The Turning Tide: Breakthrough evidence for global consciousness

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Roger D. Nelson, Director 
Global Consciousness Project, Princeton, NJ, USA 

Introduction: In August 1998 two US Embassies in Africa were bombed by terrorists. This shredding of the social contract protecting diplomacy shocked the world, and the hours around the explosions became the first formal event monitored by the Global Consciousness Project (GCP). Over the next 17 years 500 rigorously specified tests were made of the GCP’s general hypothesis that major events on the world stage would correspond to detectable changes in the data from our network of dozens of random number generators (RNG). See Figure 1. We looked at a variety of different categories of events, allowing some analysis of what characteristics seemed most conducive to the correlations found in the data apparently linked to the shared thoughts and emotions of people around the world. The overall effect size in the formal data is about one-third of a standard deviation, but over the 500 replications of the hypothesis test, this modest difference accumulates to a 7-sigma departure from expectation, and trillion-to-one odds against chance fluctuation as an explanation. This strong finding provides a basis for deeper examination of the data both to understand better how the effects arise, as well as to develop interpretations and applications. 

Method: We will consider several recent assessments of possible correlations of GCP data with external variables that are independent of the event-based analyses of the original project. These new analyses use a variety of methods including time-series, correlational, and multi-scale entropy analysis. 
1. Stock market trends 
Ulf Holmberg has shown that certain stock market measures co-vary with GCP data. (2020) A variable derived from the random numbers obtained by the GCP is statistically related to various well-known stock market index returns. The relationship is shown to be non-linear and [it is shown] that variations in the variable, to some extent, predate the underlying trade. The results presented are found to be robust and qualitatively unaffected by the removal of outliers. 
2. Google search terms 
Ulf Holmberg proposed a Google search index that is predicted to covary with GCP data (2021). Using Google Trends internet search data, Holmberg designed several search indexes and applied time series statistics to correlate the indexes with aggregates derived out of the GCP data. The analysis finds that the GCP data significantly correlates with the indexes and that the data can be used to improve the statistical model’s in-sample fit. See Figure 2. Furthermore, it is found that out-of-sample forecasts on global search trends can be made more accurate if the forecasts utilize the information contained in the GCP data. The results thus suggest that the hypothesis underlying the GCP is valid and that the GCP data can be put to practical use by individuals such as. forecasters.  
3. Multi-scale entropy 
Dean Radin found variations in long term GCP data indicating significant negentropy. (2022) The analysis examined the whole 23-year database to explore whether the emergence of negentropy was specific to formally pre-specified events or reflective of a more fundamental relationship between mind, matter, and entropy. Two methods of analysis were used to detect temporal dependencies in time-series data. Both methods provided robust statistical evidence for negentropic behaviour in what should have been, from a conventional perspective, a truly random sequence.  
4. Evoked potential analogue 
Roger Nelson discovered patterns in GCP data that resemble patterns of evoked potentials in human brains. (2020) In both cases there is a stimulating event that is linked to a characteristic response. A flash of light evokes a response in noisy data from the occipital cortex: a time-locked signal average across many flash repetitions shows a large voltage peak preceded and followed by a smaller peak of opposite sign. In a similar manner, powerfully engaging events on the world stage apparently evoke deviations in GCP data. Signal averaging and smoothing reveal the same pattern as the brain evoked response: a large peak surrounded by smaller peaks of opposite sign. See Figure 3.  
Results: Several analyses, independent of the originally specified procedures, yield interesting and robust correlation or covariance measures linked to variations in GCP data. There are potentially predictive relationships between GCP data and stock market valuation shifts, and we also can see significant correlation of GCP data to high-usage Google search terms. We find evidence that data from the GCP network varies in its calculated entropy: the data are not fully entropic, and instead show structure (negentropy) in multi-scaled entropy measures. Finally, the network appears to respond to stimulating events (disasters, celebrations) as if they were stimuli to the senses of a global mind (or at least, stimuli modulating the coherent attention of huge numbers of people). Visualized using standard brain wave processing tools, the GCP network response typically shows a characteristic pattern that parallels human brain evoked responses, albeit on a vastly different temporal scale.  
Discussion: The desire to explain data like those from the GCP leads to suggestive theories or models. One candidate is a “consciousness field” that can be modeled as an information field sourced in the mass of attentive human beings and focused by world events. Another candidate theory is a kind of observational model in which the experimenter(s) are the source of the psi effect, using precognition of future states of the data to enable opportune specification of test events. The former is a more capacious model, flexible enough to accommodate structure not predicted in the original event analysis. The latter can plausibly explain the original hypothesis test results, but not the other structure that deeper analysis reveals, nor the linkage to external correlates. 

Holmberg, U. (2020). Stock returns and the mind: An unlikely result that could change our understanding of consciousness. Journal of Consciousness Studies, 27(7–8), 31-49. 

Holmberg, U. (2021, July 23-31). Validating the GCP data hypothesis and harvesting its data [Paper presentation]. SSE-PA Connections 2021, online. 

Radin, D. (2022, March 13). Anomalous entropic effects in 23 years of continuously recorded truly random data: An exploratory analysis. 

Nelson, R. (2020). The global consciousness project’s event-related responses look like brain EEG event-related potentials. Journal of Scientific Exploration, 34(2), 246-267. 

Course Instructor

Roger Nelson
Roger Nelson Author

Roger Nelson runs the Global Consciousness Project (GCP), an international collaboration studying mass consciousness. He conducted psi research at the Princeton Engineering Anomalies Research (PEAR) laboratory from 1980 to 2002, and while at Princeton, created the GCP in 1997. Interests in psychology, physics, philosophy, and the arts facilitate his research at the edges of what we know. His focus is the subtle interconnections that define an emerging humanity.

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