If you are reading this blog, you are curious about Human nature. If you are curious about Human nature, there is a book you ABSOLUTELY have to read.  It’s the book I just finished.

Daniel Kahneman is a Professor of psychology. An extraordinary one. A psychologist who won a Nobel Prize in Economic Science.
Together with his long time collaborator Amos Tversky, they conducted research since the 1970’s that have disproved the widely accepted economic model which traditionally assumes that humans are rational and maximise utility.
Their research lead to the development of a new science called ‘Behavioural Economics’ based on the assumption that humans are irrational, and that we tend to be influenced by data that is totally irrelevant to the topic at hand.

For example, in one experiment they asked college students two questions:
“How happy are you with your life in general?” and “How many dates did you have last month?“
When asked in this order they found almost no correlation. However, simply changing the order of the questions influenced the students a great deal: those who had been on a lot of dates rated themselves as much happier than those who had not.

In another experiment in Germany, they found that experienced judges were much more likely to give shoplifters a longer sentence if they had rolled a dice loaded to give a higher number just before making that decision.

‘Thinking, Fast & Slow“‘ is a great way to start the year: after reading the book, you will feel completely comfortable being as irrational as you want, and let’s face it, nothing is more liberating than irrationality.

Another way to understand Human nature and the complex processes behind our decision making is to take one of the NLP courses that we have lined up for you this year. Visit the schedule of all courses to read more about them.

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A very interesting Newsweek article on how American children are being misdiagnosed as suffering from bi-polar disorder and the dire consequences highlights the relationship between language and our health.

In his article, Stuart Kaplan, a child psychiatrist with nearly 50 years experience, talks about the fad diagnosis that launched bi-polar disorder as a juvenile disease and the subsequent 40-fold increase of outpatient office visits for children and adolescents with bipolar disorder from 20,000 in 1994–95 to 800,000 in 2002-03. “Before 1995, bipolar disorder, once known as manic-depressive illness, was rarely diagnosed in children; today nearly one third of all children and adolescents discharged from child psychiatric hospitals are diagnosed with the disorder and medicated accordingly”.

What he tags as ‘trendy thinking’ started in the 1990s, is founded on shaky scientific grounds he says (notably that the symptoms for children bi-polar disorder include behaviours that are natural in children, and that several of the studies done by some leading scholars on the disease are based entirely on reports by parents).

Children (mis)diagnosed with bi-polar disorder “will likely be given dangerous adult medications with no known effectiveness for children and plenty of known dangers. One of these is the powerful drug valproate, a medication for seizure disorders, which has proved useful as a “mood stabilizer” in the treatment of bipolar adults but has yielded anything but clear results in children. The side effects can include fatal damage to the liver, pancreas, and brain, as well as the masculinization of female patients”. The issue is serious.

It is well worth reading the whole article which is an eye-opener on how a certain type of medicine is practiced and the consequences on our health.

NLP is a study of how language not only describes but literally determines the world we live in. And this article is a good illustration of this.

Take ‘nominalisation’ for example. A nominalisation is the process of turning a verb (i.e. a process which has movement) into a noun (thereby freezing it in time). For example: blood pressure is a noun that refers to the how the blood flows (a process) in our body. Virtually all diseases are nominalisations (i.e. a name that describes a process that is happening inside the body).

A process has movement, and can therefore easily be changed, but nouns refer to something that IS. The issue with nominalisations is that it becomes very difficult to see a way out of it.

Then, there is the issue of the psychology behind influence. When someone in a position of authority/celebrity (a fortune teller, a doctor, your parents, a friend, a celebrity etc…) tells us something, we tend to believe it (read “Influence, the Psychology of Persuasion”, by Robert Cialdini for a very good study of those mechanisms at work). So when ‘a Harvard child-psychiatry group led by Dr. Joseph Biederman, a prominent supporter of the diagnosis, recently insisted, “Juvenile bipolar disorder is a serious illness that is estimated to affect approximately 1 percent to 4 percent of children’ most people, even psychiatrists, will deem it to be true.

Another dimension of influence is that, as propagandist and advertisers know, the more we see and hear a message, the more familiar it becomes and the more we tend to believe it is true.

Finally, the more we invest (time, money, efforts) in something, the more attached we become to it because our focus becomes solely concentrated on the subject we study. Someone who specialises in studying bi-polar disorder in small children will more likely indeed find that the disease exists because the mind is programmed this way.

Have you ever wondered how psychiatrists know that someone suffers from a mental disorder? All mental disorders are compiled in a ‘bible’, a book called the DSM (Diagnostic & Statistical Manual of Mental Disorders). The book is published by the American Psychiatric Association, but is used outside the US as well. There have been several editions of the DSM since its first edition in 1952, the DSM in use nowadays is the DSM 4 published in 1994, and a major review is to be published in 2013 (DSM 5).

Of course, we need objective references and  scientific criteria in medicine, hence the necessity for a reference book such as the DSM. And it is also true that putting a noun in print and making it a ‘condition’ has a huge influence on how we see the condition, which is why the revision of the DSM attracts so much criticism. In the first edition of the DSM published in 1952, homosexuality was listed as a mental disorder. What would we do with this nowadays? Societies evolve with time and societal beliefs change.

Kaplan laments that ‘in the U.S., popular culture has had an outsize influence on psychiatry, […] the popular debut of a medical disorder began with the publication of a book, The Bipolar Child, by Dr. Demitri Papolos and Janice Papolos, a husband-and-wife team. As part of the book’s promotion, the authors were featured on the show 20/20. Within 30 minutes of the segment’s airing, 20/20 received more than 6,000 emails. Shortly thereafter, the authors appeared on Oprah and eventually sold more than 200,000 copies of their book’.

It is not possible for the human mind to be completely objective (see the post ‘the limits of reason’ in The MasterMinds Blog), but it is worth keeping an open mind and getting a wide range of information on subjects that affect us as deeply as out health.

Click here to check the schedule of courses and certification trainings on language and communication that will change how you understand information.

NB1: Kaplan is a child psychiatrist and a clinical professor of psychiatry at Penn State College of Medicine. This article is an adaptation from his book, Your Child Does Not Have Bipolar Disorder: How Bad Science and Good Public Relations Created the Diagnosis.

NB2: For more on the business model of the pharmaceutical industry and the business of defining mental illness, read this post on The MasterMinds blog.

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Remember Mona Lisa? What was she thinking about?

There is more to a smile than what we usually think. Research has shown that smiling & laughing can reduce stress, improve the immune system, and even could help with recovering from certain diseases. The most famous case is Norman Cousins’ recovery from (what is now thought to be) reactive arthritis which he claims in his book “Anatomy of an Illness” he cured with mega-doses of Vitamin C and heavy doses of daily laughter. He mentions : “I made the joyous discovery that ten minutes of genuine belly laughter had an anesthetic effect and would give me at least two hours of pain-free sleep,” he reported. “When the pain-killing effect of the laughter wore off, we would switch on the motion picture projector again and not infrequently, it would lead to another pain-free interval.”

Many Eastern traditions have also incorporated laughter as part of a daily set of practices such as Laughing Yoga and Laughing Qi Gong. The power of the Taoist ‘Inner Smile’ meditations has been well documented (we teach some of those practices during our Beat Stress, Pill Free half day workshop. Check date for the next one on the schedule of all courses webpage)

Watch the Ted video below where Ron Gutman reviews a number of studies about smiling, and reveals some unexpected results.

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In a few years time, this will be our daily reality.

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THis is the transcript of Nicholas Christakis’ Ted Talks video on how social networks shape our lives.
You can see the interactive transcript on the Ted webpage.

For me, this story begins about 15 years ago, when I was a hospice doctor at the University of Chicago. And I was taking care of people who were dying, and their families, in the South Side of Chicago. And I was observing what happened to people and their families over the course of their terminal illness. And in my lab, I was studying the widower effect, which is a very old idea in the social sciences, going back 150 years, known as “dying of a broken heart.” So, when I die, my wife’s risk of death can double, for instance, in the first year. And I had gone to take care of one particular patient, a woman who was dying of dementia. And, in this case, unlike this couple, she was being cared for by her daughter. And the daughter was exhausted from caring for her mother. And the daughter’s husband, he also was sick from his wife’s exhaustion. And I was driving home one day, and I get a phone call from the husband’s friend, calling me because he was depressed about what was happening to his friend. So here I get this call from this random guy that’s having an experience that’s being influenced by people at some social distance.

And so I suddenly realized two very simple things. First, the widowhood effect was not restricted to husbands and wives. And second, it was not restricted to pairs of people. And I started to see the world in a whole new way, like pairs of people connected to each other. And then I realized that these individuals would be connected into foursomes with other pairs of people nearby. And then, in fact, these people were embedded in other sorts of relationships, marriage and spousal and friendship and other sorts of ties. And that, in fact, these connections were vast, and that we were all embedded in this broad set of connections with each other. So I started to see the world in a completely new way, and I became obsessed with this. I became obsessed with how it might be that we’re embedded in these social networks, and how they effect our lives. So, social networks are these intricate things of beauty, and they’re so elaborate and so complex and so ubiquitous, in fact, that one has to ask what purpose they serve. Why are we embedded in social networks? I mean, how do they form? How do they operate? And how do they effect us?

And so my first topic, with respect to this, was not death, but obesity. And suddenly it had become trendy to speak about the “obesity epidemic.” And, along with my collaborator, James Fowler, we began to wonder whether obesity really was epidemic, and could it spread from person to person like the four people I discussed earlier. So this is a slide of some of our initial results. It’s 2,200 people in the year 2000. Every dot is a person. We make the dot size proportional to people’s body size. So bigger dots are bigger people. In addition, if your body size, if your BMI, your body mass index is above 30, if you’re clinically obese, we also colored the dots yellow. So, if you look at this image, right away you might be able to see that there are clusters of obese and non-obese people in the image. But the visual complexity is still very high. It’s not obvious exactly what’s going on. In addition, some questions are immediately raised. How much clustering is there? Is there more clustering than would be due to chance alone? How big are the clusters? How far do they reach? And, most importantly, what causes the clusters?

So we did some mathematics to study the size of these clusters. This here shows, on the Y-axis, the increase in the probability that a person is obese, given that a social contact of theirs is obese. And on the X-axis, the degrees of separation between the two people. And on the far left, you see the purple [bar]. It says that, if your friends are obese, your risk of obesity is 45 percent higher. And the next bar over, the [red bar], says that, if your friend’s friends are obese, your risk of obesity is 25 percent higher. And then the next [bar] over says that, if your friend’s friend’s friend, someone you probably don’t even know, is obese, your risk of obesity is 10 percent higher. And it’s only when you get to your friend’s friend’s friend’s friends, that there’s no longer a relationship between that person’s body size and your own body size.

Well, what might be causing this clustering? There are at least three possibilities. One possibility is that, as I gain weight, it causes you to gain weight, a kind of induction, a kind of spread from person to person. Another possibility, very obvious, is homophily, or “birds of a feather flock together.” Here, I form my tie to you because you and I share a similar body size. And the last possibility is what is known as confounding, because it confounds our ability to figure out what’s going on. And here, the idea is not that my weight gain is causing your weight gain, nor that I preferentially form a tie with you because you and I share the same body size, but rather that we share a common exposure to something, like a health club, that makes us both lose weight at the same time.

And when we studied these data, we found evidence for all of these things, including for induction. And we found that, if your friend becomes obese, it increases your risk of obesity by about 57 percent in the same given time period. There can be many mechanisms for this effect. One possibility is that your friends say to you something like — you know, they adopt a behavior that spreads to you — like, they say, “Let’s go have muffins and beer,” which is a terrible combination. But you adopt that combination, and then you start gaining weight like them. Another more subtle possibility is that they start gaining weight, and it changes your ideas of what an acceptable body size is. Here, what’s spreading from person to person is not a behavior, but rather a norm. An idea is spreading.

Now, headline writers had a field day with our studies. I think the headline in the New York Times was, “Are you packing it on? Blame your fat friends.” What was interesting to us is that the European headline writers had a different take: They said, “Are your friends gaining weight? Perhaps you are to blame.” (Laughter) And we thought this was a very interesting comment on America — and kind of self-serving, “not-my-responsibility” kind of phenomenon.

Now, I want to be very clear: we do not think our work should or could justify prejudice against people of one or another body size at all. Now, our next questions was: Could we actually visualize this spread? Was weight gain in one person actually spreading to weight gain in another person? And this was complicated because we needed to take into account the fact that the network structure, the architecture of the ties, was changing across time. In addition, because obesity is not a unicentric epidemic, there’s not a “patient zero” of the obesity epidemic — if we find that guy, there was a spread of obesity out from him. It’s a multicentric epidemic. Lots of people are doing things at the same time. And I’m about to show you a 30 second video animation that took me and James five years of our lives to do. So, again, every dot is a person. Every tie between them is a relationship. We’re going to put this into motion now, taking daily cuts to the network for about 30 years.

The dot sizes are going to grow. You’re going to see a sea of yellow take over. You’re going to see people be born and die; dots will appear and disappear. Ties will form and break. Marriages and divorces, friendings and defriendings. A lot of complexity, a lot is happening just in this thirty year period that includes the obesity epidemic. And, by the end, you’re going to see clusters of obese and non-obese individuals within the network. Now, when looked at this, it changed the way I see things, because this thing, this network, is changing across time, it has a memory, it moves, things flow within it, it has a kind of consistency. People can die, but it doesn’t die; it still persists. And it has a kind of resilience that allows it to persist across time.

And so, I came to see these kinds of social networks as living things, as living things that we could put under a kind of microscope to study and analyze and understand. And we used a variety of techniques to do this. And we started exploring all kinds of other phenomena. We looked at smoking and drinking behavior, and voting behavior, and divorce — which can spread — and altruism. And, eventually, we became interested in emotions. Now, when we have emotions, we show them. Why do we show our emotions? I mean, there would be an advantage to experiencing our emotions inside, you know, anger or happiness. But we don’t just experience them, we show them. And not only do we show them, but others can read them. And, not only can they read them, but they copy them. There’s emotional contagion that takes place in human populations. And so this function of emotions suggest that, in addition to any other purpose they serve, they’re a kind of primitive form of communication. And that, in fact, if we really want to understand human emotions, we need to think about them in this way.

Now, we’re accustomed to thinking about emotions in this way, in simple, sort of, brief periods of time. So, for example, I was giving this talk recently in New York City, and I said, “You know, like how when you’re on the subway, and the other person across the subway car smiles at you, and you just instinctively smile back.” And they looked at me, said, “We don’t do that in New York City.” (Laughter) And I said, “Everywhere else in the world, that’s normal human behavior.” And so there’s a very instinctive way in which we briefly transmit emotions to each other. And, in fact, emotional contagion can be broader still, like we could have punctuated expressions of anger, as in riots. The question that we wanted to ask was: Could emotion spread, in a more sustained way than riots, across time. and involve large numbers of people, not just this pair of individuals smiling at each other in the subway car? Maybe there’s a kind of below-the-surface quiet riot that animates us all the time. Maybe there are emotional stampedes that ripple through social networks. Maybe, in fact, emotions have a collective existence, not just an individual existence.

And this is one of the first images we made to study this phenomenon. Again, a social network, but now we color the people yellow if they’re happy and blue if they’re sad and green in between. And if you look at this image, you can right away see clusters of happy and unhappy people, again, spreading to three degrees of separation. And you might form the intuition that the unhappy people occupy a different structural location within the network. There’s a middle and an edge to this network, and the unhappy people seem to be located at the edges. So to invoke another metaphor, if you imagine social networks as a kind of vast fabric of humanity — I’m connected to you and you to her, on out endlessly into the distance — this fabric is actually like an old-fashioned American quilt, and it has patches on it, happy and unhappy patches. And whether you become happy or not depends in part on whether you occupy a happy patch.

(Laughter)

So, this work with emotions, which are so fundamental, then got us to thinking about, maybe the fundamental causes of human social networks are somehow encoded in our genes. Because human social networks, whenever they are mapped, always kind of look like this, this picture of the network. But they never look like this. Why do they not look like this? Why don’t we form human social networks that look like a regular lattice? Well, the striking patterns of human social networks, their ubiquity, and their apparent purpose beg questions about whether we evolved to have social networks in the first place, and whether we evolved to form networks with a particular structure.

And notice first of all … And so, to understand this, though, we need to dissect network structure a little bit first. Notice that every person in this network has exactly the same structural location as every other person. But that’s not the case with real networks. So, for example, here is a real network of college students at an elite northeastern university. And now I’m highlighting a few dots. and if you look here at the dots, compare node B, in the upper left, to node D in the far right. B has four friends coming out from him. And D has six friends coming out from him. And so, those two individuals have different numbers of friends. That’s very obvious, we all know that. But certain other aspects of social network structure are not so obvious.

Compare node B in the upper left to node A in the lower left. And now those people both have four friends, but A’s friends all know each other, and B’s friends do not. So the friend of a friend of A’s, is back again a friend of A’s, whereas the friend of a friend of B’s is not a friend of B’s, but is farther away in the network. This is known as transitivity in networks. And, finally, compare nodes C and D. C and D both have six friends. If you talk to them, and you said, “What is your social life like?” they would say, “I’ve got six friends. That’s my social experience.” But now we, with a bird’s eye view, looking at this network, can see that they occupy very different social worlds. And I can cultivate that intuition in you by just asking you: Who would you rather be if a deadly germ was spreading through the network? Would you rather be C or D? You’d rather be D, on the edge of the network. And now who would you rather be if a juicy piece of gossip, not about you, was spreading through the network? Now, you would rather be C.

So different structural locations have different implications for you life. And, in fact, when we did some experiments looking at this, what we found is that 46 percent of the variation in how many friends you have is explained by your genes. But this is not surprising. We know that some people are born shy and some are born gregarious. That’s obvious. But we also found some non-obvious things. For instance, 47 percent in the variation in whether your friends know each other is attributable to your genes. Whether your friends know each other has not just to do with their genes, but with yours. And we think the reason for this is that some people like to introduce their friends to each other — you know who you are — and others of you keep them apart and don’t introduce your friends to each other. And so some people knit together the networks around them, creating a kind of dense web of ties in which they’re comfortably embedded. And finally, we even found that 30 percent of the variation in whether or not people are in the middle or on the edge of the network can also be attributed to their genes. So whether you find yourself in the middle or on the edge, is also partially heritable.

Now, what is the point of this? How does this help us understand [the world]? How does this help us figure out some of the problems that are effecting us these days? Well, the argument I’d like to make is that networks have value. They are a kind of social capital. New properties emerge because of our embeddedness in social networks, and these properties inhere in the structure of the networks, not just in the individuals within them. So think about these two common objects. They’re both made of carbon, and yet one of them has carbon atoms in it that are arranged in one particular way, on the left, and you get graphite, which is soft and dark. But if you take the same carbon atoms and interconnect them a different way, you get diamond, which is clear and hard. And those properties of softness and hardness and darkness and clearness do not reside in the carbon atoms. They reside in the interconnections between the carbon atoms, or at least arise because of the interconnections between the carbon atoms. So, similarly, the pattern of connections among people confers upon the groups of people different properties. It is the ties between people that makes the whole greater than the sum of its parts. And so it is not just what’s happening to these people — whether they’re losing weight or gaining weight, or becoming rich or becoming poor, or becoming happy or not becoming happy — that affects us; it’s also the actual architecture of the ties around us.

Our experience of the world depends on the actual structure of the networks in which we’re residing and on all the kinds of things that ripple and flow through the network. Now, the reason, I think, that this is the case is that human beings assemble themselves and form a kind of superorganism. Now, a superorganism is a collection of individuals which show or evince behaviors or phenomena that are not reducible to the study of individuals and that must be understood by reference to, and by studying, the collective, like, for example, a hive of bees that’s finding a new nesting site, or a flock of birds that’s evading a predator, or a flock of birds that’s able to pool its wisdom and navigate and find a tiny speck of an island in the middle of the Pacific, or a pack of wolves that’s able to bring down larger prey. Superorganisms have properties that cannot be understood just by studying the individuals. I think understanding social networks and how they form and operate, can help us understand not just health and emotions but all kinds of other phenomena — like crime, and warfare, and economic phenomena like bank runs and market crashes and the adoption of innovation and the spread of product adoption.

Now, look at this. I think we form social networks because the benefits of a connected life outweigh the costs. If I were always violent towards you or gave you misinformation, or made you sad, or infected you with deadly germs, you would cut the ties to me, and the network would disintegrate. So the spread of good and valuable things is required to sustain and nourish social networks. Similarly, social networks are required for the spread of good and valuable things, like love and kindness and happiness and altruism and ideas. I think, in fact, that if we realized how valuable social networks are, we’d spend a lot more time nourishing them and sustaining them, because I think social networks are fundamentally related to goodness. And what I think the world needs now is more connections.

Thank you.

(Applause)

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Nicholas Christakis studies the subtle influence of large social networks on our lives. He came up with astonishing discoveries.
One surprising example is obesity.
Looking at the spread of obesity in large social networks, he found that there are clear clusters of obesity. In short, if your friends are fat, you are more likely to be fat. So far so good, this is understandable: you tend to go out with your friends, eat in the same places, share the same activities etc…
But what is unexpected is that the cluster extend to 3 degrees of separation! In short, your friends’ friends’ friends can make you fat!
Watch the Ted Talks video below for more.

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What we really need to teach kids in science class: The BS (Bad Science) detector by Sharon Begley, based on Ben Goldacre (of London School of Hygiene & Tropical Medicine) new book, “Bad Science: Quacks, Hacks, and Big Pharma Flacks”.

Observational studies (such eating an olive oil based diet etc…) are not a reliable basis for health advice.

Also, ignore the law of regression to the mean at your own risks. Example: attributing recovery from many ailments to the treatment is ignoring the fact that they have a natural cycle (i.e. they disappear after a while), and that people tend to seek treatment at the peak of their discomfort (i.e. they would start to get better anyway).

Read along if you want to learn about a really interesting experiment done in the classroom…

Click on this link to the Newsweek article.

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Scientists have created the first device to render an object invisible in three dimensions.
Click on the link that will take you to the BBC online article.
Invisibility Cloak

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A fascinating video from TedTalks by Ray Kurzweil on the exponential growth of Technology. Kurzweil explains how easy it is to predict the evolution of technology (contrary to the stock markets), and how the speed of new discoveries grows exponentially. Science fiction future is just a corner away! Ever wished you could sit at the bottom of your pool for 4 hours? It may be possible as soon as 2020!

‘Inventor and futurist Ray Kurzweil illustrates the increasingly exponential evolution of technology, predicting a sharp rise in computing capability, robotics and life expectancy within the next 15 years. He outlines the shocking ways we’ll use technology to augment our own capabilities, forever blurring the lines between human and machine. A prolific inventor, Kurzweil developed the first Optical Character Recognition (OCR) system, the first text-to-speech reader for the blind, one of the first speech-recognition systems, and numerous electronic instruments. He’s written several books exploring the social impact of technology, including The Age of Spiritual Machines and The Singularity is Near: When Humans Transcend Biology’.

(Recorded February 2005 in Monterey, CA. Duration: 23:41)

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Susan Blackmore is dedicated to understanding the scientific nature of consciousness. Her latest work centers on the existence of memes — little bits of knowledge, lore, habit that seem to spread themselves using human brains as mere carriers. She’s exploring the existence of a new class of meme, spread by human technology. It’s temporarily named the “teme.”

[ted id=269]

If ‘Memes’ are ideas, habits, attitudes, knowledge … ‘vMemes’ are their container, the way we think about Memes. These vMemes are the foundation of our values, what we hold true, important, which we are not conscious about, and which drive ALL our actions and thoughts.

To learn more, discover your and other people’s vMemes, understand what deeply motivates people, and improve communication and therefore effectiveness, register for the ‘Thinking Styles’ week end course (which includes 3 online assessments, free if you sign up before the deadline). Click HERE and select “Thinking Styles” course in the schedule of workshops. This course is a must if you work with people (coach, HR management, trainer, recruiter, educator…)

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