For over two decades, the Princeton Engineering Anomalies Research (PEAR) lab explored one of the most intriguing questions in modern science: Can human consciousness directly influence the physical world?

At the heart of this investigation was the humble Random Event Generator (REG)—a device designed to produce unpredictable sequences, like a digital coin-flipper. But PEAR researchers suspected that beneath the surface noise, patterns might emerge—not from hardware malfunctions or software glitches, but from the minds of human participants.

A Surprising Correlation

Over 12 years and more than 1,000 experimental series, PEAR’s studies showed statistically significant deviations from chance when human operators attempted to mentally influence REG outputs. The average effect size was small (about 0.0001 bits per bit processed), but across billions of bits, the accumulated results exceeded 7 sigma (p ≈ 3.5 × 10⁻¹³)—a threshold that surpasses the gold standard for discovery in physics.

Not Just Close Proximity

These effects weren’t limited to operators physically near the device. Experiments where individuals were remote in space and time showed similar outcomes. Even when the REGs were run at one time and operators focused their intentions at another, anomalous shifts persisted. This suggests that whatever mechanism underlies the effect is not bounded by classical ideas of location or causality.

Hardware Matters

The results only held when true physical randomness was used. REGs based on quantum or electronic noise (like diode-based sources) showed anomalies. But when deterministic pseudorandom algorithms were used—no matter how complex—the effects vanished. This points to the importance of actual entropy and randomness as a substrate for consciousness interaction.

Patterns in the Noise

Delving deeper, PEAR discovered additional structures in the data:

  • Gender differences: Males and females influenced REGs differently, and in some experiments, the combination of genders (e.g., bonded pairs) led to stronger effects than individuals alone.
  • Series-position effects: Results often peaked during an operator’s first session, declined for a few, and then stabilized—a pattern hinting at psychological or cognitive factors at play.
  • Resonant conditions: Experiments involving aesthetic or meaningful feedback (e.g. the ArtREG device, where operators tried to influence images appearing on a screen) often produced similar small but structured effects.

Scaling Up: The MegaREG Experiment

In the MegaREG studies, researchers scaled up trial sizes by 10,000× to see if more bits meant clearer effects. Surprisingly, while larger datasets did show effects, the results inverted—going in the opposite direction of intention. The cause remains unclear, but suggests that interaction with randomness may involve more than just linear scaling of intention.

Beyond the Data: A Pragmatic Interpretation

The PEAR results raise a deeper question: what makes a system responsive to consciousness? Why do effects depend not just on intention, but on context, meaning, and engagement?

At Wyrd Technologies, where we host the original PEAR equipment on loan from the International Consciousness Research Labs (ICRL), we approach this question through the Model of Pragmatic Information (MPI)—a framework that complements and extends the PEAR findings.

Where classical science is concerned with measurable outcomes and Shannon-style information (bits), MPI focuses on meaning—information that emerges within relationships. According to MPI:

  • Consciousness interacts most effectively with systems where there is relational, symbolic, or ecological significance.
  • Pragmatic information arises when intention, context, and potential for change are coherent.
  • Anomalies occur not just because someone “wills” them, but because the system allows entangled meaning to form and persist across the interface between mind and matter.

Reinterpreting some PEAR results through the lens of MPI:

  • The MegaREG inversion may reflect a breakdown in meaningful feedback. As trials scaled to 2 million bits, participants became dissociated from outcomes—eroding the contextual link that stabilizes mind-matter entanglement.
  • The series-position effect aligns with MPI’s principle that novelty and engagement strengthen entanglement. Over time, as actions become habitual, meaning decays and so does effect strength.
  • The stronger effects in gendered or emotionally bonded pairs make sense in MPI terms: mutual resonance and shared intention enhance relational coherence, which strengthens pragmatic information coupling.

In short, MPI suggests that it’s not just what’s being measured that matters—it’s how it matters. The more a system supports symbolic, relational, or ecological meaning, the more it becomes responsive to consciousness.

Consciousness Is a Player, Not a Passenger

The PEAR Lab’s REG experiments challenge a foundational assumption in science: that the observer is separate from the observed. Instead, they suggest that consciousness is not merely watching the unfolding of the universe—it may be co-creating it, one bit at a time.

As we design future technologies—from biofeedback to consciousness interfaces—the legacy of PEAR, reframed through the lens of pragmatic information, offers a crucial insight: where there is true randomness, and true meaning, the door may be open for the mind to step in.

References

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  2. Dunne, B. J. (1998). Gender Differences in Human/Machine Anomalies. Journal of Scientific Exploration, 12(1), 3–55.
  3. Dunne, B. J., & Jahn, R. G. (1995). Consciousness and Anomalous Physical Phenomena. Technical Note PEAR 95004, Princeton Engineering Anomalies Research.
  4. Dunne, B. J., Dobyns, Y. H., Jahn, R. G., & Nelson, R. D. (1994). Series Position Effects in Random Event Generator Experiments. Journal of Scientific Exploration, 8(2), 197–215.
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  8. Jahn, R. G., Dunne, B. J., Dobyns, Y. H., Nelson, R. D., & Bradish, G. J. (2000). ArtREG: A Random Event Experiment Utilizing Picture-Preference Feedback. Journal of Scientific Exploration, 14(3), 383–409.
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  10. Jahn, R. G., & Dunne, B. J. (2003). Problems of Reproducibility in Complex Mind-Matter Systems (with Harald Atmanspacher). Journal of Scientific Exploration, 17(2), 243–270.
  11. Jahn, R. G., & Dunne, B. J. (2004). Sensors, Filters, and the Source of Reality. Journal of Scientific Exploration, 18(4), 547–570.
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  13. Nelson, R. D. (1997). Wishing for Good Weather: A Natural Experiment in Group Consciousness. Journal of Scientific Exploration, 11(1), 47–58.
  14. Nelson, R. D., Jahn, R. G., Dobyns, Y. H., Dunne, B. J., & Bradish, G. J. (2000). The MegaREG Experiment: Replication and Interpretation. Journal of Scientific Exploration, 14(4), 499–555.
  15. Wyrd Technologies (2024–2025). The Model of Pragmatic Information (MPI). [Internal Wyrd Tech white papers, project documentation, and theory development].
consciousness model of pragmatic information parapsychology PEAR Lab Princeton Engineering Anomalies Research psi Random Event Generators REGs RNGs