Category Archives: Neuroscanning

There Are No Short Cuts to Being Human

The Velvet Sundown fooled a lot of people, including millions of fans on Spotify and the writers and editors at Rolling Stone. It was a band that suddenly showed up on Spotify several months ago, with full albums of vintage Americana styled rock. Millions started streaming the band’s songs – except there was no band. The songs, the album art, the band’s photos – it was all generated by AI.

When you know this and relisten to the songs, you swear you would have never been fooled. Those who are now in the know say the music is formulaic, derivative and uninspired. Yet we were fooled, or, at least, millions of us were – taken in by an AI hoax, or what is now euphemistically labelled on Spotify as “a synthetic music project guided by human creative direction and composed, voiced and visualized with the support of artificial intelligence.”

Formulaic. Derivative. Synthetic. We mean these as criticisms. But they are accurate descriptions of exactly how AI works. It is synthesis by formulas (or algorithms) that parse billions or trillions of data points, identify patterns and derive the finished product from it. That is AI’s greatest strength…and its biggest downfall.

The human brain, on the other hand, works quite differently. Our biggest constraint is the limit of our working memory. When we analyze disparate data points, the available slots in our temporary memory bank can be as low as in the single digits. To cognitively function beyond this limit, we have to do two things: “chunk” them together into mental building blocks and code them with emotional tags. That is the human brain’s greatest strength… and again, it’s biggest downfall. What the human brain is best at is what AI is unable to do. And vice versa.

A few posts back when talking about one less-than-impressive experience with an AI tool, I ended by musing what role humans might play as AI evolves and becomes more capable. One possible answer is something labelled “HITL” or “Humans in the Loop.” It plugs the “humanness” that sits in our brains into the equation, allowing AI to do what it’s best at and humans to provide the spark of intuition or the “gut checks” that currently cannot come from an algorithm.

As an example, let me return to the subject of that previous post, building a website. There is a lot that AI could do to build out a website. What it can’t do very well is anticipate how a human might interact with the website. These “use cases” should come from a human, perhaps one like me.

Let me tell you why I believe I’m qualified for the job. For many years, I studied online user behavior quite obsessively and published several white papers that are still cited in the academic world. I was a researcher for hire, with contracts with all the major online players. I say this not to pump my own ego (okay, maybe a little bit – I am human after all) but to set up the process of how I acquired this particular brand of expertise.

It was accumulated over time, as I learned how to analyze online interactions, code eye-tracking sessions, talked to users about goals and intentions. All the while, I was continually plugging new data into my few available working memory slots and “chunking” them into the building blocks of my expertise, to the point where I could quickly look at a website or search results page and provide a pretty accurate “gut call” prediction of how a user would interact with it. This is – without exception – how humans become experts at anything. Malcolm Gladwell called it the “10,000-hour rule.” For humans to add any value “in the loop” they must put in the time. There are no short cuts.

Or – at least – there never used to be. There is now, and that brings up a problem.

Humans now do something called “cognitive off-loading.” If something looks like it’s going to be a drudge to do, we now get Chat-GPT to do it. This is the slogging mental work that our brains are not particularly well suited to. That’s probably why we hate doing it – the brain is trying to shirk the work by tagging it with a negative emotion (brains are sneaky that way). Why not get AI, who can instantly sort through billions of data points and synthesize it into a one-page summary, to do our dirty work for us?

But by off-loading, we short circuit the very process required to build that uniquely human expertise. Writer, researcher and educational change advocate Eva Keiffenheim outlines the potential danger for humans who “off-load” to a digital brain; we may lose the sole advantage we can offer in an artificially intelligent world, “If you can’t recall it without a device, you haven’t truly learned it. You’ve rented the information. We get stuck at ‘knowing about’ a topic, never reaching the automaticity of ‘knowing how.’”

For generations, we’ve treasured the concept of “know how.” Perhaps, in all that time, we forgot how much hard mental work was required to gain it. That could be why we are quick to trade it away now that we can.

Face Time in the Real World is Important

For all the advances made in neuroscience, we still don’t fully understand how our brains respond to other people. What we do know is that it’s complex.

Join the Chorus

Recent studies, including this one from Rochester University, are showing that when we see someone we recognize, the brain responds with a chorus of neuronal activity. Neurons from different parts of the brain fire in unison, creating a congruent response that may simultaneously pull from memory, from emotion, from the rational regions of our prefrontal cortex and from other deep-seated areas of our brain. The firing of any one neuron may be relatively subtle, but together this chorus of neurons can create a powerful response to a person. This cognitive choir represents our total comprehension of an individual.

Non-Verbal Communication

“You’ll have your looks, your pretty face. – And don’t underestimate the importance of body language!” – Ursula, The Little Mermaid

Given that we respond to people with different parts of the brain, it makes sense that we use part of the brain we didn’t realize when communicating with someone else. In 1967, psychologist Albert Mehrabian attempted to pin this down with some actual numbers, publishing a paper in which he put forth what became known as Mehrabian’s Rule: 7% of communication is verbal, 38% is tone of voice and 55% is body language.

Like many oft-quoted rules, this one is typically mis-quoted. It’s not that words are not important when we communication something. Words convey the message. But it’s the non-verbal part that determines how we interpret the message – and whether we trust it or not.

Folk wisdom has told us, “Your mouth is telling me one thing, but your eyes are telling me another.” In this case, folk wisdom is right. We evolved to respond to another person with our whole bodies, with our brains playing the part of conductor. Maybe the numbers don’t exactly add up to Mehrabian’s neat and tidy ratio, but the importance of non-verbal communication is undeniable. We intuitively pick up incredibly subtle hints: a slight tremor in the voice, a bead of sweat on the forehead, a slight turn down of one corner of the mouth, perhaps a foot tapping or a finger trembling, a split-second darting of the eye. All this is subconsciously monitored, fed to the brain and orchestrated into a judgment about a person and what they’re trying to tell us. This is how we evolved to judge whether we should build trust or lose it.

Face to Face vs Face to Screen

Now, we get to the question you knew was coming, “What happens when we have to make these decisions about someone else through a screen rather than face to face?”

Given that we don’t fully understand how the brain responds to people yet, it’s hard to say how much of our ability to judge whether we should convey trust or withhold it is impaired by screen-to-screen communication. My guess is that the impairment is significant, probably well over 50%. It’s difficult to test this in a laboratory setting, given that it generally requires some type of neuroimaging, such as an fMRI scanner. In order to present a stimulus for the brain to respond to when the subject is strapped in, a screen is really the only option. But common sense tells me – given the sophisticated and orchestrated nature of our brain’s social responses – that a lot is lost in translation from a real-world encounter to a screen recording.

New Faces vs Old Ones

If we think of how our brains respond to faces, we realize that in today’s world, a lot of our social judgements are increasing made without face-to-face encounters. In a case where we know someone, we will pull forward a snapshot of our entire history with that person. The current communication is just another data point in a rich collection of interpersonal experience. One would think that would substantially increase our odds of making a valid judgement.

But what if we must make a judgement on someone we’ve never met before, and have only seen through a screen; be it a TikTok post, an Instagram Reel, a YouTube video or a Facebook Post? What if we have to decide whether to believe an influencer when making an important life decision? Are we willing to rely on a fraction of our brain’s capacity when deciding whether to place trust in someone we’ve never met?

Why Hate is Trending Up

There seems to be a lot of hate in the world lately. But hate is a hard thing to quantify. There are, however, a couple places that may put some hard numbers behind my hunch.

Google’s NGram viewer tracks the frequency of the appearance of a word through published books from 2022 all the way back to 1800. According to NGram, the usage of “hate” has skyrocketed, beginning in the mid 1980s. In 2022, the last year you can search for, the frequency of usage of “hate” was 3 times higher than it historically was.

NGram also allows you to search separately for usage in American English and British English. You’ll either be happy or dismayed to learn that hate knows no boundaries. The British hate almost as much as Americans. They had the same steep incline over the past 4 decades. However, Americans still have an edge on usage, with a frequency that is about 40% higher than those speaking the Queen’s English.

One difference between the two graphs were during the years of the First World War. Then, usage of “hate” in England spiked briefly. The U.S. didn’t have the same spike.

Another way to measure hate is provided by the Southern Poverty Law Center in Montgomery, Alabama, who have been publishing a “hate map” since 2000. The map tracks hate and antigovernment groups. In the year 2000, the first year of the map, the SPLC tracked 599 hate groups across the U.S. By 2023, the number of hate groups had exploded by 240 percent to 1430.

So – yeah – it looks like we all hate a little more than we used to. I’ve talked before about Overton’s Window, that construct that defines what it is acceptable to talk about in public. And based on both these quantitative measures, it looks like “hate” is trending up. A lot.

I’m not immune to trends. I don’t personally track such things, but I’m pretty sure the word “hate” has slipped from my lips more often in the past few years. But here’s the thing. It’s almost never used towards a person I know well. It’s certainly never used towards a person I’m in the same room with. It’s almost always used towards a faceless construct that represents a person or a group of people that I really don’t know very well. It’s not like I sit down and have a coffee with them every week. And there we have one of the common catalysts of hate – something called “dehumanization.”

Dehumanization is a mental backflip where we take a group and strip them of their human qualities, including intelligence, compassion, kindness or social awareness. We in our own “in group” make those in the “out group” less than human so it’s easier to hate them. They are “stupid”, “ignorant”, “evil” or “animals”.

But an interesting thing happens when we’re forced to sit face to face with a representative from this group and actually engage then in conversation so we can learn more about them. Suddenly, we see they’re not as stupid, evil or animalistic as we thought. Sure, we might not agree with them on everything, but we don’t hate them. And the reason for this is due to another thing that makes us human, a molecule called oxytocin.

Oxytocin has been called the “Trust molecule” by neuroeconomist Paul Zak. It kicks off a neurochemical reaction that readies our brains to be empathetic and trusting. It is part of our evolved trust sensing mechanism, orchestrating a delicate dance by our prefrontal cortex and other regions like the amygdala.

But to get the oxytocin flowing, you really need to be face-to-face with a person. You need to be communicating with your whole body, not just your eyes or ears. The way we actually communicate has been called the 7-38-55 rule, thanks to research done in the 1960’s and 70’s by UCLA body language researcher Albert Mehrabian. He showed that 7% of communication is verbal, 38% is tone of voice and 55% is through body language.

It’s that 93% of communication that is critical in the building of trust. And it can only happen face to face. Unfortunately, our society has done a dramatic about-face away from communication that happens in a shared physical space towards communication that is mediated through electronic platforms. And that started to happen about 40 years ago.

Hmmm, I wonder if there’s a connection?

Talking Out Loud to Myself

I talk to myself out loud. Yes, full conversations, questions and answers, even debates — I can do everything all by myself.

I don’t do it when people are around. I’m just not that confident in my own cognitive quirks. It doesn’t seem, well… normal, you know?

But between you and me, I do it all the time. I usually walk at the same time. For me, nothing works better than some walking and talking with myself to work out particularly thorny problems.

Now, if I was using Google to diagnose myself, it would be a coin toss whether I was crazy or a genius. It could go either way.  One of the sites I clicked to said it could be a symptom of psychosis. But another site pointed to a study at Bangor University (2012 – Kirkham, Breeze, Mari-Beffa) that indicates that talking to yourself out loud may indicate a higher level of intelligence. Apparently, Nikola Tesla talked to himself during lightning storms. Of course, he also had a severe aversion to women who wore pearl earrings. So the jury may still be out on that one.

I think pushing your inner voice through the language processing center of your brain and actually talking out loud does something to crystallize fleeting thoughts. One of the researchers of the Bangor study, Paloma Mari-Beffa, agrees with this hypothesis:

“Our results demonstrated that, even if we talk to ourselves to gain control during challenging tasks, performance substantially improves when we do it out loud.”

Mari-Beffa continues,

“Talking out loud, when the mind is not wandering, could actually be a sign of high cognitive functioning. Rather than being mentally ill, it can make you intellectually more competent. The stereotype of the mad scientist talking to themselves, lost in their own inner world, might reflect the reality of a genius who uses all the means at their disposal to increase their brain power.”

When I looked for any academic studies to support the value of talking out loud to yourself, I found one (Huang, Carr and Cao, 2001) that was obviously aimed at neuroscientists, something I definitely am not. But after plowing through it, I think it said the brain does work differently when you say things out loud.

Another one (Gruber, von Cramon 2001) even said that when we artificially suppress our strategy of verbalizing our thoughts, our brains seem to operate the same way that a monkey’s brain would, using different parts of the brain to complete different tasks (e.g., visual, spatial or auditory). But when allowed to talk to themselves, humans tend to use a verbalizing strategy to accomplish all kinds of tasks. This indicates that verbalization seems to be the preferred way humans work stuff out. It gives guide rails and a road map to our human brain.

But if we’ve learned anything about human brains, we’ve learned that they don’t all work the same way. Are some brains more likely to benefit from the owner talking to themselves out loud, for instance? Take introverts, for example. I am a self-confessed introvert. And I talk to myself. So I had to ask, are introverts more likely to have deep, meaningful conversations with themselves?

If you’re not an introvert, let me first tell you that introverts are generally terrible at small talk. But — if I do say so myself — we’re great at “big” talk. We like to go deep in our conversations, generally with just one other person. Walking and talking with someone is an introvert’s idea of a good time. So walking and talking with yourself should be the introvert’s holy grail.

While I couldn’t find any empirical evidence to support this correlation between self-talk and introversion, I did find a bucketful of sites about introverts noting that it’s pretty common for us to talk to ourselves. We are inclined to process information internally before we engage externally, so self-talk becomes an important tool in helping us to organize our thoughts.

Remember, external engagements tend to drain the battery of an introvert, so a little power management before the engagement to prevent running out of juice midway through a social occasion makes sense.

I know this is all a lot to think about. Maybe it would help to talk it out — by yourself.

Feature image by Brecht Bug – Flickr – Creative Commons

The Dangerous Bits about ChatGPT

Last week, I shared how ChatGPT got a few things wrong when I asked it “who Gord Hotchkiss was.” I did this with my tongue at least partially implanted in cheek – but the response did show me a real potential danger here, coming from how we will interact with ChatGPT.

When things go wrong, we love to assign blame. And if ChatGPT gets things wrong, we will be quick to point the finger at it. But let’s remember, ChatGPT is a tool, and the fault very seldom lies with the tool. The fault usually lies with the person using the tool.

First of all, let’s look at why ChatGPT put together a bio for myself that was somewhat less than accurate (although it was very flattering to yours truly).

When AI Hallucinates

I have found a few articles that calls ChatGPT out for lying. But lying is an intentional act, and – as far as I know – ChatGPT has no intention of deliberately leading us astray. Based on how ChatGPT pulls together information and synthesizes it into a natural language response, it actually thought that “Gord Hotchkiss” did the things it told me I had done.

You could more accurately say ChatGPT is hallucinating – giving a false picture based on what information it retrieves and then tries to connect into a narrative. It’s a flaw that will undoubtedly get better with time.

The problem comes with how ChatGPT handles its dataset and determines relevance between items in that dataset. In this thorough examination by Machine Learning expert Devansh Devansh, ChatGPT is compared to predictive autocomplete on your phone. Sometimes, through a glitch in the AI, it can take a weird direction.

When this happens on your phone, it’s word by word and you can easily spot where things are going off the rail.  With ChatGPT, an initial error that might be small at first continues to propagate until the AI has spun complete bullshit and packaged it as truth. This is how it fabricated the Think Tank of Human Values in Business, a completely fictional organization, and inserted it into my CV in a very convincing way.

There are many, many others who know much more about AI and Natural Language Processing that I do, so I’m going to recognize my limits and leave it there. Let’s just say that ChatGPT is prone to sharing it’s AI hallucinations in a very convincing way.

Users of ChatGPT Won’t Admit Its Limitations

I know and you know that marketers are salivating over the possibility of AI producing content at scale for automated marketing campaigns. There is a frenzy of positively giddy accounts about how ChatGPT will “revolutionize Content Creation and Analysis” – including this admittedly tongue in cheek one co-authored by MediaPost Editor in Chief Joe Mandese and – of course – ChatGPT.

So what happens when ChatGPT starts to hallucinate in the middle of massive social media campaign that is totally on autopilot? Who will be the ghost in the machine that will say “Whoa there, let’s just take a sec to make sure we’re not spinning out fictitious and potentially dangerous content?”

No one. Marketers are only human, and humans will always look for the path of least resistance. We work to eliminate friction, not add it. If we can automate marketing, we will. And we will shift the onus of verifying information to the consumer of that information.

Don’t tell me we won’t, because we have in the past and we will in the future.

We Believe What We’re Told

We might like to believe we’re Cartesian, but when it comes to consuming information, we’re actually Spinozian

Let me explain. French philosopher René Descartes and Dutch philosopher Baruch Spinoza had two different views of how we determine if something is true.

Descartes believed that understanding and believing were two different processes. According to Descartes, when we get new information, we first analyze it and then decide if we believe it or not. This is the rational assessment that publishers and marketers always insist that we humans do and it’s their fallback position when they’re accused of spreading misinformation.

But Baruch Spinoza believed that understanding and belief happened at the same time. We start from a default position of believing information to be true without really analyzing it.

In 1993, Harvard Psychology Professor Daniel Gilbert decided to put the debate to the test (Gilbert, Tafarodi and Malone). He split a group of volunteers in half and gave both a text description detailing a real robbery. In the text there were true statements, in green, and false statements, in red. Some of the false statements made the crime appear to be more violent.

After reading the text, the study participants were supposed to decide on a fair sentence. But one of the groups got interrupted with distractions. The other group completed the exercise with no distractions. Gilbert and his researchers believed the distracted group would behave in a more typical way.

The distracted group gave out substantially harsher sentences than the other group. Because they were distracted, they forgot that green sentences were true and red ones were false. They believed everything they read (in fact, Gilbert’s paper was called “You Can’t Not Believe Everything You Read).”

Gilbert’s study showed that humans tend to believe first and that we actually have to “unbelieve” if something is eventually proven to us to be false. Once study even found the place in our brain where this happens – the Right Inferior Prefrontal Cortex. This suggests that “unbelieving” causes the brain to have to work harder than believing, which happens by default. 

This brings up a three-pronged dilemma when we consider ChatGPT: it will tend to hallucinate (at least for now), users of ChatGPT will disregard that flaw when there are significant benefits to doing so, and consumers of ChatGPT generated content will believe those hallucinations without rational consideration.

When Gilbert wrote his paper, he was still 3 decades away from this dilemma, but he wrapped up with a prescient debate:

“The Spinozan hypothesis suggests that we are not by nature, but we can be by artifice, skeptical consumers of information. If we allow this conceptualization of belief to replace our Cartesian folk psychology, then how shall we use it to structure our own society? Shall we pander to our initial gullibility and accept the social costs of prior restraint, realizing that some good ideas will inevitably be suppressed by the arbiters of right thinking? Or shall we deregulate the marketplace of thought and accept the costs that may accrue when people are allowed to encounter bad ideas? The answer is not an easy one, but history suggests that unless we make this decision ourselves, someone will gladly make it for us. “

Daniel Gilbert

What Gilbert couldn’t know at the time was that “someone” might actually be a “something.”

(Image:  Etienne Girardet on Unsplash)

Does Social Media “Dumb Down” the Wisdom of Crowds?

We assume that democracy is the gold standard of sustainable political social contracts. And it’s hard to argue against that. As Winston Churchill said, “democracy is the worst form of government – except for all the others that have been tried.”

Democracy may not be perfect, but it works. Or, at least, it seems to work better than all the other options. Essentially, democracy depends on probability – on being right more often than we’re wrong.

At the very heart of democracy is the principle of majority rule. And that is based on something called Jury Theorem, put forward by the Marquis de Condorcet in his 1785 work, Essay on the Application of Analysis to the Probability of Majority Decisions. Essentially, it says that the probability of making the right decision increases when you average the decisions of as many people as possible. This was the basis of James Suroweicki’s 2004 book, The Wisdom of Crowds.

But here’s the thing about the wisdom of crowds – it only applies when those individual decisions are reached independently. Once we start influencing each other’s decision, that wisdom disappears. And that makes social psychologist Solomon Asch’s famous conformity experiments of 1951 a disturbingly significant fly in the ointment of democracy.

You’re probably all aware of the seminal study, but I’ll recap anyway. Asch gathered groups of people and showed them a card with three lines of obviously different lengths. Then he asked participants which line was the closest to the reference line. The answer was obvious – even a toddler can get this test right pretty much every time.

But unknown to the test subject, all the rest of the participants were “stooges” – actors paid to sometimes give an obviously incorrect answer. And when this happened, Asch was amazed to find that the test subjects often went against the evidence of their own eyes just to conform with the group. When wrong answers were given, a third of the subjects always conformed, 75% of the subjects conformed at least once, and only 25% stuck to the evidence in front of them and gave the right answer.

The results baffled Asch. The most interesting question to him was why this was happening. Were people making a decision to go against their better judgment – choosing to go with the crowd rather than what they were seeing with their own eyes? Or was something happening below the level of consciousness? This was something Solomon Asch wondered about right until his death in 1996. Unfortunately, he never had the means to explore the question further.

But, in 2005, a group of researchers at Emory University, led by Gregory Berns, did have a way. Here, Asch’s experiment was restaged, only this time participants were in a fMRI machine so Bern and his researchers could peak at what was actually happening in their brains. The results were staggering.

They found that conformity actually changes the way our brain works. It’s not that we change what we say to conform with what others are saying, despite what we see with our own eyes. What we see is changed by what others are saying.

If, Berns and his researchers reasoned, you were consciously making a decision to go against the evidence of your own eyes just to conform with the group, you should see activity in the frontal areas of our brain that are engaged in monitoring conflicts, planning and other higher-order mental activities.

But that isn’t what they found. In those participants that went along with obviously incorrect answers from the group, the parts of the brain that showed activity were only in the posterior parts of the brain – those that control spatial awareness and visual perception. There was no indication of an internal mental conflict. The brain was actually changing how it processed the information it was receiving from the eyes.

This is stunning. It means that conformity isn’t a conscious decision. Our desire to conform is wired so deeply in our brains, it actually changes how we perceive the world. We never have the chance to be objectively right, because we never realize we’re wrong.

But what about those that went resisted conformity and stuck to the evidence they were seeing with their own eyes? Here again, the results were fascinating. The researchers found that in these cases, they saw a spike of activity in the right amygdala and right caudate nucleus – areas involved in the processing of strong emotions, including fear, anger and anxiety. Those that stuck to the evidence of their own eyes had to overcome emotional hurdles to do so. In the published paper, the authors called this the “pain of independence.”

This study highlights a massively important limitation in the social contract of democracy. As technology increasingly imposes social conformity on our culture, we lose the ability to collectively make the right decision. Essentially, is shows that this effect not only erases the wisdom of crowds, but actively works against it by exacting an emotional price for being an independent thinker.

The Physical Foundations of Friendship

It’s no secret that I worry about what the unintended consequences might be for us as we increasingly substitute a digital world for a physical one. What might happen to our society as we spend less time face-to-face with people and more time face-to-face with a screen?

Take friendship, for example. I have written before about how Facebook friends and real friends are not the same thing. A lot of this has to do with the mental work required to maintain a true friendship. This cognitive requirement led British anthropologist Robin Dunbar to come up with something called Dunbar’s Number – a rough rule-of-thumb that says we can’t really maintain a network of more than 150 friends, give or take a few.

Before you say, “I have way more friends on Facebook than that,” realize that I don’t care what your Facebook Friend count is. Mine numbers at least 3 times more than Dunbar’s 150 limit. But they are not all true friends. Many are just the result of me clicking a link on my laptop. It’s quick, it’s easy, and there is absolutely no requirement to put any skin in the game. Once clicked, I don’t have to do anything to maintain these friendships. They are just part of a digital tally that persists until I might click again, “unfriending” them. Nowhere is the ongoing physical friction that demands the maintenance required to keep a true friendship from slipping into entropy.

So I was wondering – what is that magical physical and mental alchemy that causes us to become friends with someone in the first place? When we share physical space with another human, what is the spark that causes us to want to get to know them better? Or – on the flip side – what are the red flags that cause us to head for the other end of the room to avoid talking to them? Fortunately, there is some science that has addressed those questions.

We become friends because of something in sociology call homophily – being like each other. In today’s world, that leads to some unfortunate social consequences, but in our evolutionary environment, it made sense. It has to do with kinship ties and what ethologist Richard Dawkins called The Selfish Gene. We want family to survive to pass on our genes. The best way to motivate us to protect others is to have an emotional bond to them. And it just so happens that family members tend to look somewhat alike. So we like – or love – others who are like us.

If we tie in the impact of geography over our history, we start to understand why this is so. Geography that restricted travel and led to inbreeding generally dictated a certain degree of genetic “sameness” in our tribe. It was a quick way to sort in-groups from out-groups. And in a bloodier, less politically correct world, this was a matter of survival.

But this geographic connection works both ways. Geographic restrictions lead to homophily, but repeated exposure to the same people also increases the odds that you’ll like them. In psychology, this is called mere-exposure effect.

In these two ways, the limitations of a physical world has a deep, deep impact on the nature of friendship. But let’s focus on the first for a moment. 

It appears we have built-in “friend detectors” that can actually sense genetic similarities. In a rather fascinating study, Nicholas Christakis and James Fowler found that friends are so alike genetically, they could actually be family. If you drill down to the individual building blocks of a gene at the nucleotide level, your friends are as alike genetically to you as your fourth cousin. As Christakis and Fowler say in their study, “friends may be a kind of ‘functional kin’.”

This shows how deeply friendships bonds are hardwired into us. Of course, this doesn’t happen equally across all genes. Evolution is nothing if not practical. For example, Christakis and Fowler found that specific systems do stay “heterophilic” (not alike) – such as our immune system. This makes sense. If you have a group of people who stay in close proximity to each other, it’s going to remain more resistant to epidemics if there is some variety in what they’re individually immune to. If everyone had exactly the same immunity profile, the group would be highly resistant to some bugs and completely vulnerable to others. It would be putting all your disease prevention eggs in one basket.

But in another example of extreme genetic practicality, how similar we smell to our friends can be determined genetically.  Think about it. Would you rather be close to people who generally smell the same, or those that smell different? It seems a little silly in today’s world of private homes and extreme hygiene, but when you’re sharing very close living quarters with others and there’s no such thing as showers and baths, how everyone smells becomes extremely important.

Christakis and Fowler found that our olfactory sensibilities tend to trend to the homophilic side between friends. In other words, the people we like smell alike. And this is important because of something called olfactory fatigue. We use smell as a difference detector. It warns us when something is not right. And our nose starts to ignore smells it gets used to, even offensive ones. It’s why you can’t smell your own typical body odor. Or, in another even less elegant example, it’s why your farts don’t stink as much as others. 

Given all this, it would make sense that if you had to spend time close to others, you would pick people who smelled like you. Your nose would automatically be less sensitive to their own smells. And that’s exactly what a new study from the Weizmann Institute of Science found. In the study, the scent signatures of complete strangers were sampled using an electronic sniffer called an eNose. Then the strangers were asked to engage in nonverbal social interactions in pairs. After, they were asked to rate each interaction based on how likely they would be to become friends with the person. The result? Based on their smells alone, the researchers were able to predict with 71% accuracy who would become friends.

The foundations of friendship run deep – down to the genetic building blocks that make us who we are. These foundations were built in a physical world over millions of years. They engage senses that evolved to help us experience that physical world. Those foundations are not going to disappear in the next decade or two, no matter how addictive Facebook or TikTok becomes. We can continue to layer technology over these foundations, but to deny them it to ignore human nature.

Using Science for Selling: Sometimes Yes, Sometimes No

A recent study out of Ohio State University seems like one of those that the world really didn’t need. The researchers were exploring whether introducing science into the marketing would help sell chocolate chip cookies.

And to us who make a living in marketing, this is one of those things that might make us say “Duh, you needed research to tell us that? Of course you don’t use science to sell chocolate chip cookies!”

But bear with me, because if we keep asking why enough, we can come up with some answers that might surprise us.

So, what did the researchers learn? I quote,

“Specifically, since hedonic attributes are associated with warmth, the coldness associated with science is conceptually disfluent with the anticipated warmth of hedonic products and attributes, reducing product valuation.”

Ohio State Study

In other words – much simpler and fewer in number – science doesn’t help sell cookies. And it’s because our brains think differently about some things than other.

For example, a study published in the journal Computers in Human Behavior (Casado-Aranda, Sanchez-Fernandez and Garcia) found that when we’re exposed to “hedonic” ads – ads that appeal to pleasurable sensations – the parts of our brain that retrieve memories kicks in. This isn’t true when we see utilitarian ads. Predictably, we approach those ads as a problem to be solved and engage the parts of our brain that control working memory and the ability to focus our attention.

Essentially, these two advertising approaches take two different paths in our awareness, one takes the “thinking” path and one takes the “feeling” path. Or, as Nobel Laureate Daniel Kahneman would say, one takes the “thinking slow” path and one takes the “thinking fast” path.

Yet another study begins to show why this may be so. Let’s go back to chocolate chip cookies for a moment. When you smell a fresh baked cookie, it’s not just the sensory appeal “in the moment” that makes the cookie irresistible. It’s also the memories it brings back for you. We know that how things smell is a particularly effective way to trigger this connection with the past. Certain smells – like that of cookies just out of the oven – can be the shortest path between today and some childhood memory. These are called associative memories. And they’re a big part of “feeling” something rather than just “thinking” about it.

At the University of California – Irvine – Neuroscientists discovered a very specific type of neuron in our memory centers that oversee the creation of new associative memories. They’re called “fan cells” and it seems that these neurons are responsible for creating the link between new input and those emotion-inducing memories that we may have tucked away from our past. And – critically – it seems that dopamine is the key to linking the two. When our brains “smell” a potential reward, it kicks these fan cells into gear and our brain is bathed in the “warm fuzzies.” Lead research Kei Igarashi, said,

“We never expected that dopamine is involved in the memory circuit. However, when the evidence accumulated, it gradually became clear that dopamine is involved. These experiments were like a detective story for us, and we are excited about the results.”

Kei Igarashi – University of California – Irvine

Not surprisingly – as our first study found – introducing science into this whole process can be a bit of a buzz kill. It would be like inviting Bill Nye the Science Guy to teach you about quantum physics during your Saturday morning cuddle time.

All of this probably seems overwhelmingly academic to you. Selling something like chocolate chip cookies isn’t something that should take three different scientific studies and strapping several people inside a fMRI machine to explain. We should be able to rely on our guts, and our guts know that science has no place in a campaign built on an emotional appeal.

But there is a point to all this. Different marketing approaches are handled by different parts of the brain, and knowing that allows us to reinforce our marketing intuition with a better understanding of why we humans do the things we do.

Utilitarian appeals activate the parts of the brain that are front and center, the data crunching, evaluating and rational parts of our cognitive machinery.

Hedonic appeals probe the subterranean depths of our brains, unpacking memories and prodding emotions below the thresholds of us being conscious of the process. We respond viscerally – which literally means “from our guts”.

If we’re talking about selling chocolate chip cookies, we have moved about as far towards the hedonic end of the scale as we can. At the other end we would find something like motor oil – where scientific messaging such as “advanced formulation” or “proven engine protection” would be more persuasive. But almost all other products fall somewhere in between. They are a mix of hedonic and utilitarian factors. And we haven’t even factored in the most significant of all consumer considerations – risk and how to avoid it. Think how complex things would get in our brains if we were buying a new car!

Buying chocolate chip cookies might seem like a no brainer – because – well – it almost is. Beyond dosing our neural pathways with dopamine, our brains barely kick in when considering whether to grab a bag of Chips Ahoy on our next trip to the store. In fact, the last thing you want your brain to do when you’re craving chewy chocolate is to kick in. Then you would start considering things like caloric intake and how you should be cutting down on processed sugar. Chocolate chip cookies might be a no-brainer, but almost nothing else in the consumer world is that simple.

Marketing is relying more and more on data. But data is typically restricted to answering “who”, “what”, “when” and “where” questions. It’s studies like the ones I shared here that start to pick apart the “why” of marketing.

And when things get complex, asking “why” is exactly what we need to do.

Why Our Brains Struggle With The Threat Of Data Privacy

It seems contradictory. We don’t want to share our personal data but, according to a recent study reported on by MediaPost’s Laurie Sullivan, we want the brands we trust to know us when we come shopping. It seems paradoxical.

But it’s not — really.  It ties in with the way we’ve always been thinking.

Again, we just have to understand that we really don’t understand how the data ecosystem works — at least, not on an instant and intuitive level. Our brains have no evolved mechanisms that deal with new concepts like data privacy. So we have borrowed other parts of the brain that do exist. Evolutionary biologists call this “exaption.”

For example, the way we deal with brands seems to be the same way we deal with people — and we have tons of experience doing that. Some people we trust. Most people we don’t. For the people we trust, we have no problem sharing something of our selves. In fact, it’s exactly that sharing that nurtures relationships and helps them grow.

It’s different with people we don’t trust. Not only do we not share with them, we work to avoid them, putting physical distance between us and them. We’d cross to the other side of the street to avoid bumping into them.

In a world that was ordered and regulated by proximity, this worked remarkably well. Keeping our enemies at arm’s length generally kept us safe from harm.

Now, of course, distance doesn’t mean the same thing it used to. We now maneuver in a world of data, where proximity and distance have little impact. But our brains don’t know that.

As I said, the brain doesn’t really know how digital data ecosystems work, so it does its best to substitute concepts it has evolved to handle those it doesn’t understand at an intuitive level.

The proxy for distance the brain seems to use is task focus. If we’re trying to do something, everything related to that thing is “near” and everything not relevant to it is “far. But this is an imperfect proxy at best and an outright misleading one at worst.

For example, we will allow our data to be collected in order to complete the task. The task is “near.” In most cases, the data we share has little to do with the task we’re trying to accomplish. It is labelled by the brain as “far” and therefore poses no immediate threat.

It’s a bait and switch tactic that data harvesters have perfected. Our trust-warning systems are not engaged because there are no proximate signs to trigger them. Any potential breaches of trust happen well after the fact – if they happen at all. Most times, we’re simply not aware of where our data goes or what happens to it. All we know is that allowing that data to be collected takes us one step closer to accomplishing our task.

That’s what sometimes happens when we borrow one evolved trait to deal with a new situation:  The fit is not always perfect. Some aspects work, others don’t.

And that is exactly what is happening when we try to deal with the continual erosion of online trust. In the moment, our brain is trying to apply the same mechanisms it uses to assess trust in a physical world. What we don’t realize is that we’re missing the warning signs our brains have evolved to intuitively look for.

We also drag this evolved luggage with us when we’re dealing with our favorite brands. One of the reasons you trust your closest friends is that they know you inside and out. This intimacy is a product of a physical world. It comes from sharing the same space with people.

In the virtual world, we expect the brands we know and love to have this same knowledge of us. It frustrates us when we are treated like a stranger. Think of how you would react if the people you love the most gave you the same treatment.

This jury-rigging of our personal relationship machinery to do double duty for the way we deal with brands may sound far-fetched, but marketing brands have only been around for a few hundred years. That is just not enough time for us to evolve new mechanisms to deal with them.

Yes, the rational, “slow loop” part of our brains can understand brands, but the “fast loop” has no “brand” or “data privacy” modules. It has no choice but to use the functional parts it does have.

As I mentioned in a previous post, there are multiple studies that indicate that it’s these parts of our brain that fire instantly, setting the stage for all the rationalization that will follow. And, as our own neuro-imaging study showed, it seems that the brain treats brands the same way it treats people.

I’ve been watching this intersection between technology and human behaviour for a long time now. More often than not, I see this tendency of the brain to make split-section decisions in environments where it just doesn’t have the proper equipment to make those decisions. When we stop to think about these things, we believe we understand them. And we do, but we had to stop to think. In the vast majority of cases, that’s just not how the brain works.

Media: The Midpoint of the Stories that Connect Us

I’m in the mood for navel gazing: looking inward.

Take the concept of “media,” for instance. Based on the masthead above this post, it’s what this site — and this editorial section — is all about. I’m supposed to be on the “inside” when it comes to media.

But media is also “inside” — quite literally. The word means “middle layer,” so it’s something in between.

There is a nuance here that’s important. Based on the very definition of the word, it’s something equidistant from both ends. And that introduces a concept we in media must think about: We have to meet our audience halfway. We cannot take a unilateral view of our function.

When we talk about media, we have to understand what gets passed through this “middle layer.” Is it information? Well, then we have to decide what information is. Again, the etymology of the word “inform” shows us that informing someone is to “give form to their mind.” But that mind isn’t a blank slate or a lump of clay to be molded as we want. There is already “form” there. And if, through media, we are meeting them halfway, we have to know something about what that form may be.

We come back to this: Media is the midpoint between what we, the tellers,  believe, and what we want our audience to believe. We are looking for the shortest distance between those two points. And, as self-help author Patti Digh wrote, “The shortest distance between two people is a story.”

We understand the world through stories — so media has become the platform for the telling of stories. Stories assume a common bond between the teller and the listener. It puts media squarely in the middle ground that defines its purpose, the point halfway between us. When we are on the receiving end of a story, our medium of choice is the one closest to us, in terms of our beliefs and our world narrative. These media are built on common ideological ground.

And, if we look at a recent study that helps us understand how the brain builds models of the things around us, we begin to understand the complexity that lies within a story.

This study from the Max Planck Institute for Human Cognitive and Brain Sciences shows that our brains are constantly categorizing the world around us. And if we’re asked to recognize something, our brains have a hierarchy of concepts that it will activate, depending on the situation. The higher you go in the hierarchy, the more parts of your brain that are activated.

For example, if I asked you to imagine a phone ringing, the same auditory centers in your brain that activate when you actually hear the phone would kick into gear and give you a quick and dirty cognitive representation of the sound. But if I asked you to describe what your phone does for you in your life, many more parts of your brain would activate, and you would step up the hierarchy into increasingly abstract concepts that define your phone’s place in your own world. That is where we find the “story” of our phone.

As psychologist Robert Epstein  says in this essay, we do not process a story like a computer. It is not data that we crunch and analyze. Rather, it’s another type of pattern match, between new information and what we already believe to be true.

As I’ve said many times, we have to understand why there is such a wide gap in how we all interpret the world. And the reason can be found in how we process what we take in through our senses.

The immediate sensory interpretation is essentially a quick and dirty pattern match. There would be no evolutionary purpose to store more information than is necessary to quickly categorize something. And the fidelity of that match is just accurate enough to do the job — nothing more.

For example, if I asked you to draw a can of Coca-Cola from memory, how accurate do you think it would be? The answer, proven over and over again, is that it probably wouldn’t look much like the “real thing.”

That’s coming from one sense, but the rest of your senses are just as faulty. You think you know how Coke smells and tastes and feels as you drink it, but these are low fidelity tags that act in a split second to help us recognize the world around us. They don’t have to be exact representations because that would take too much processing power.

But what’s really important to us is our “story” of Coke. That was clearly shown in one of my favorite neuromarketing studies, done at Baylor University by Read Montague.

He and his team reenacted the famous Pepsi Challenge — a blind taste test pitting Coke against Pepsi. But this time, they scanned the participant’s brains while they were drinking. The researchers found that when Coke drinkers didn’t know what they were drinking, only certain areas of their brains activated, and it didn’t really matter if they were drinking Coke or Pepsi.

But when they knew they were drinking Coke, suddenly many more parts of the brain started lighting up, including the prefrontal cortex, the part of the brain that is usually involved in creating our own personal narratives to help us understand our place in the world.

And while the actual can of Coke doesn’t change from person to person, our Story of Coke can be an individual to us as our own fingerprints.

We in the media are in the business of telling stories. This post is a story. Everything we do is a story. Sometimes they successfully connect with others, and sometimes they don’t. But in order to make effective use of the media we chose as a platform, we must remember we can only take a story halfway. On the other end there is our audience, each of whom has their own narratives that define them. Media is the middle ground where those two things connect.