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Upcoming Talk: What Psychologists & Quantum Physicists Can Teach Each Other

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By Doug Marman

I will be giving a talk at a university in Toronto on Friday, October 5 at 2:00 PM – 3:00 PM, EDT, at York University, 4700 Keele Street, Toronto, ON, Toronto, Ontario M3J 1P3. The public is welcome to attend.

You can find more information at these links:
Facebook, Meetup, The Hidden Teachings of Rumi webpage

Here is an overview of what I will be talking about:

For the last 100 years, psychologists have been moving toward a more scientific approach, to find principles that can be established on the firm ground of objectivity. At the same time, quantum physicists have been turning the foundations of physics in exactly the opposite direction, toward the realization that objectivity is impossible when observing quantum behavior; that “forces” do not force particles, they only influence them; and that it is quantum entanglement between particles and the environment that create the appearance of a solid objective reality.

Psychology can learn important lessons from these quantum discoveries. For example, it offers new insights into the recent “replication crisis” in psychology experiments by showing that there is a direct relationship between the replication problem and the “measurement problem” in quantum physics. I recently published an interpretation of quantum mechanics that also suggests the possibility that subatomic particles may behave so strangely because they possess an element of sentience, and all of the strangest aspects of quantum mechanics can be explained by this sentience. This new interpretation predicts that quantum behavior should also be present whenever relationships form between sentient agents, including organisms and human beings. If this is true, then psychology will never become a hard science like classical physics because there are too many quantum effects involved in human perception and experience.

At the same time, psychology has lessons it can teach physics. Over the last century, physicists have failed to find a way to understand the quantum mystery. Perceptual “sets” and “schemas” offer insights that open the door to a deeper understanding. The scientific lens of perception comes from schemas learned from centuries of studying mechanisms and reactions to forces. This is why the principle of objectivity became the foundation of science at the same time as the Industrial Revolution took off. But this lens of perception has not been able to solve the paradoxes of quantum mechanics, the mystery of what makes organisms alive, or the enigma of consciousness. An understanding of perceptual sets can play a role in expanding the reach of quantum physics, especially when it gives us insights into why quantum relationships between sentient quanta should indeed create forces of attraction and repulsion, as physicists have learned.

If have questions, comments, feedback, or would just like to engage in dialogue on this subject, feel free to start the discussion below.

Science Paper Published: The Lenses of Perception Interpretation of Quantum Mechanics

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By Doug Marman

A paper I wrote for the peer reviewed Integral Review Journal was just published. You can read the paper here: http://integral-review.org/current_issue/vol-14-no-1-aug-2018/

This paper is a formal scientific paper that I have been working on for two years. I have tried to write it to be understandable to anyone who enjoys science and knows something about quantum physics. If you have read my book, Lenses of Perception, you will see that this paper presents the same ideas in a more formal and more thorough scientific manner.

The Editor-in-Chief of Integral Review Journal, Jonathan Reams, introduces my paper with these comments:

40 years ago I began my university education studying physics, but dropped out and later turned to studying consciousness (and leadership). Along the way I have encountered numerous perspectives on the relationship between the two subjects, with a polarity in perspectives, from materialist interpretations to idealist ones. This conversation continues today, being taken more and more seriously as it becomes apparent that we cannot ignore an integral view of the intimately intertwined nature of consciousness and matter. The science magazine Nature recently highlighted this as an ongoing conundrum (see article here). An example of an integrative perspective comes in the notion of panpsychism, that consciousness is a fundamental feature of physical matter, which is being taken seriously by a wider range of mainstream physicists and others (see article here). All of this leads into the territory IR has always been intended to serve as a platform for new thinking from an integral view.

Thus we fittingly begin this issue with Doug Marman’s The Lenses of Perception Interpretation of Quantum Mechanics. At IR, we are always on the lookout for new thought and Marman delivers on this. His article is a substantive piece of investigation into some of the most fundamental questions science has ever tried to answer. In true transdisciplinary fashion, Marman covers a wide range of disciplinary knowledge. He begins by showing similarities between quanta and living organisms, leading to an inescapable predication that quantum behaviour is driven by sentience. This leads naturally into a detailed examination of consciousness itself and how participation is a creative process of perception…. Marman then lays out a set of nine postulates that lay a more formal foundation to show how his Lenses of Perception interpretation can address a wide ranging and essential set of issues generally held as necessary for any theory to be able to bring coherence to our understanding of all physical processes. Having done this, an examination of quantum formalism and how the LoP interpretation (using first, second and third person lenses) not only meets the tests of quantum formalism, but even shows why the second person lens of relationship is necessary for understanding it. Finally, Marman lays out how his LoP interpretation meets a variety of challenges, including the five unsolved problems of physics, and points to ways to test out this interpretation. The overall scope, depth, breadth and rigor of Marman’s work makes this article a seminal contribution to discourse around these fundamental questions, and IR is pleased to publish it here.

If you have any technical questions, comments, feedback, or if you are interested in dialogue over any of the issues raised in my paper, please feel free to start the discussion below.

The Fallacy of Complexity

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By Doug Marman

Even the simplest organisms are amazingly complicated. This is why scientists who focus on the origin of life often study complexity. They try to find ways that intricate patterns can emerge from simple algorithms. They hope that this will give us clues on how cellular life evolved. This is a fallacy.

The mistake comes from confusing complexity, in general, with the specific kind of intricacies we find in living things. There is so much vague thinking about this subject that many scientists think that generating any kind of complexity can help solve the mystery of life. Countless hours have been wasted on this pursuit.

Professor Sharon Glotzer talks with some engineering students. Photo from University of Michigan.

A recent article raises this issue again. “A ‘Digital Alchemist’ Unravels the Mysteries of Complexity” describes the fascinating work of Sharon Glotzer and her 33-person team, at the University of Michigan.

Glotzer uses computer simulations to study emergence — the phenomenon whereby simple objects give rise to surprising collective behaviors. “When flocks of starlings make these incredible patterns in the sky that look like they’re not even real, the way they’re changing constantly — people have been seeing those patterns since people were on the planet,” she said. “But only recently have scientists started to ask the question, how do they do that? How are the birds communicating so that it seems like they’re all following a blueprint?”[1]

Glotzer specializes in the way inert shapes can naturally align to create surprisingly complex patterns.

For example, if you have a room full of spheres, all the same size, they will naturally assemble into a simple lattice pattern. You only need to shake them gently and they will fall into this simple repeating pattern. What Glotzer discovered is that if you start with other shapes, such as pyramids, made from triangles on all sides, they produce quasi-crystalline patterns that never repeat. Simple shapes can produce surprisingly complex patterns.

Glotzer sees this as a potential new insight into the origin of life. She said:

Most scientists think that to have order you need chemical bonds — you need interactions. And we’ve shown that you don’t. You can just have objects that, if you just confine them enough, can self-organize… So it’s a completely different way to think about life and increasing complexity… I know because I’ve done this, that I can take a bunch of objects and put them in a little droplet and shrink the droplet a little, and these objects will spontaneously organize. So maybe that phenomenon is important in the origin of life, and I don’t think that’s been considered.

This insight about the patterns created by different shapes is valuable for the work that Glotzer does: creating new materials through molecular engineering. Unfortunately, it isn’t going to helps us solve the mystery of the origin of life because it displays the wrong kind of complexity.

This simple mistake happens far too often. It is time to kill this fallacy.

The reason that even smart scientists fall for this error is that they really don’t understand organic life. They can’t explain how even the simplest cells survive. Physics and chemistry don’t give us the tools needed to illuminate the secret of life.

What happens when we face something unknown, something we don’t understand? We naturally compare it to things that we know. That is why scientists keep trying to see if mechanical reactions can explain life.

Unfortunately, this doesn’t help, for a simple reason: Life is complicated in a special way that machines can’t achieve. Once you see this, you will realize why all of the games with computer algorithms, looking for ways to create complexity, are a waste of time.

To understand this, let’s start with one of the best introductions to this problem and how it relates to the origin of life. In Richard Dawkin’s book, “The Blind Watchmaker,” he asks:

So, what is a complex thing? How should we recognize it? In what sense is it true to say that a watch or an airliner or an earwig or a person is complex, but the moon is simple?[2]

Dawkins takes us down this path to show that we have to throw away many of the simplest ideas about complexity if we want to get at what really matters. For example, the moon is simple because it is one homogeneous thing, like a bowl of milk or the endless sands in the Sahara desert. Dawkins suggests that we need a system with many different elements. That is the kind of complication we are looking for.

However, this isn’t enough. A mountain, like Mont Blanc, is made up of many different types of rocks. And every area of Mont Blanc is truly unique and distinct from every other, making it far from simple. But this doesn’t resemble the patterns we find in organisms.

Mont Blanc, the highest mountain in the Alps. Photo from Wikipedia.

He then asks if we can get closer to the mystery of life by looking at probabilities. What if we say something is complex only if it has an arrangement of many different elements in a way that is highly improbable?

[I]f you take the parts of an airliner and jumble them up at random, the likelihood that you would happen to assemble a working Boeing is vanishingly small. There are billions of possible ways of putting together the bits of an airliner, and only one, or very few, of them would actually be an airliner. There are even more ways of putting together the scrambled parts of a human.

This approach to a definition of complexity is promising, but something more is still needed. There are billions of ways of throwing together the bits of Mont Blanc, it might be said, and only one of them is Mont Blanc. So what is it that makes the airliner and the human complicated, if Mont Blanc is simple?[3]

In other words, the complexity we are looking for can’t be found by just throwing things together. We need to see something more than just an accumulation of parts.

This shows why Glotzer’s discovery is not going to help. She researches the results of tossing things together. Yes, they can make amazing patterns that never repeat, which are fascinating, but it is still just a pile of parts. By itself, this pile doesn’t do anything special.

Therefore, it isn’t the improbability of a non-repeating pattern that we are looking for. We need something more. As Dawkins says:

If we see a plane in the air we can be sure that it was not assembled by randomly throwing scrap metal together…[4]

Intentional flight requires a different type of complexity. A plane allows people to travel around the world. That is what jumps out at us. Jets can’t be created by just throwing things together and hoping that something special is going to emerge.

But this is where I part ways with Richard Dawkins, because even this isn’t the kind of complexity we are looking for in living creatures. Why? Because planes are designed and constructed by human beings from a plan, from a blueprint. On the other hand, multicellular creatures, such as animals, fish, even trees and plants, develop from single cells, into complex bodies, made up of many organs that work intricately with each other. We don’t see the same thing in even the most sophisticated machines.

Can we explain the difference between the complexity of machines and organisms? Let’s look.

Planes don’t grow from seeds. That’s one difference. Here is another, plants and animals are not assembled by outsiders.

Airliners don’t seek for food or fuel on their own, while creatures are able to overcome incredible obstacles to find nutrition. Jets don’t develop unique ways of defending themselves from predators. And planes don’t reproduce by mating with other aircraft, or by dividing into two.

Organisms clearly show us a different kind of complexity than machines. Scientists keep trying to treat creatures as if they are sophisticated machines, but the metaphor fails in important ways. For example, biologists have been forced to abandon the old idea that DNA contains a blueprint for constructing the body of animals. It simply doesn’t work.

When DNA was first discovered, biologists expected to find one gene for every protein and enzyme needed in the human body. Once they mapped the whole genome, however, they found that there aren’t even close to enough genes to pull this off.

Every gene is involved in multiple roles. They also need to work with countless other genes. Many times, parts of one gene are used with parts from another, to get what is needed. And genes are turned on and off from outside the DNA.

Look at trees. They don’t follow a blueprint or a plan. That’s why the branches, leaves, and seeds emerge spontaneously at different places, making each tree unique. The blueprint idea simply doesn’t work as an explanation. This is one of the many failed attempts to compare living things to machines.

So we need to find a different kind of complexity than we see in machines. How do we describe this difference? Here is one way: You can’t take a creature apart to study how all of its organs and cells work together. If you try to do this, you will kill it.

That leads us to an even bigger difference: If a bird dies, it can no longer fly or search for food. Its body is just as complex as it was the moment before it died, but now it no longer hops on its feet, flaps its wings, or sings.

Robert Rosen’s description of complexity brings us closer to the mystery of life that we are searching for: A living organism is a system that cannot be fully explained by reducing it to its parts because it can only live when its parts work in a relationship with each other as a whole.

Rosen puts it this way:

It has turned out that, in order to be in a position to say what life is, we must spend a great deal of time in understanding what life is not. Thus, I will be spending a great deal of time with mechanisms and machines, ultimately to reject them, and replace them with something else. This is in fact the most radical step I shall take, because for the past three centuries, ideas of mechanism and machine have constituted the very essence of the adjective ‘scientific’; a rejection of them thus seems like a rejection of science itself.

But this turns out to be only a prejudice, and like all prejudices, it has disastrous consequences. In the present case, it makes the question ‘What is life?’ unanswerable; the initial presupposition that we are dealing with mechanism already excludes most of what we need to arrive at an answer. No amount of refinement or subtlety within the world of mechanism can avail; once we are in that world, what we need is already gone.[5]

This helps us see the enigma of life more clearly. This is the puzzle we need to solve. Now that we understand the mystery we are up against, it is easy to see why most discussions about complexity and the origin of life completely miss the point. Complex mechanisms and chemical reactions are not enough. Even random events won’t help because the puzzle we need to solve is to explain what makes living things alive.

No one has found a mixture of chemicals that alters its course, avoids threats, or replenishes itself. Chemical reactions simply stop when the energy driving them runs out. Then where does the remarkable desire for life come from?

A crystal, a candle flame, a hurricane, or a Bénard cell does not seek resources when the material conditions for continued catalysis runs out; they cease. Living things do so until all options are exhausted. Some of the simplest organisms engage in surprisingly elaborate behaviors to forestall cessation.[6]

How did a self-organizing, autocatalytic chemical system come to persist in such a way that it could be described as self-preserving…? We do not know. Moreover, we do not appear to be overly concerned that we do not know. The answer cannot be, it just did.[7]

One way to make this point even clearer is by distinguishing between “self-ordering” systems and the kind of organization that we see in living organisms, where cells and organs form responsive relationships, as they work with each other toward a common goal.

Self-ordering should not be confused with self-organization.[8]

A flame on a candle, the vortex that forms in tornados and hurricanes, and crystalline shapes are all examples of self-ordering. They are all the result of physical dynamics that can be explained with physics and chemistry.

No truly sophisticated function has ever arisen from self-ordered states.[9]

Living organizations are different. They require relationships between responsive life forms. For example, human beings work together for a common purpose. Cells and organs work together as a whole. And flocks of starlings fly together as a group. These types of living organizations can’t be explained by simple cause and effect mechanisms or principles of chemistry.

Swarm of starlings. Photo from Wikipedia.

What Glotzer is talking about is clearly self-ordering, not self-organizing. Glotzer’s work is fascinating, but there is no great mystery in the way objects self-order and arrange themselves. This isn’t going to help us solve the enigma of life. Even a well-planned blueprint isn’t enough.

Living organizations and living organisms have a special form of complexity that can never be fully understood by taking them apart.

[1] Natalie Wolchover quotes Sharon Glotzer, “A ‘Digital Alchemist’ Unravels the Mysteries of Complexity,” Quanta Magazine, March 8, 2017.

[2] Richard Dawkins, The Blind Watchmaker (New York: W. W. Norton & Company, 1986), p. 6.

[3] Richard Dawkins, The Blind Watchmaker (New York: W. W. Norton & Company, 1986), p. 7.

[4] Richard Dawkins, The Blind Watchmaker (New York: W. W. Norton & Company, 1986), p. 8.

[5] Robert Rosen, Life Itself: A Comprehensive Inquiry into the Nature, Origin, and Fabrication of Life (New York: Columbia University Press, 1991), p. xv-xvi.

[6] Lyon, “To Be or Not To Be: Where Is Self-Preservation in Evolutionary Theory?” Major Transitions, p. 106.

[7] Ibid., p. 122.

[8] Abel DL, Trevors JT. Self-Organization vs. Self-Ordering events in life-origin models. Physics of Life Reviews. 2006;3, page 211. Also available from http://lifeorigin.academia.edu/DrDavidLAbel.

[9] Abel, DL. Life Origin, A Scientific Approach, edited for the non-scientist. Available from http://lifeorigin.info/whats-the-difference-between-self-ordering-and-self-organizing.html – _ENREF_21

The Reproducibility Crisis of Psychology and What It Is Trying to Tell Us

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By Doug Marman

Over the last few years, a raging crisis has hit the field of psychology: Most published studies can’t be replicated by others. For example, 100 experiments published by highly respected psychology journals were recently tested and only 36% produced results in agreement with the original reports.[1] This is called the “reproducibility crisis.”

It’s a complicated problem. It isn’t caused by fraud, except in rare cases. Many factors are involved, as explained by this article. For example, designing psychology experiments is more difficult than it sounds, and drawing conclusions often involves complex statistical analysis. Even the experiments aimed at reproducing experiments have been found wanting.[2]

This has created a rift among psychologists, with half saying that the problem is more about the way reproducibility tests are run, with the other half feeling “the academic ground give up beneath their feet.” This led one reporter to ask:

“Crisis or not, if we end up with a more rigorous approach to science, and more confidence in what it tells us, surely that is a good thing?”[3]

No, I don’t think that is the answer. In fact, I believe it will make the reproducibility problem worse. The rigorous approach of traditional science is part of the problem. It is time to put a spotlight on how objectivity can interfere with psychology experiments. Otherwise, we are going to continue casting doubt on valid scientific experiments.

Take, for example, an experiment that is literally a textbook case:[4] In the 1980s, Fritz Strack and his co-workers showed that when a person smiles, it improves their mood. Many well-known psychologists, such as William James, and scientists, such as Charles Darwin, have said that expressions create emotions. It makes sense. The challenge was how to design an experiment that scientifically verifies this.

You can’t just ask people to smile, because that automatically makes them conscious of what they’re doing. That will invalidate the results. Strack and his co-workers needed to find a way to get people to move their mouths into a smile, or a pout, without them knowing what they were doing. They found an ingenious solution.

When they asked people to hold a pen in their mouths, with their mouths closed, they automatically moved their faces into a sort of pout. When they asked another group to hold a pen between their teeth without closing their lips, they naturally formed a smile. The subjects had no idea what the test was really about. They were told that the experiment was studying people trying to do two things at the same time. They needed to hold the pen in their mouths while evaluating a series of Far Side cartoons.

Images from an experiment that tested the influence of smiling versus pouting.

The results showed that the group with smiles found the cartoons funnier than the group who was pouting. In other words, just putting your face into a smile naturally brightens your day.

The experiment has been verified countless times over the last twenty-five years, by many researchers. Some have expanded and tested the idea in new ways, besides smiles and pouts, and found similar results. For example, if you take a confident stance, in front of a group, you feel more confident.

So, Strack volunteered to have his classic study be tested by a team of researchers who wanted to reproduce psychology experiments. He wasn’t concerned. It had already been validated before.

Unfortunately, results from the replication experiment contradict Strack’s conclusion. The new test was run by seventeen scientists, across eight countries, using 2,000 subjects. They found no evidence that an unintentional smile or pout made any difference in the funniness of cartoons.[5]

How can this be?

Strack questions the conclusions and the set-up of the experiments. He voiced his concerns even before the testing began, after looking over their approach. At first, as I read Strack’s complaints, it felt like he was trying to defend his original work. But a number of things made me question my first impression.

First, Strack himself offered his experiment to be tested for replication and willingly supplied his original notes and evidence. Second, it had been confirmed successfully many times by other researchers. Third, he questioned the impact of the replication experimenters excluding the results of 600 subjects because they felt those subjects were holding the pens incorrectly or their answers were too wildly divergent. Did their selection to exclude certain results introduce a bias? Fourth, Strack pointed out that many of the subjects were psychology students. Since this was a textbook case, they could have recognized the experiment and its true purpose. That would have prevented them from acting naturally. They should never have been involved.

But it was the fifth point he made that jolted my attention. Strack said that he didn’t like the addition of cameras in the room watching the subjects because it could make the participants self-conscious. That jogged my memory. I had seen this scenario before.

It was one of the most famous early studies in psychology. In 1897, George Stratton strapped on a pair of lenses over his eyes that inverted and reversed his field of view.[6] He knew that our eyes have built-in lenses that produce the same effect: All of the images hitting our retinas are flipped upside-down and reversed. Stratton wanted to see if his mind would naturally find a way to invert and correct his vision.

Sure enough, after five days of looking through inverting lenses, he saw everything as right-side-up. After a week, his new vision felt completely normal.

The results were so startling that hundreds of follow-on experiments were run to reproduce the results. Many did, but some could not. For example, David Linden, a hundred years later, called Stratton’s theory of achieving upright vision a myth.[7] This has created an ongoing controversy.

I studied dozens of experiments with inverting lenses to find an explanation for what was going on. Why were the results so different? I finally found an answer in the longest study ever performed (40 days).[8] Ivan Kohler discovered, unexpectedly, that when he tried to examine the subjects every day with a battery of clinical tests, it interfered with their ability to adapt. They actually regressed.[9]

At first, Kohler thought lab tests would help show the progress his subjects were displaying. Just as Linden did, Kohler brought them in for examination on a daily basis. However, the tests made things worse. The subjects reverted back, losing the gains they had made. What’s going on, he wondered? Kohler had to alter his tests before figuring out the problem. As soon as the experiments were designed to resemble the everyday world, the problem disappeared:

“When the subject was asked to ‘aim’ at something, or to put up his hands in protection when danger threatened…he made correct responses. But when he was asked, ‘Please point this marker in the direction the light is coming from,’ errors occurred.”[10]

That’s when Kohler realized that the subjects were adapting instinctively to the real world. The moment they tried to think critically and objectively about what they were seeing, it broke their “perceptual set.” They reverted back to pre-experimental ways of seeing the world. Asking them to analyze what they were doing prevented them from adapting.

This was hard to understand, Kohler wrote. It took weeks to solve the mystery. For example, after fourteen days of fencing practice, subjects with inverting lenses were able to respond to their opponent’s blade without errors. When it came to fencing, the correct reaction was all that mattered. But if he asked them the question, “Where do you see the rapier point?” it forced them to think critically about what they were experiencing, breaking their lens of perception. They immediately reverted back to old ways of seeing. His question interfered with their instinctive responses.

Getting the subjects to think objectively about what they were doing prevented them from adapting to upright vision. This was the mistake Linden had made. Even though Linden ran his experiment thirty years after Kohler, he didn’t realize the negative impact of objectivity. No wonder all his subjects failed to achieve upright vision.

This is the same affect that cameras can have on subjects. Strack was right: It would make them conscious of being recorded and seeing what they were doing objectively. It makes the experience less natural. On top of this chilling effect of cameras, all of the instructions telling the subjects what to do were presented by a recorded video, in a closed room with no other people, making the experience even more sterile and impersonal.

Can this explain why the subjects showed no positive effects from their unintentional smiles? I think it does. Remember, Strack was trying to study an unconscious effect. He designed his experiments specifically to avoid any interference of conscious thought on the part of the subjects. If moving their mouths into the shape of a smile influences their mood, it is going to happen unconsciously. This means they need to feel at ease and natural, or it isn’t going to work. Thinking critically and objectively about what they were doing is going to interfere.

Think of the irony: Subjecting the subjects of psychology experiments to rigorous, clinical objectivity prevented the very thing they were trying to study—natural responses. They intentionally used cameras and pre-recorded instructions to eliminate outside biases, and without knowing it they introduced a new bias that was just as powerful—objectivity.

Imagine what would happen to a loving relationship if you started analyzing your life partner or lover objectively. Do you think your relationship is going to get better or worse? Is it going to warm up or cool down your natural and playful back-and-forth exchanges?

Psychology research projects have noted the detrimental impact of objectivity on natural relationships. For example, in the last few decades, psychologists have looked closer at the way people learn new skills. John Flach, Professor of Psychology at Wright State University, offers an interesting illustration for how skill-based learning works: Look at the process a child goes through when first learning how to walk, then how to skate on ice, next how to do a handstand, and finally how to walk on stilts.

Each skill needs a “different type of coordination pattern,” a different way of acting to achieve control.[11] In other words, they each require a different lens of perception, a different way of seeing, to master these skills. They learn this unconsciously through trial and error.

Skill-based learning starts with actions. Trying something gives the child feedback, such as falling on their faces or flipping onto their backs. Then they try a new approach. With each loop of trial and error they gradually figure out how to balance and how to move. Learning at this stage is non-verbal and not mediated by thought: The child can’t explain how to balance on stilts. They don’t know how they learned to walk on their hands or skate on ice. They just did it.

This natural learning process is the best way to acquire new skills. No one teaches babies how to talk. They learn it themselves by making sounds and hearing the sounds they make. They learn how to use their bodies the same way: They form working relationships with their muscles and cells. They figure it out without thinking about it.

This is different from academic study, where we consciously think to understand new ideas and what they mean. Our natural process for learning new skills, on the other hand, is largely unconscious and critical thinking can interfere with this natural process.

Psychology experiments are not easy to design. The more rigorous and objective you make them, the more artificial they become, preventing the natural responses you are looking for. You end up learning less about how people act in the real world and more how they behave in a clinical lab.

This is why, as I said above, I believe more objectivity will make the reproducibility crisis worse, not better. What is needed is a better understanding of our lenses of perception, and where to use them. For example, objectivity, as a way of seeing, shouldn’t be the goal of science, but as a tool for double-checking and verifying our experiments. If we want our relationships with others and with our bodies to be natural and spontaneous, we need a relational lens instead, not objectivity.

Over the last century, psychologists have tried to become more rigorous and objective—to become more like physicists. At the same time physicists have come to realize that objectivity can’t explain the behavior of subatomic particles. This is the lesson they learned from quantum mechanics: How you set up an experiment alters the results, and there is nothing you can do to avoid this. In other words, there is no such thing as a fully objective perspective because all measurements influence the outcome.

This same principle applies to the study of natural human responses. It can’t be avoided. Objectivity and critical analysis can and will interfere. If we understand this better, I believe psychology experiments will become easier to reproduce.

I think Katie Palmer got it right when she said that the reproducibility crisis comes down to this:

“The field [of psychology] may have to think differently about how it thinks about itself.”

[1] Open Science Collaboration (over 260 co-authors), “Estimating the Reproducibility of Psychological Science,” Science, August 28, 2015: Vol. 349, Issue 6251.

[2] Daniel T. Gilbert, Gary King, Stephen Pettigrew, Timothy D. Wilson, Comment on ‘Estimating the Reproducibility of Psychological Science,’” Science, March 4, 2016: Vol. 351, Issue 6277.

[3] Ed Young, “Psychology’s Replication Crisis Can’t Be Wished Away,” The Atlantic, March 4, 2016.

[4] Fritz Strack, Leonard L. Martin, Sabine Stepper, “Inhibiting and Facilitating Conditions of the Human Smile: A Nonobtrusive Test of the Facial Feedback Hypothesis,” Journal of Personality and Social Psychology, Vol 54(5), May 1988, 768-777.

[5] Daniel Engber, “Sad Face,” Slate magazine,  August 28, 2016.

[6] George M. Stratton, “Vision without Inversion of the Retinal Image,” Psychological Review 4, no. 4 (1897), p. 341-360.

[7] David E. J. Linden, Ulrich Kallenbach, Armin Heinecke, Wolf Singer, Rainer Goebel, “The Myth of Upright Vision,” Perception 28, no. 4 (1999), p. 469-481. Also posted at http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.294.9093&rep=rep1&type=pdf.

[8] Ivo Kohler, The Formation and Transformation of the Perceptual World, tr. Harry Fiss (New York: International Universities Press, 1964).

[9] Doug Marman, “Lenses of Perception: A Surprising New Look at the Origin of Life, the Laws of Nature, and Our Universe,” (Ridgefield, Washington, Lenses of Perception Press, 2016.), p. 88-90.

[10] Ivo Kohler, The Formation and Transformation of the Perceptual World, p. 153-155.

[11] John M. Flach and Fred Voorhorst, “What Matters?: Putting Common Sense to Work,” (Dayton, Ohio, Wright State University Libraries, 2016), p. 104-105.

Understanding Our Holographic Universe

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By Doug Marman

A sketch of the timeline of the holographic Universe. Time runs from left to right. The far left is blurry because space and time are not yet well defined. Patterns from those early formative times shaped the development of stars and galaxies in the Universe today (far right). Credit: Paul McFadden.

Scientists from the UK, Canada, and Italy, recently announced the first empirical evidence that our universe is “holographic.” Unfortunately, the meaning of this is often confused. Even the scientists who published the report seem to be getting it wrong.

For example, one of the authors of the study, Kostas Skenderis, explained it this way:

“Imagine that everything you see, feel, and hear in three dimensions (and your perception of time) in fact emanates from a flat two-dimensional field. The idea is similar to that of ordinary holograms, where a three-dimensional image is encoded in a two-dimensional surface, such as in the hologram on a credit card. However, this time, the entire Universe is encoded.”

This explanation is backwards. Our perceptions and experiences don’t emanate from two dimensions. It is the objective space-time world that is a projection, a 2-D projection that leaves out the countless invisible exchanges that make it real.

This needs explaining, but the right picture is simple: Everything visible and tangible is only the surface appearance of invisible relationships at the quantum level. Objective reality is a projection on a two-dimensional surface.

This makes a whole lot more sense because we experience the same thing in our daily lives. All the important events of our lives are the results of relationships with others. Our attractions, desires, hopes and dreams all spring from these relationships and shape the outcome of the choices we make.

We aren’t surprised when two friends get married because we know their relationship is the cause. Marriage is the end result. The same is true for companies, institutions, and societies. Everything objectively visible is the outcome of invisible relationships. This is the lesson of quantum physics. (More on this in a moment.)

This raises a question: Why would scientists working directly with quantum equations get this backwards? There are two main reasons for this. First, because physicists have no agreed-on way to interpret quantum equations. Physicists don’t have a good explanation for what quantum relationships, such as entanglement, mean or why they exist. The result of this is that most scientists revert to an objective picture of reality, even though quantum physics suggests that there is much more going on beneath the surface.

The second reason is that mathematics has a peculiar limitation: It can’t distinguish cause from effect. It only shows us correlations. This makes it easy to get the story backwards. For example, look at Isaac Newton’s second law of motion, which says:

F (force) = m (mass) X a (acceleration).

It is easy to think this formula is telling us that forces make objects accelerate, but this is wrong. It only says that there is a relationship between force, mass, and acceleration.

This illustration shows how space-time warps around planet Earth. Image by NASA.

Quantum experiments, on the other hand, have shown that forces are not true causes; they are the results of invisible quantum exchanges between charged particles.[1] Attraction and repulsion emerge from a quantum relationship that is not objectively visible.[2] This is where forces come from.

Or, to put this another way, forces are projections from a dimension that is not objective.

Space-time includes everything that is objectively visible, tangible, and measurable. In other words, this is the empirical world, the reality we see, hear, and feel with our senses. It turns out that this reality is a 2-D fabric woven from discrete events where energy is exchanged.[3]

This doesn’t mean the objective world is an illusion, but that it is only the surface appearance. It doesn’t capture the depths of our experiences any more than a person’s words, alone, capture the full meaning of what is hidden between their words, tones of voice, facial expressions and other non-verbal cues. The full meaning of what someone is saying is three-dimensional compared to their words alone.

However, even though many physicists picture the holographic principle backwards, they are right about the importance of this principle: It offers a bridge between the quantum world and the space-time universe. Over 10,000 papers have been written on the idea, because everything we have learned about quantum physics suggests that space-time emerges somehow from quantum entanglement. Now, we have the first empirical evidence that this principle is true.

The Lenses of Perception (LoP) Interpretation of Quantum Mechanics shows how space-time emerges from entangled relationships between particles, similar to the quantum theory of “decoherence.”[4] It also shows that space-time is two-dimensional because every particle is tied to space through other particles that it is directly in contact with, as other physicists have conjectured.[5] And it shows how invisible quantum exchanges cross over to become visible and objective, as other physicists have explained.[6]

This recent discovery adds further validation to the LoP Interpretation.

[1] Bruce A. Schumm, Deep Down Things: The Breathtaking Beauty of Particle Physics (Baltimore: John Hopkins University Press, 2004), p. 222-251.

[2] Ruth E. Kastner, Understanding Our Unseen Reality: Solving Quantum Riddles, (London: Imperial College Press, 2015), ch. 4, “Forces and the Relativistic Realm,” subsection: “Forces as Possibility.”

[3] Ruth E. Kastner, The Transactional Interpretation of Quantum Mechanics: The Reality of Possibility, (New York: Cambridge University Press, 2013), p. 171-178.

[4] Erich Joos, Elements of Environmental Decoherence, http://arxiv.org/pdf/quant-ph/9908008v1.pdf (August 2, 1999

[5] T. Padmanabhan, “Emergent Perspective of Gravity and Dark Energy,” Research in Astronomy and Astrophysics  12, no. 8 (2012), p. 897. Also posted at http://arxiv.org/pdf/1207.0505v1.pdf, p. 6.

[6] Kastner, Understanding Our Unseen Reality, ch. 5, “From Virtual to Possible to Real,” subsection: “Distinguishing between the Microscopic and Macroscopic Worlds.”