Can we gain Insight into the nature and origin of UAPs

This text is the synthesis of more than 10 years of work, carried out in a rather discontinuous way depending on my workload. It describes the strategy pursued since 2004 (yes—quite a long time ago!), with the aim of bringing elements of proof (or at least the most convincing possible) that a structured intelligence lies behind the activity of UAPs, or the UFO phenomenon. This is not a classic analysis of testimonies, as you will see.

The text, presented here in the form of questions and answers, is loosely based on an interview with Marie-Thérèse de Brosses given at the end of August 2015 for the French radio station Ici & Maintenant. It also sheds light on the context of the mathematical paper that I co-authored and posted on arXiv, as well as on the GEIPAN website.

It is important to note that it does not represent a firm position, but rather a series of hypotheses, variously consolidated by scientific or philosophical arguments.

Finally, it is also important to specify that this work was developed independently of CNES (the French Space Agency) and specifically of GEIPAN, whose mission is to investigate Unidentified Aerospace Phenomena. Some people know that I also work within this small team of four people, in Toulouse.

Are we able to demonstrate that some UFO(s) have an "Extra-Terrestrial" origin?

A classic but difficult question… This type of question bundles several presuppositions. The acronym “UFO” speaks of:

• “Objects” — i.e., something material;
• “Flying” — i.e., something dynamic, perhaps piloted, but in any case suggesting an intelligence behind it;
• and, for many people, something coming from somewhere other than Earth.

It also carries a number of clichés: flying saucers, extraterrestrial beings, little greys (!)…

>> Okay, but can we simplify the problem and simply PROVE the existence of an INTELLIGENCE at work behind some UFOs?

Maybe that is easier.

But we would first need to define what we mean by a PROOF. And, in practice, that does not interest many people in ufology:

Scientific proof and legal proof are not the same thing.

In UFO matters, we often drift toward the second type of proof—“to bring the intimate conviction of…”—but is that enough?

>> In that case, what could constitute reliable and sufficient proof?

In terms of individual documents: not much.

With the development of information technology, documents offered as “evidence” are increasingly easy to falsify.

Today, even a sincere witness with objective material can be questioned. As I sometimes say: tomorrow you could take a picture of a flying saucer landing in your garden (sic!)—it would not serve as proof and would not overturn opinions. You would need much more.

In reality, a single testimony—even sincere and objective—does not have sufficient value to serve as proof, or to bring that intimate conviction to the public.

So how could we prove the existence of an intelligence?

By looking for a hidden order within the immense mass of available UFO testimonies—unexplained phenomena, classified as “PAN D” under the CNES/GEIPAN typology.

Then by measuring the probability that this order cannot be due to chance—and finally, that this order indicates an intention.

Individually, testimonies usually contain only a very small amount of exploitable information. Collectively, after more than 60 years of archival accumulation, they represent a colossal mass of information.

The goal is to find a proof that does not depend on a single witness—whom one could always challenge—but rather a proof that emerges from the mass of data, which cannot reasonably be suspected of hoax: a pattern traced by behavior, over several generations, at the scale of the planet.

>> In that case, what data should we analyze and extract from this mass of testimonies?

I chose to rely on two types of elementary data, the most common ones, so as to obtain as independent, transversal, and as comprehensive a basis for comparison as possible.

>> Meaning?

In general, in most testimonies, we have a place and a date—i.e., “space” data, connected to the environment, and “time” data. Historically, I treated these two types separately, starting with environmental data (everything we can observe around us: people, infrastructure, forests, rivers, etc.).

How could unexplained phenomena be related to the environment?

UFOs are only a small subset of unexplained phenomena. If “UFOs” are technologically advanced objects, we can use foresight and attempt to extrapolate the concerns of a “human from the future”—a being able to see farther in time and space.

Starting from our underlying motivations as a species, we can try to identify what may be of interest to an advanced civilization. We will see that, among these concerns, the question of long-term environmental balances—ecosystems—likely becomes central, since they make it possible to sustain the evolution of life, intelligence, and cultures.

This is ultimately about identifying the factors that constrain the destiny of civilizations—factors that can call into question the survival of species and the evolution of life on habitable planets. But I will come back to that.

In addition, from a logical point of view, we can group unexplained phenomena—UFOs or PAN D—into three categories:

• (a) Phenomena produced by the environment. Favorable local conditions produce the phenomenon. For example, will-o’-the-wisps (natural methane emissions) or Thai lanterns (human-made) belong to the environment and are “endogenous”.
• (b1) Phenomena coming from outside and entering the local environment to interact, transmit, or collect information. Example: a drone with a camera (“active exogenous”).
• (b2) Phenomena passively passing through the local environment (that of the observer), with no direct relation to it. Example: a shooting star, an airplane (“passive exogenous”).

Fig. 1 — Origin of phenomena and their connection with the environment: (a) endogenous; (b1)/(b2) exogenous, active/passive.

What is interesting to note is that, in two out of three cases, the phenomena—whatever they are—have something to do with the environment.

>> So the spatial data…

Yes: it will allow us to study whether there is a relationship between phenomena and the environment—for example, whether there are environmental peculiarities in the places where phenomena are observed.

Is that why, in 2004, you built the U-Sphere website?

Exactly. U-Sphere initially aimed to develop mapping tools and set up databases to analyze relationships between environmental “spheres” and UFOs—in particular, whether there could be links with major environmental risks (called “systemic” risks, because they are likely to seriously disrupt ecosystems).

Between 2004 and 2008, I devoted myself to developing the cartographic layer to represent environmental data, and to performing correlation calculations with observations.

The idea was to identify the major environmental risks that could decisively condition the planet’s future. When I began this work, the discipline now called Earth system science was not yet established as such; it is a subject that has been steadily gaining importance.

Fig. 2 — “Ecosystemology”: main environmental risks for humanity at the planetary scale (Asteroids & Comets are missing from this diagram!).

The selected risks are of two types: natural and artificial (anthropogenic—mainly Nuclear, Bacteriological, and Chemical risks). A diagram I called “Ecosystemology” identifies them.

Ufologists have often observed strange correlations between UFO appearances and certain places, without making any connection beyond nuclear power.

The World Economic Forum (WEF) has also gradually taken an interest in these issues. This is not surprising: when human interests are organized on a global scale, it is normal to do everything possible to preserve them. The WEF now publishes an annual Global Risks Report, detailing and measuring major risks to humanity.

>> And the temporal data?

Yes—and it is easier to grasp. Time data corresponds to the simple reading of a signal: the number of “UFO” sightings over time. It allows us to attach events to a chronology.

What is the distribution of phenomena over time?

Globally, observations are reported every day by witnesses at a roughly constant level. But, exceptionally, what are called “waves of sightings” occur: suddenly, over large geographic areas—across a country or a continent—dozens, if not hundreds, of sightings are reported.

Fig. 3 — The 10 most important waves of observations (testimonies per day), smoothed over 10 weeks. L. Hatch data, 2000.

Fig. 4 — The 10 most important waves of observations (testimonies per day), smoothed over 3 months. L. Hatch data, 2000.

By retaining only the 12 strongest waves on the preceding diagrams, here are some “key” dates: 1947, 1952, 1954, 1965, 1974…

Some of these years are well known to ufologists.

Precisely:

Table 1 — The 12 most important waves of observations since the explosion of the phenomenon in 1947.

Wave	Year (decimal)	Date (DD/MM/YYYY)
v0	1947.51	07/06/1947
v1	1950.24	03/29/1950
v2	1952.57	07/28/1952
v3	1954.78	10/14/1954
v4	1957.84	05/11/1957
v5	1965.63	08/20/1965
v6	1966.30	04/22/1966
v8	1967.72	09/19/1967
v9	1968.56	07/23/1968
v10	1973.79	10/17/1973
v11	1974.16	02/28/1974
v12	1990.84	05/11/1990

>> What characterizes these waves of observations?

There is no academic definition, but let’s say that, over about a week, the usual number of sightings is multiplied by 10.

Fig. 4 — Average number of sightings during a wave.

A wave of observations typically starts about a month before reaching its maximum, and continues for about a month afterwards.

Why and how could observation waves occur?

To this day, no one knows. These waves show no particular warning signs, and no one has yet produced a convincing explanation.

>> Aren’t there at least some working hypotheses?

Of course. I have at least three families of hypotheses in mind:

• The “supervised learning” hypothesis (active exogenous hypothesis; cf. Fig. 1 (b1)).

This was suggested by Fred Beckman and Prof. Price-Williams of the University of Los Angeles. These two scientists would have come up with the idea when they saw graphs produced from Jacques Vallée’s computer.

A difficult result to obtain at the time, since it took Jacques Vallée a little more than four years to build the necessary databases. He later popularized the idea under the name “control theory”.

>> Hmm. “Control theory” or “supervised learning”—but what does that mean exactly?

It is a term used by artificial intelligence researchers:

The regular repetition of information by a teacher (here, the “supervisor”) to allow the learning system to record it. The supervisor observes and monitors the student’s progress and chooses an appropriate educational program in order to optimize learning.

>> If I understand correctly… applied to “UFOs”, what would that mean? What exactly would we be learning?

By being repeatedly exposed to testimonies—and therefore to reported information about UFOs—we would gradually become familiar with the concepts and ideas linked to “UFOs”: extraterrestrial intelligences, extraterrestrial life, spaceships, exoplanets, interstellar travel…

These themes have been taken up by literature and cinema and have echoed through popular culture, to the point that the “ins and outs” (i.e., “who creates the information?”) can become inextricable.

At the level of society, it is a form of acculturation or social engineering that disrupts our way of seeing things. Roswell is a pure archetype: the grey alien head with big almond eyes has been massively popularized.

Be that as it may, this hypothesis was proposed at the time without a solid theoretical foundation. But we will come back to that.

• The hypothesis of a production of human collective consciousness that would generate visions (endogenous hypothesis; cf. Fig. 1 (a)).

This production reappears in certain fragile or sensitive individuals in the form of dreams, hallucinations, flashes, and various forms of “attacks”, possibly of a psychiatric nature. This is a hypothesis evoked by the psychoanalyst C. Jung in his book Flying Saucers: A Modern Myth of Things Seen in the Skies (1958).

>> But are there examples of psychosocial phenomena that could synchronize individual events into these waves of observation?

We have very little scientific data—except on subjects that are unfortunately rather morbid. Suicides appear to be contagious (behavioral contagion—Gould, 1990). More recently, it was found that mass killings may also follow this kind of pattern, with psychosocial contagion lasting 13 days (Contagion in Mass Killings and School Shootings, Sherry Towers, 2015). These contagion patterns, generally propagated by the media, seem linked to the strong emotional component of the phenomena.

However, it is true that in the case of UFO sightings, emotion is also a major factor: it is common for the phenomenon to alter individuals’ conceptions, or at least strongly reinforce them.

That said, C. Jung wanted to specify the limits of any approach that tries to reduce everything to psychosocial considerations: physical effects external to individuals cannot be regarded as a psychosocial effect.

• These waves would be the result of environmental activity not specifically linked to humans (passive exogenous hypothesis; cf. Fig. 1 (b2)).

A hypothesis I proposed to test on U-Sphere.

>> But what environmental phenomena—strong enough and recurring at intervals of several years—can we imagine?

It is difficult to imagine such phenomena. However, we can narrow the field to phenomena with long activity cycles—since UFO sighting waves occur on those time scales—and which can influence humans.

>> What are you thinking of?

Some scientists, like Jacques Vallée, had already considered correlations with planetary cycles. For my part, I wanted to check the effect of solar activity—the only one that, in my view, could plausibly have such a massive influence.

The effects of the Sun

The Sun has cycles of approximately 11 years, accompanied by solar flares that are not fully predictable. Beyond this 11-year cycle, other cycles are superimposed, in a rhythm sometimes described as “powers of two”—i.e., doubling each time: 22 years, 44 years, etc.

On these time scales, we know at least two kinds of solar effects:

• A psychosocial influence suggested by various studies—for example on suicide rates (Dood, Henry and Berk, 2006, Do ambient electromagnetic fields affect behavior? A demonstration of the relationship between geomagnetic storm activity and suicide) or on stock market activity (Theodore Modis, Sunspots, GDP and the stock market, 2007).
• More directly, an influence on plants—at polar latitudes—has also been observed: cellular degeneration caused by radiation.

>> But what relationship could there be between suicide rates (again!) and solar—or stock market—activity? It sounds crazy!

Less than it seems. The effect would be mediated by extremely low frequency (ELF) currents flowing in the Earth and driven by solar activity. In general, these currents may influence the nervous system and human emotions, although this remains poorly understood. And the stock market is, almost by nature, extremely sensitive to the emotional reactions of individuals.

Given that the first two hypotheses lacked usable data (1 and 2), I committed myself to the third hypothesis (3), searching for a possible relationship between solar activity and UFOs. This is a subject I explored on my site in 2010 by writing various articles about solar activity.

>> What did you find?

Well—nothing significant! But there was a surprise at the end.

I relied on worldwide observational data between 1946 and 2000—testimonies collected by Larry Hatch, one of the most comprehensive compilations I know of, with the advantage of being relatively homogeneous over time.

Within these data, I looked for identical frequency repeats—whether for solar activity or for UFO waves.

The distribution of observation waves

For this, I used different analysis methods (the most classic being the Fourier transform), but I also used an algorithm developed by Jacques Vallée in the 1980s. It had the advantage of being more sensitive than a Fourier transform, because it retains all the information initially contained in the data.

Fig. 5 — To measure the most significant frequencies, a program was used to identify the number of intervals (in weeks) between any two waves.

Table 2 — Only the 10 most frequently occurring time intervals, denoted [X_i], are shown below.

Δ Week	Xi	Power rank	Δ Waves
116	X1	3	v3–v2
161	X2	8	v3–v4
264	X3	2	v0–v2
379	X4	1	v0–v3
539	X5	5	v0–v4
992	X8	7	v3–v10
1099	X9	6	v0–v9
1372	X10	4	v0–v10
1882	X11	10	v3–v12
2261	X12	9	v0–v12

• Δ Week: time interval in weeks between two waves,
• X_i: name given to the interval,
• Power rank: ranking by intensity,
• Δ Waves: waves concerned.

The above intervals generally correspond to the elapsed time (measured in weeks, Δ Week) between the two strongest waves of observations (v0 and v3) and the other waves.

However, even if there is some synchronization on certain peaks with half-periods of solar activity, this was not sufficiently significant. Yet then I noticed something unexpected.

>> What was it?

While working on the most significant time intervals, I found that the time between certain waves was steadily increasing—roughly doubling each time: from 2.5 years to 5 years, then 10 years, then 20, then 40. This is a “power of 2” law.

More precisely, four out of the six intervals involving the first wave (v0, July 1947) were connected by an extremely precise mathematical law:

Table 3 — Four significant intervals (in weeks) and the corresponding dates. The “exponential” regression law that connects them is: Δ Week = 128.9 × 2.045^x.

x	Xn	v0–vi	Δ Week	Δ Years	vi (Year)
0	—	v0–v0	0	0	1947.51
1	X3	v0–v2	264	5.05954825	1952.57
2	X5	v0–v4	539	10.329911	1957.84
3	X9	v0–v9	1099	21.0622861	1968.55
4	X12	v0–v12	2261	43.3319644	1990.84

This entry is equivalent to: Δ Year = 2.045^x (difference in years). Coefficient of determination R² = 0.999992; p-value < 2 × 10^-6. This subject was mentioned in 2010 on U-Sphere.

>> Maybe it was just chance?

That was the key issue.

First, the correlation itself was extremely strong. With a value of “1”, we have a perfect correlation. Here, the residual error is on the order of 7 × 10^-6, corresponding to a pattern that should occur less than once in 50,000 under the tested null model.

But in addition, there were three other surprising points:

• This distribution allows us to recover v1 for x = 0. We then obtain, using v1, an adjusted equation even closer to a pure power of two: 2.005^x. The probability that a random distribution would also follow a progression so close to a power of two becomes infinitesimal. This is important—we will see why.
• This law also makes it possible to determine v3 for x = 1.5. The best approximation found is:

Fig. 6 — Best function found to compute v0, (v1), v2, v3, v4, v9, v12. Y-axis: difference in years.

• Finally, by shifting this same equation in time, we can connect the waves from v3 (cf. Table 2), although this is less significant because it relies on less regular x-values:

Fig. 7 — The same function makes it possible to compute v2, v3, v4, v8, v10, v12, with an offset in x.

>> Over 54 years of observations, finding a synchronous organization at the global scale is astonishing. What interpretations can we give?

Review of the proposed hypotheses

Based on the hypotheses mentioned above:

• Regarding a relationship with solar activity (passive exogenous hypothesis; cf. Fig. 1 (b2)), although there are disturbing parallels that do not rule it out, it seemed insufficiently significant.

• Regarding the psychosocial hypothesis (endogenous hypothesis; cf. Fig. 1 (a)), we have seen that while effects of crystallization and psychosocial contagion may occur during emotionally resonant events, the question raised by these results is entirely new: is human collective consciousness capable of generating not only joint events at certain times, but also events ordered in time according to a power law? To my knowledge, there is no study of psychosocial phenomena reproducing such ordered patterns. It would be entirely new.

• But above all, the supervised learning hypothesis is reinforced (active exogenous hypothesis; cf. Fig. 1 (b1)). Indeed, the repetition of an event with spacing that increases regularly over time—as observed for UFO waves—matches a well-known supervised learning technique: what some call “spaced retrieval”.

>> What is this “spaced retrieval” method?

It is a method of learning (retaining) as efficiently as possible.

We generally know that, in order to retain information—a lesson—it must be repeated several times.

But what is the optimal waiting time between repetitions? This remains fairly empirical, but one defended approach is to use our own tendency to forget. By measuring our forgetting rate, we can estimate how often information needs to be refreshed.

It appears that an efficient strategy is to double the time between each revision—which is precisely a power-of-two law (2^x, where x is the revision number). This principle is linked to the forgetting curve described by Hermann Ebbinghaus.

Fig. 8 — Some computer programs that help you memorize information, such as “SuperMemo”, calculate an ideal repetition interval between two reviews, based on your own abilities and on the difficulty of the material to be learned. The more abstract a subject is for an individual (i.e., the less it connects to other knowledge), the more quickly it is forgotten.

The key point is that this method can apply to both individual and collective learning. However, the more you widen the population base, with a communication channel of comparable breadth, the longer the interval between repetitions must be: it must account for the time required for information to disseminate through the social network and then be absorbed—i.e., its inertia. Individual-level repeats are measured in days, organizational-level repeats in weeks, and country-level repeats in years. But the same power law remains, with a scaling factor k: k × 2^x.

>> Still, supervised learning is hard to accept. Wouldn’t that imply an external agent—an intelligence—organizing these demonstrations and manipulating individuals?

That is the principle of supervised learning: it is led by an external supervisor who sets the tempo.

In any case, in 2010, when I approached these aspects, I had to admit it was useless to push conjectures much further: even if this hypothesis could be supported by an organized temporal distribution, it remained fragile.

But a few years later I found a radically different way to cross-check and validate this information.

Study on spatial data

>> What did you do from 2010 onward?

I focused on spatial data. As I said, by logical deduction we assume that in many cases “something must tie the phenomena to the environment”. The objective was to verify this mathematically: “Could a relationship emerge between the locations of phenomena of unknown origin (type D) and certain environmental characteristics?”

I had made good progress in previous years, having developed a mapping program to cross environmental data, and I was obtaining results with respect to population density. However, I was not satisfied with the mathematical method I was using at the time: it consisted of dividing territory into small rectangular surface elements. Depending on the observation scale, results varied. I had to use smoothing methods, which I had begun to do.

Rather than reinventing the wheel, I turned to a mathematics lab specializing in spatial data processing in Toulouse (TSE), with the support of CNES/GEIPAN, which kindly took up this challenge.

>> What data did you use for this study? The “environment” is a vast notion!

Yes. I had several types of data in mind (what we call “variables”):

• First, variables that could constitute known—or at least expected—biases in testimony:
  • Population density: more observers should mean more testimonies. But how many? It was interesting to measure the exact degree of correspondence between population density and testimony intensity.
  • Sunshine: a clear, sunny sky may encourage people to be outside—and thus increase opportunities for observation.
  • Airports: more activity in the sky (moving lights) could generate “false positives” that should not be classified as PAN D. We also wanted to measure that.
• Second, more general variables describing the nature of the environment—two of which seemed to recur at times in PAN D observations:
  • Freshwater or marshy areas,
  • Forests.
• Finally—and more recently—following the approach defended for years on U-Sphere: variables related to environmental risks likely to cause significant and lasting disruptions and to have a serious impact on the planet’s future. These variables are mapped and monitored globally by international organizations. For mainland France (the subject of the study), we retained risks essentially of human origin (serious natural risks such as volcanoes or seismic zones being too poorly represented):
  • Polluted sites,
  • Nuclear activity as a whole (not only nuclear power plants).

For PAN D data, we used cases from the National Centre for Space Studies (CNES), GEIPAN: 380 phenomena classified “D” over a period of 40 years. These data have the advantage of being homogeneous in space: GEIPAN is a national-level one-stop shop and does not favor one region over another.

>> In a nutshell, what methodology did you use?

These environmental variables had to be compared with the distribution of UAP D in order to measure their degree of correlation—i.e., whether they were likely to correspond to the distribution of type D phenomena.

Moreover, the objective was not to compare variables one by one, but to consider them together, in order to bring out their intrinsic ability to explain the PAN D distribution.

Indeed, if one variable is entirely explained by the distribution of another, the former should not appear significant.

>> So—your results?

Astonishing.

For the first time, we obtained an objective measure of the relationship between PAN D and the environment—especially with nuclear sites, so dear to ufologists.

It was all the more interesting because it was based on a formal demonstration.

And above all, it was not just nuclear sites: polluted sites were also involved. This reinforced the “environmentalist” hypothesis I had sought to defend for years. The contribution of each variable to the distribution of PAN D is indicated in the table below by its p-value.

Table 4 — List of variables and their correlation level with PAN D.

Variable	p-value	Interpretation
Population	< 10-16	Very highly significant
Nuclear	< 0.0001	Highly significant
Pollution	< 0.004	Very significant
Water	< 0.069	Not significant
Forests	< 0.15	Not significant
Airports	< 0.17	Not significant
Sun	< 0.31	Not significant
PAN A	< 0.43	Not significant

Of course, the method can always be criticized, but we were able to lay the foundations for an analysis methodology, and today there is a concrete basis for discussing the validity of these results.

>> At the same time, you know that correlation does not necessarily mean a “cause-and-effect” relationship. There may be hidden variables you did not identify. For example, could there be real effects on people living near polluted or nuclear sites—linked to chemicals?

Perhaps.

But note that, even if they are not perfect, CNES investigations have never demonstrated such a link: UAPs are classified “D” only after exhausting all known hypotheses.

Moreover, at the scientific level, there is currently no known information suggesting that, around nuclear-industry sites, people are more likely to experience hallucinatory delusions than elsewhere. That does not mean the avenue should not be explored, but at this stage it seems even more fragile than, for example, hypotheses related to individuals who identify as electrohypersensitive.

>> And why not simply psychosocial causes? Perhaps these are regions where people are sensitized by the presence of infrastructures or sites that generate concern, creating a ripple effect. How can we tell whether manifestations are not provoked by an over-reaction of the population?

This is why we decided to check whether explained phenomena—PAN A—could also constitute an explanatory variable for the distribution of PAN D.

Let me explain: when a witness decides to report an observation, they do not know, a priori, how it will be classified by the CNES investigator. However, if there were regions where populations were “psychologically more sensitive”, favoring testimonies, there should be not only more PAN D but also more explainable PAN A/B/C—especially if reports were driven by an ambient form of paranoia. That is why we tested whether the distribution of PAN A followed that of PAN D.

The result, shown in the table above, is eloquent: there is no correlation between the distribution of PAN A and PAN D (p < 0.43). This allows us to rule out psychosocial factors endogenous to the observations—that is, originating within the population.

Astonishing.

For the first time, we obtained an objective measure of the relationship between PAN D and the environment—especially with nuclear sites, so dear to ufologists.

It was all the more interesting because it was based on a formal demonstration.

And above all, it was not just nuclear sites: polluted sites were also involved. This reinforced the “environmentalist” hypothesis I had sought to defend for years. The contribution of each variable to the distribution of PAN D is indicated in the table below by its p-value.

Table 4 — List of variables and their correlation level with PAN D.

Variable	p-value	Interpretation
Population	< 10-16	Very highly significant
Nuclear	< 0.0001	Highly significant
Pollution	< 0.004	Very significant
Water	< 0.069	Not significant
Forests	< 0.15	Not significant
Airports	< 0.17	Not significant
Sun	< 0.31	Not significant
PAN A	< 0.43	Not significant

Of course, the method can always be criticized, but we were able to lay the foundations for an analysis methodology, and today there is a concrete basis for discussing the validity of these results.

>> At the same time, you know that correlation does not necessarily mean a “cause-and-effect” relationship. There may be hidden variables you did not identify. For example, could there be real effects on people living near polluted or nuclear sites—linked to chemicals?

Perhaps.

But note that, even if they are not perfect, CNES investigations have never demonstrated such a link: UAPs are classified “D” only after exhausting all known hypotheses.

Moreover, at the scientific level, there is currently no known information suggesting that, around nuclear-industry sites, people are more likely to experience hallucinatory delusions than elsewhere. That does not mean the avenue should not be explored, but at this stage it seems even more fragile than, for example, hypotheses related to individuals who identify as electrohypersensitive.

>> And why not simply psychosocial causes? Perhaps these are regions where people are sensitized by the presence of infrastructures or sites that generate concern, creating a ripple effect. How can we tell whether manifestations are not provoked by an over-reaction of the population?

This is why we decided to check whether explained phenomena—PAN A—could also constitute an explanatory variable for the distribution of PAN D.

Let me explain: when a witness decides to report an observation, they do not know, a priori, how it will be classified by the CNES investigator. However, if there were regions where populations were “psychologically more sensitive”, favoring testimonies, there should be not only more PAN D but also more explainable PAN A/B/C—especially if reports were driven by an ambient form of paranoia. That is why we tested whether the distribution of PAN A followed that of PAN D.

The result, shown in the table above, is eloquent: there is no correlation between the distribution of PAN A and PAN D (p < 0.43). This allows us to rule out psychosocial factors endogenous to the observations—that is, originating within the population.

Yes, of course. I am thinking of two categories of people:

• Those from popular, traditionalist circles—often more religious—which constitute about 25% of the French population. These populations are more resistant to outsiders and are less used to being in contact with other ideas. The “UFO” subject is rather frowned upon. Among the people whose testimonies are collected at GEIPAN, it is those from these circles who are most afraid of ridicule and rejection by their peers, and who generally ask us for absolute anonymity. They do not like to testify—contrary to what is often imagined.

• Paradoxically, while education tends to increase openness, there is also a notable exception among some scientists in experimental (“hard”) sciences, who are supposed to explain how the world and the universe work. Faced with the UFO phenomenon, some of these so-called “rationalists” want an answer at all costs. Their explanatory power over the world is Science—even if it means forgetting its limits and those of reason. This is a dogmatic drift of science and a diversion of the critical method in favor of a rampant skepticism that destroys any information that does not fit within their framework of thought. Note that this population is not statistically significant: it represents less than 1.4% of the total population.

>> Okay. But in the end, what social variable do you identify? This still seems quite varied.

Well—less than you might think. If we set aside the last category (not very representative), it turns out that the Front National vote covers these categories rather well.

>> Are you serious? The UFO subject is already controversial—if you add politics on top of it, you won’t calm the debate!

This is about staying factual. It turns out that the Front National vote is indeed a cultural marker associated with working-class circles, and electoral sociology studies show that it is very strongly correlated with a low level of education—a sensitive subject that is not well known to the public.

Ultimately, with precise, territory-wide data, after verification, the p-value found was even better than for nuclear activity. It will, moreover, be the subject of a future study.

Fig. 11 — Comparison of the distribution of the FN vote with the distribution of the model residuals.

>> I’m stunned. This is still shocking—especially for a topic already struggling for credibility…

Be careful: this is not a value judgment. The FN vote is also a protest vote reflecting the failure of education and integration policies. It is measured as territorial averages, which should never be interpreted individually: you can always find an individual close to FN ideas who likes to talk about UFOs.

And the “National Front” variable is not ideal either: what is interesting are certain determinants within that population—cultural fundamentals that can be read through nationalisms. Moreover, we find similar traits among witnesses of Marian apparitions: generally people from extremely modest and rural backgrounds.

>> I do see on your maps a gap with Brittany and the Basque Country.

Yes—because their traditions do not bind them to the National Front.

>> Why?

The Front National is also the result of a popular defensive reaction of local cultures in the face of immigration waves at the beginning of the 20th century, which affected the Mediterranean basin and northern France. There were processes of diffusion and cultural blending spanning several generations.

Brittany and the Basque Country have been relatively preserved, and they also vote less FN: they are strong cultures, but not anchored in a national identity in the same way.

In truth, there is no ideal variable to represent traditionalist cultural identity in France associated with a low level of education. The FN variable is a good approximation—and it fits the supervised learning interpretation well.

>> And you’ve come full circle—finding structured and targeted learning in the spatial dimension?

Absolutely—which was fascinating. What is more, this learning appeared to be driven externally (supervision), independently of individuals’ will, given the lack of relationship with the distribution of PAN A. There would be a maximization of effects and actions, both in space—across territory—and in time, revealed by two completely independent calculation approaches.

Implications

>> What are the possible consequences and interpretations of these results? Under the supervised learning hypothesis, how do you understand the purpose of potential “supervisors”?

As we have seen, this is based on targeting values in order to advance certain subjects within the population.

It sounds like an educational program—perhaps even psychosocial manipulation (one could argue that any form of education is a form of manipulation). The supervising system “injects” information gradually into the territory while remaining below a threshold of “detectability”, thanks to communication in peer-to-peer mode: addressing only small numbers of people and letting information propagate from them.

In a way, this resembles a form of “vaccination” of the human social body, so that the immune system can eventually accept these values/subjects/notions.

Society does not naturally accept this information—perceived as aberrant—and develops resistance. These resistances manifest in various ways at both individual and collective levels: “intellectual blindness”, mockery, rejection. We see exactly the same symptoms as in change management.

Once UFO testimonies are disseminated and integrated by the human social body, they are appropriated and taken up in culture in different forms—concepts and ideas.

>> But given what you said earlier, there is also an environmental—or even ecological—targeting by the phenomenon?

Yes. As I said in the introduction, this can be approached by asking: “What could interest the human of the future?”

After millions of years of evolution, we have become what we are today: a conscious human species—sapiens sapiens.

However, we remain a fragile product on the scale of the universe, exposed to risks we help create.

The survival of our evolutionary path—at least in the short term—still depends on protecting the ecosystems that enabled this extraordinary emergence. This is reflected in the monitoring of environmental risks: at the planetary level, we seek to monitor hazards in order to anticipate and control them. And this surveillance—progressively improving—extends to increasingly vast scales of time and space.

>> Us—and… the others?

Indeed. It is also the question of developing collective intelligence in a network.

Protecting intelligence and environmental wealth—and perhaps also stimulating it wherever it may emerge—are and will probably always remain among our challenges as a species.

The stakes for future progress likely lie in our ability to bring together the diverse peoples of Earth to collectively resolve the global challenges ahead. As progress is made, peoples master increasingly vast scales of time and space; these scales overlap, necessarily interconnect, and confront shared problems.

With other humans, if we sometimes inhabit the same territory, we necessarily inhabit the same planet. By extension, we may also cohabit within the galaxy with other intelligences—and then we will have to share this space in good understanding.

>> So one of the objectives of these supervisors would be to develop this collective intelligence?

Yes. If we reason beyond the individual, developing collective intelligence means creating wealth by linking societies—and, more broadly, civilizations—so that they can share the best of themselves. In systems thinking, we sometimes say that the whole is greater than the sum of its parts.

Generally speaking, the civilizations of the future will become what I call “Gardeners of the Universe”. Intervening on increasingly vast scales of time and space, they will help develop collective intelligence, seeking to plant seeds and stimulate evolution around them.

>> How do you imagine these “gardeners” operating on Earth?

When appropriate, by pursuing two types of objectives:

• Objective 1: Protect intelligence on planets by alerting it to risks, without violating societies’ self-determinism. Prioritize alerting over intervention, by sending relatively ostentatious messages to decision-makers (those with the capacity to act), so that they question their responsibilities—without jeopardizing Objective 2.

• Objective 2: Develop collective intelligence by gradually preparing contact with other civilizations, before even considering cooperation.

>> Practically speaking?

By creating communication bridges between civilizations—neither too wide nor too narrow—in order to preserve each culture’s specificities. This work is carried out over several human generations, so that everyone can represent themselves and address the other without importing symbols or concepts wholesale.

>> Why focus on preserving cultural specificities? Is cultural identity really that important?

In truth, it is our only wealth. Culture is what we have to share with other civilizations: our way of understanding nature, perceiving the environment and the universe. On Earth, each culture has uniquely appropriated its environment, shaped objects, and created words, languages, ideas—things that only make sense in the places and times that gave birth to them.

This is not the case with our technique or our science, which will inevitably be (re)discovered by other civilizations. Technology and science can even constitute risks for societies that do not have the ethical or moral structures to circumvent their dangers.

Ultimately, each culture is the result of a patient construction—a balance between humans and nature—developed over hundreds or thousands of years through trial, error, and search. This makes a culture non-transferable: it is born, flourishes, and lives within a given social and environmental space.

And that is—regardless of our level of evolution—what we have to contribute to other civilizations: the perspective that our culture gives us on the world, on the universe.

Cultures can be seen as ecosystems that must be preserved. Respecting their development means respecting their art, ways of life, and symbolic tools.

This brings us to the notion of “cultural ethnocide” developed by sociologist Robert Jaulin in the 1970s.

>> Meaning?

A culture that is too fragile—unprepared for the shock of meeting another—could be destroyed. Even without conflict, an unprepared culture could be seduced by another’s technological advance and import cultural objects that would destabilize its way of life, traditions, and more broadly its relationship to the environment.

Yet, if the goal is to develop a greater collective intelligence, it is essential that each civilization retains its specificities—its cultural identity—so it can share its gaze with others.

>> So, to summarize: Objective 2 would be to develop collective intelligence by bringing different cultures into contact. That contact would require a preparation phase—cultural awareness—through supervised learning.

Exactly. And still in a logic of “energy savings”, Objective 2 would be linked to Objective 1 as early as possible.

>> Applied to UFOs—how would this preparation phase unfold?

In this context, UFO appearances are a pretext to introduce concepts about extraterrestrial intelligences—to learn to think “the other” with our own words.

Moreover, UFO testimonies sometimes resemble a staged play, describing absurd scenarios set up for the sole purpose of being seen by single witnesses.

For example, in the Valensole case, imagining two extraterrestrials from the depths of the universe stepping out of their craft, crouching to look at a lavender plant, and then leaving, seems completely absurd.

It makes sense if we understand that, under the supervised learning hypothesis, the images that must be reflected back are purely imaginary: they are fictional scenarios that do not represent the “supervisors’” reality, but only a cardboard reality credible enough to impress witnesses.

UFO appearances, in general, remain based on the human archetypes of the target culture: projections from human fantasies and elements of human collective consciousness. In theory, if successful, they can even be maintained and extended by that collective consciousness.

The objective is not to show what the other (e.g., an extraterrestrial) really is, but to awaken consciousness—to learn to think of the other by extending our own symbols. And each new symbolic tool created by humans from these observations will eventually be reused in later observations.

Note that this work on consciousness is also driven by the progress of scientific thought, alongside philosophy. We see it in the new notions manipulated by scientists: exoplanets, habitable zone, panspermia, Earth similarity index, exobiology, extraterrestrial life, etc.

>> If apparitions remain based on archetypes, it becomes difficult to disentangle this from the psychosocial hypothesis. It’s inextricable, isn’t it?

Indeed, if this integration of concepts is carried out optimally, it can become close to an activity of human collective consciousness emerging in the form of delusions or hallucinations.

If this precaution is not taken for PAN A, the reaction of human collective consciousness could be mistaken for material “UFO” activity—real (PAN D).

>> How would these resurgences of human collective consciousness occur?

These modes of expression remain to be demonstrated. Nevertheless, we can suppose that they might crystallize in and around psychologically sensitive individuals. Phenomena may be individually and/or collectively experienced by witnesses in the form of hypnotic trances.

Whether they are resonance phenomena (as we have seen for suicides or mass crimes), they can manifest as testimonies of neutral or positive “appearances” (lights, etc.) taking up classic UFO themes.

Or, conversely, as dissonance phenomena (neuroses/rejection): testimonies of negative, traumatic appearances—such as sleep paralysis or “abductions” (kidnappings by aliens). Local cultures can crystallize the phenomenon based on elements of their traditions.

It is generally admitted that such phenomena can originate in trauma or in people with particular sensitivity. This results in a mental hold on the subject(s): altered states of consciousness—trance, hypnotic or semi-hypnotic states, hallucinatory sleep that can extend to those around them.

However, not all phenomena can be reduced to the sociopsychological thesis given the material aspects reported in some UFO sightings. To this we can add the time-ordered structure of the phenomenon: to our knowledge, there is no sociopsychological phenomenon capable of being ordered in this way.

>> Finally, back to our hypothesis of a supervising intelligence: the contact with it—since that is what we are talking about—when would it happen?

In spaced learning theory, it is often considered that after five repetitions, “ordinary” knowledge becomes stabilized. According to the previous models, the next wave (the fifth) belonging to the initial cycle would occur between late October and November 2035.

Under the supervised learning theory, the learning period would then be over: there would be actual “contact”, and the beginning of regular communication with our supervisors—whoever they are.

>> A concluding word?

I would like to thank all those who helped me and contributed directly or indirectly to deciphering these data—and, more broadly, all those who have supported me over the past years.

References

Synoptic diagram

Logical diagram describing the article and the research framework (click to zoom) ```