiment paradigms provide a converging physiological line of support. However, ongoing mixed replication outcomes and the absence of a clear mechanism keep the question open.

Conclusion

If “real” means “detectable above chance with well-controlled methods,” portions of the precognition literature meet that definition, albeit with small effect sizes and unresolved theoretical issues. Future work should focus on multi-lab, pre-registered replications and theoretical integration with models of time and consciousness.

References

  1. Honorton, C., & Ferrari, D. C. (1989). “Future telling”: A meta-analysis of forced-choice precognition experiments, 1935–1987. Journal of Parapsychology, 53(4), 281–308. Abstract
  2. Storm, L., & Ertel, S. (2001). Does precognition exist? A meta-analysis of free-response experiments. Journal of Parapsychology, 65(3), 211–240. Abstract
  3. Mossbridge, J., Tressoldi, P., & Utts, J. (2012). Predictive physiological anticipation preceding seemingly unpredictable stimuli: A meta-analysis. Frontiers in Psychology, 3, 390. Full text
  4. Bem, D. J. (2011). Feeling the future: Experimental evidence for anomalous retroactive influences on cognition and affect. Journal of Personality and Social Psychology, 100(3), 407–425. DOI
  5. Bem, D. J., Tressoldi, P. E., Rabeyron, T., & Duggan, M. (2015). Feeling the future: A meta-analysis of 90 experiments on the anomalous anticipation of random future events. F1000Research, 4, 1188. Full text