Category Archives: Cognition

Prospect Theory, Back Burners and Relationship Risk

What does relationship infidelity and consumer behavior have in common? Both are changing, thanks to technology – or, more specifically – the intersection between technology and our brains. And for you regular readers, you know that stuff is right in my wheelhouse.

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Dr. Michelle Drouin

So I was fascinated by a recent presentation given by Dr. Michelle Drouin from Purdue University. She talked about how connected technologies are impacting the way we think about relationship investment.

The idea of “investing” in a relationship probably paints in a less romantic light then we typically think of, but it’s an accurate description. We calculate odds and evaluate risk. It’s what we do. Now, in the case of love, an admittedly heuristic process becomes even less rational. Our subliminal risk appraisal system is subjugated by a volatile cocktail of hormones and neurotransmitters. But – at the end of the day – we calculate odds.

If you take all this into account, Dr. Drouin’s research into “back burners” becomes fascinating, if not all that surprising. In the paper, back burners are defined as “a desired potential or continuing romantic/sexual partner with whom one communicates, but to whom one is not exclusively committed.” “Back burners” are our fall back bets when it comes to relationships or sexual liaisons. And they’re not exclusive to single people. People in committed relationships also keep a stable of “back burners.” Women keep an average of 4 potential “relationship” candidates from their entire list of contacts and 8 potential “liaison” candidates. Men, predictably, keep more options open. Male participants in the study reported an average of over 8 “relationship” options and 26 liaison “back burners.” Drouin’s hypothesis is that this number has recently jumped thanks to technology, especially with the connectivity offered through social media. We’re keeping more “back burners” because we can.

What does this have to do with advertising? The point I’m making is that this behavior is not unique. Humans treat pretty much everything like an open marketplace. We are constantly balancing risk and reward amongst all the options that are open to us, subconsciously calculating the odds. It’s called Prospect Theory. And, thanks to technology, that market is much larger than it’s ever been before. In this new world, our brain has become a Vegas odds maker on steroids.

In Drouin’s research, it appears that new technologies like Tinder, What’sapp and Facebook have had a huge impact on how we view relationships. Our fidelity balance has been tipped to the negative. Because we have more alternatives – and it’s easier to stay connected with those alternatives and keep them on the “back burner” – the odds are worth keeping our options open. Monogamy may not be our best bet anymore. Facebook is cited in one-third of all divorce cases in the U.K. And in Italy, evidence from the social messaging app What’sapp shows up in nearly half of the divorce proceedings.

So, it appears that humans are loyal – until a better offer with a degree of risk we can live with comes along.

This brings us back to our behaviors in the consumer world. It’s the same mental process, applied in a different environment. In this environment, relationships are defined as brand loyalty. And, as Emanuel Rosen and Itamar Simonson show in their book Absolute Value, we are increasingly keeping our options open in more and more consumer decisions. When it comes to buying stuff – even if we have brand loyalty – we are increasingly aware of the “back burners” available to us.

 

 

 

Why Our Brains are Blocking Ads

On Mediapost alone in the last three months, there have been 172 articles written that have included the words “ad blockers” or “ad blocking.” That’s not really surprising, given that Mediapost covers the advertising biz and ad blocking is killing that particular biz, to the tune of an estimated loss of $41 billion in 2016. eMarketer estimates 70 million Americans, or 1 out of every 4 people online, uses ad blockers.

Paul Verna, an eMarketer Senior Analyst said “Ad blocking is a detriment to the entire advertising ecosystem, affecting mostly publishers, but also marketers, agencies and others whose businesses depend on ad revenue.” The UK’s culture Secretary, John Whittingdale, went even further, saying that ad blocking is a “modern-day protection racket.”

Here’s the problem with all this finger pointing. If you’re looking for a culprit to blame, don’t look at the technology or the companies deploying that technology. New technologies don’t cause us to change our behaviors – they enable behaviors that weren’t an option before. To get to the bottom of the growth of ad blocking, we have to go to the common denominator – the people those ads are aimed at. More specifically, we have to look at what’s happening in the brains of those people.

In the past, the majority of our interaction with advertising was done while our brain was idling, with no specific task in mind. I refer to this as bottom up environmental scanning. Essentially, we’re looking for something to capture our attention: a TV show, a book, a magazine article, a newspaper column. We were open to being engaged by stimuli from our environment (in other words, being activated from the “bottom up”).

In this mode, the brain is in a very accepting state. We match signals from our environment with concepts and beliefs we hold in our mind. We’re relatively open to input and if the mental association is a positive or intriguing one – we’re willing to spend some time to engage.

We also have to consider the effect of priming in this state. Priming sets a subconscious framework for the brain that then affects any subsequent mental processing. The traditional prime that was in place when we were exposed to advertising was a fairly benign one: we were looking to be entertained or informed, often the advertising content was delivered wrapped in a content package that we had an affinity for (our favorite show, a preferred newspaper, etc), and advertising was delivered in discrete chunks that our brain had been trained to identify and process accordingly.

All this means that in traditional exposures to ads, our brain was probably in the most accepting state possible. We were looking for something interesting, we were primed to be in a positive frame of mind and our brains could easily handle the contextual switches required to consider an ad and it’s message.

We also have to remember that we had a relatively static ad consumption environment that usually matched our expectations of how ads would be delivered. We expected commercial breaks in TV shows. We didn’t expect ads in the middle of a movie or book, two formats that required extended focusing of attention and didn’t lend themselves to mental contextual task switches. Each task switch brings with it a refocusing of attention and a brief burst of heightened awareness as our brains are forced to reassess its environment. These are fine in some environments – not in others.

Now, let’s look at the difference in cognitive contexts that accompany the deliver of most digital ads. First of all, when we’re online on our desktop or engaged with a mobile device, it’s generally in what I’ll call a “top down foraging” mode. We’re looking for something specific and we have intent in mind. This means there’s already a task lodged in our working memory (hence “top down”) and our attentional spotlight is on and focused on that task. This creates a very different environment for ad consumption.

When we’re in foraging mode, we suddenly are driven by an instinct that is as old as the human race (actually, much older than that): Optimal Foraging Theory. In this mode, we are constantly filtering the stimuli of our environment to see what is relevant to our intent. It’s this filtering that causes attentional blindness to non-relevant factors – whether they be advertising banners or people dressed up like gorillas. This filtering happens on a subconscious basis and the brain uses a primal engine to drive it – the promise of reward or the frustration of failure. When it comes to foraging – for food or for information – frustration is a feature, not a bug.

Our brains have a two loop learning process. It starts with a prediction – what psychologists and economists call “expected utility.” We mentally place bets on possible outcomes and go with the one that promises the best reward. If we’re right, the reward system of the brain gives us a shot of dopamine. Things are good. But if we bet wrong, a different part of the brain kicks in: the right anterior insula, the adjacent right ventral prefrontal cortex and the anterior cingulate cortex. Those are the centers of the brain that regulate pain. Nature is not subtle about these things – especially when the survival of the species depends on it. If we find what we’re looking for, we get a natural high. If we don’t, it’s actually causes us pain – but not in a physical way. We know it as frustration. Its purpose is to encourage us to not make the same mistake twice

The reason we’re blocking ads is that in the context those ads are being delivered, irrelevant ads are – quite literally – painful. Even relevant ads have a very high threshold to get over. Ad blocking has little to do with technology or “protection rackets” or predatory business practices. It has to do with the hardwiring of our brains. So if the media or the ad industry want to blame something or someone, let’s start there.

Where Context Comes From

Fellow Spinner Cory Treffiletti told you last week that data without context is noise.

Absolutely right.

I want to continue that conversation, because it’s an important one. It’s all about context. So let’s talk a little more about context. And specifically how we decide what makes up that context.

You might have seen or heard the hubbub that emerged around a tweet from Neil Degrasse Tyson a month ago: “Earth needs a virtual country: #Rationalia, with a one-line Constitution: All policy shall be based on the weight of evidence”

Nice thought, but it ignited a social media shit-storm. Which was entirely predictable. Because we don’t want to be rational. We want to be human. Did 79 episodes of Star Trek teach us nothing?

The biggest beef against #Rationalia was that evidence is typically in the eyes of the beholder. It’s all a matter of context. I’m guessing that the policies that come from evidence in the hands of Republicans will not bear much resemblance to policies that come from the evidence of Democrats. The evidence could be the same but the context is different, because Democrats and Republicans think differently.

Like Treffiletti said – evidence without context is just noise. And our context is only marginally based on evidence. And that’s why #Rationalia – as intellectually attractive as it might be – won’t work.

We as humans understand the world through something called sense making. This is the process we use to build context. In 2006, psychologist Gary Klein shed new light on how we make sense of the world. We start with a frame that captures our current understanding of the situation and depending on the evidence presented to us, we decide whether to elaborate our frame or discard it and create a new frame. So, sensemaking is really an iterative loop that is constantly using our current frame as a reference point.

But here’s the thing. What we consider as evidence depends on the frame we already have in place. It’s the filter that determines what data we pay attention to. And much as Neil Degrasse Tyson would like the governments of the world to be totally unbiased in the filtering of evidence, “that dog just won’t hunt.” It can’t – because we can’t consider data without some context to put it in.

Perhaps someday artificial intelligence will advance to the point where it can pull unbiased context out of random data. Maybe computers will be able to do what we’re unable to – make sense of the noise without assuming a pre-existing frame. But we’re not there yet. And even if we were, we would simply look at the conclusions of the computer and decide whether we agree with them or not. As long as humans are in charge, there will always be a biased filter in place.

So back to Cory’s column. If context is so important, think about where that context is coming from. Who is defining the context and what frame are they operating from? That in turn will define what data you consider and how you consider it.

Perhaps the most important decision before considering data is to be totally clear about what the goal is. Goals, together with experience, form the underpinning of beliefs. Frames are then built on those beliefs. Context comes from those frames. And context is the filter we apply to evidence.

Happiness as a Corporate Metric

Costa Rica is the happiest place on earth. The least happy place on earth? That would be Botswana.

At least, those are the results according to by the things measured by the Happy Planet Index. The index is a measure of three factors, life expectancy, Experienced Well Being and Ecological Footprint. Western nations tend to do very well on the first two measures, but suck at the third. The index is looking for balance – being happy without raping and pillaging the earth. Here in North America, we still have a ways to go in that department.

In another study – the 2015 UN’s World Happiness Report – a different weighting of factors treated the western world a little better. When we tip the balance towards individual happiness and away from the environment and sustainability; Denmark, Switzerland, Iceland, Norway, Finland and Canada topped the rankings. Apparently, snow is good for the soul. At the bottom of the list were Benin, Afghanistan, Togo, Syria and Burundi (it’s hard to believe anywhere scored worse than Syria – mental note: stroke Burundi off my travel bucket list).

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The 4th King of Bhutan: Jigme Singye Wangchuck

In 1971, the 4th Dragon King of Bhutan, Jigme Singye Wangchuck was so enamored with the idea of happiness as a goal that he introduced a new measure of a nation’s worth: Gross National Happiness. He believed that the western world’s obsession with materialism represented by Gross National Product shouldn’t be the sole measure of progress. Things like sustainable development, care for the environment, good governance and preservation of culture deserved to be measured as well. In the 45 years since the idea of Gross National Happiness was first floated by his Royal Dragonship, it’s been slow to take, but perhaps it’s time has come. By the way, in the UN survey, Bhutan was in the middle of the pack for happiness, ranking 84th out of 157 countries.

Happiness should be important with companies as well. There’s even an investment fund that invests exclusively in companies with happy employees. But happiness can be an elusive goal, especially when we try to wrestle it to the ground in the way of a hard performance metric in a corporate environment. What exactly are we measuring when we measure happiness? And who’s happiness are we measuring? Our customers? Our shareholders? Our employees? All of the above?

Let’s single out employees. Companies like Zappos and Southwest Airlines have tried to make employee happiness a metric that matters. But what makes an employee happy? Perhaps we can find a clue in a recent survey from Ypulse that asked Millennials which companies they’d most like to work at. The top 10 answers were:

  1. Google
  2. Apple
  3. Disney
  4. Non-profit/charity
  5. School/community/university
  6. Hospital
  7. U.S. government
  8. Myself/my own company
  9. Amazon
  10. FBI/CIA

It’s an interesting list. It’s not the list you’d expect from a generation that simply wants to get rich quick. You don’t work at a hospital or the FBI if you want to make big bucks. This is a list that comes from people who want to make a difference. They want meaning. In the words of Steve Jobs, they “want to put a ding in the universe.”

I get that. I recently discovered just how hard happiness is to pin down. After selling my company, I was fortunate enough to achieve financial independence and retire at 51. I should have been deliriously happy, right? Well, I wasn’t suicidal by any means, but I would say my level of happiness actually decreased after I tried retirement. I was at the other end of my career path from Millennials, but meaning remained just as important to me.

In a study of retirement satisfaction published in the Journal of Financial Counselling and Planning, Sarah Arsebedo and Martin Seay found that psychologist Martin Seligman’s positive psychological attributes, referred to as PERMA (Positive emotions, Engagement, [Family] Relationships, Meaning and Accomplishment) – don’t go away when we retire. These things are necessary to happiness. For men in particular – and increasingly so with women – we rely on our jobs to provide many of these. This was certainly true for me.

It’s good we’re paying more attention to happiness. But it’s also important that we understand what we’re talking about when we refer to happiness. It has little to do with monetary measures of success. Whether we’re talking nations, corporations or employees, it turns out that happiness means a sense of interconnectedness, contribution and personal values. It means living beyond ourselves and leaving some footprint that won’t fade when we no longer walk this earth.

Ultimately, it means doing stuff that matters.

 

What Would a “Time Well Spent” World Look Like?

I’m worried about us. And it’s not just because we seem bent on death by ultra-conservative parochialism and xenophobia. I’m worried because I believe we’re spending all our time doing the wrong things. We’re fiddling while Rome burns.

Technology is our new drug of choice and we’re hooked. We’re fascinated by the trivial. We’re dumping huge gobs of time down the drain playing virtual games, updating social statuses, clicking on clickbait and watching videos of epic wardrobe malfunctions. Humans should be better than this.

It’s okay to spend some time doing nothing. The brain needs some downtime. But something, somewhere has gone seriously wrong. We are now spending the majority of our lives doing useless things. TV used to be the biggest time suck, but in 2015, for the first time ever, the boob tube was overtaken by time spent with mobile apps. According to a survey conducted by Flurry, in the second quarter of 2015 we spent about 2.8 hours per day watching TV. And we spent 3.3 hours on mobile apps. That’s a grand total of 6.1 hours per day or one third of the time we spend awake. Yes, both things can happen at the same time, so there is undoubtedly overlap, but still- that’s a scary-assed statistic!

And it’s getting worse. In a previous Flurry poll conducted in 2013, we spent a total of 298 hours between TV and mobile apps versus 366 hours in 2015. That’s a 22.8% increase in just two years. We’re spending way more time doing nothing. And those totals don’t even include things like time spent in front of a gaming console. For kids, tack on an average of another 10 hours per week and you can double that for hard-core male gamers. Our addiction to gaming has even led to death in extreme cases.

Even in the wildest stretches of imagination, this can’t qualify as “time well spent.”

We’re treading on very dangerous and very thin ice here. And, we no longer have history to learn from. It’s the first time we’ve ever encountered this. Technology is now only one small degree of separation from plugging directly into the pleasure center of our brains. And science has proven that a good shot of self-administered dopamine can supersede everything –water, food, sex. True, these experiments were administered on rats – primarily because it’s been unethical to go too far on replicating the experiments with humans – but are you willing to risk the entire future of mankind on the bet that we’re really that much smarter than rats?

My fear is that technology is becoming a slightly more sophisticated lever we push to get that dopamine rush. And developers know exactly what they’re doing. They are making that lever as addictive as possible. They are pushing us towards the brink of death by technological lobotomization. They’re lulling us into a false sense of security by offering us the distraction of viral videos, infinitely scrolling social notification feeds and mobile game apps. It’s the intellectual equivalent of fast food – quite literally “brain candy.

Here the hypocrisy of for-profit interest becomes evident. The corporate response typically rests on individual freedom of choice and the consumer’s ability to exercise will power. “We are just giving them what they’re asking for,” touts the stereotypical PR flack. But if you have an entire industry with reams of developers and researchers all aiming to hook you on their addictive product and your only defense is the same faulty neurological defense system that has already fallen victim to fast food, porn, big tobacco, the alcohol industry and the $350 billion illegal drug trade, where would you be placing your bets?

Technology should be our greatest achievement. It should make us better, not turn us into a bunch of lazy screen-addicted louts. And it certainly could be this way. What would it mean if technology helped us spend our time well? This is the hope behind the Time Well Spent Manifesto. Ethan Harris, a design ethicist and product philosopher at Google is one of the co-directors. Here is an excerpt from the manifesto:

We believe in a new kind of design, that lets us connect without getting sucked in. And disconnect, without missing something important.

And we believe in a new kind economy that’s built to help us spend time well, where products compete to help us live by our values.

I believe in the Manifesto. I believe we’re being willingly led down a scary and potentially ruinous path. Worst of all, I believe there is nothing we can – or will – do about it. Problems like this are seldom solved by foresight and good intentions. Things only change after we drive off the cliff.

The problem is that most of us never see it coming. And we never see it coming because we’re too busy watching a video of masturbating monkeys on Youtube.

Can Stories Make Us Better?

In writing this column, I often put ideas on the shelf for a while. Sometimes, world events conspire to make one of these shelved ideas suddenly relevant. This happened this past weekend.

The idea that caught my eye some months ago was an article that explored whether robots could learn morality by reading stories. On the face of it, it was mildly intriguing. But early Sunday morning as the heartbreaking news filtered to me from Orlando, a deeper connection emerged.

When we speak of unintended consequence, which we have before, the media amplification of acts of terror are one of them. The staggeringly sad fact is that shocking casualty numbers have their own media value. And that, said one analyst who was commenting on ways to deal with terrorism, is a new reality we have to come to terms with. When we in the media business make stories news worthy we assign worth not just for news consumers but also to newsmakers – those troubled individuals who have the motivation and the means to blow apart the daily news cycle.

This same analyst, when asked how we deal with terrorism, made the point you can’t prevent lone acts of terrorism. The only answer is to use that same network of cultural connections we use to amplify catastrophic events to create an environment that dampens rather than intensifies violent impulse. We in the media and advertising industries have to use our considerable skills in setting cultural contexts to create an environment that reduces the odds of a violent outcome. And sadly, this is a game of odds. There are no absolute answers here – there is just a statistical lowering of the curve. Sometimes, despite your best efforts, the unimaginable still happens.

But how do you use the tools at our disposal to amplify morality? Here, perhaps the story I shelved some months ago can provide some clues.

In the study from Georgia Tech, Mark Riedl and Brent Harrison used stories as models of acceptable morality. For most of human history, popular culture included at least an element of moral code. We encoded the values we held most dear into our stories. It provided a base for acceptable behavior, either through positive reinforcement of commonly understood virtues (prudence, justice, temperance, courage, faith, hope and charity) or warnings about universal vices (lust, gluttony, greed, sloth, wrath, envy and pride). Sometimes these stories had religious foundations, sometimes they were secular morality fables but they all served the same purpose. They taught us what was acceptable behavior.

Stories were never originally intended to entertain. They were created to pass along knowledge and cultural wisdom. Entertainment came after when we discovered the more entertaining the story, the more effective it was at its primary purpose: education. And this is how the researchers used stories. Robots can’t be entertained, but they can be educated.

At some point in the last century, we focused on the entertainment value of stories over education and, in doing so, rotated our moral compass 180 degrees. If you look at what is most likely to titillate, sin almost always trumps sainthood. Review that list of virtues and vices and you’ll see that the stories of our current popular culture focus on vice – that list could be the programming handbook for any Hollywood producer. I don’t intend this a sermon – I enjoy Game of Thrones as much as the next person. I simply state it as a fact. Our popular culture – and the amplification that comes from it – is focused almost exclusively on the worst aspects of human nature. If robots were receiving their behavioral instruction through these stories, they would be programmed to be psychopathic moral degenerates.

For most of us, we can absorb this continual stream of anti-social programming and not be affected by it. We still know what is right and what is wrong. But in a world where it’s the “black swan” outliers that grab the news headlines, we have to think about the consequences that reach beyond the mainstream. When we abandon the moral purpose of stories and focus on their entertainment aspect, are we also abandoning a commonly understood value landscape?

If you’re looking for absolute answers here, you won’t find them. That’s just not the world we live in. And am I naïve when I say the stories we chose to tell may have an influence on isolated violent events such as happened in Orlando? Perhaps. Despite all our best intentions, Omar Mateen might still have gone horribly offside.

But all things and all people are, to some extent, products of their environment. And because we in media and advertising are storytellers, we set that cultural environment. That’s our job. Because of this, I belief we have a moral obligation. We have to start paying more attention to the stories we tell.

 

 

 

 

Ex Machina’s Script for Our Future

One of the more interesting movies I’ve watched in the past year has been Ex Machina. Unlike the abysmally disappointing Transcendence (how can you screw up Kurzweil – for God’s sake), Ex Machina is a tightly directed, frighteningly claustrophobic sci-fi thriller that peels back the moral layers of artificial intelligence one by one.

If you haven’t seen it, do so. But until you do, here’s the basic set up. Caleb Smith (Domhnall Gleeson) is a programmer at a huge Internet search company called Blue Book (think Google). He wins a contest where the prize is a week spent with the CEO, Nathan Bateman (Oscar Isaac) at his private retreat. Bateman’s character is best described as Larry Page meets Steve Jobs meets Larry Ellison meets Charlie Sheen – brilliant as hell but one messed up dude. It soon becomes apparent that the contest is a ruse and Smith is there to play the human in an elaborate Turing Test to determine if the robot Ava (Alicia Vikander) is capable of consciousness.

About half way through the movie, Bateman confesses to Smith the source of Ava’s intelligence “software.” It came from Blue Book’s own search data:

‘It was the weird thing about search engines. They were like striking oil in a world that hadn’t invented internal combustion. They gave too much raw material. No one knew what to do with it. My competitors were fixated on sucking it up, and trying to monetize via shopping and social media. They thought engines were a map of what people were thinking. But actually, they were a map of how people were thinking. Impulse, response. Fluid, imperfect. Patterned, chaotic.”

As a search behaviour guy – that sounded like more fact than fiction. I’ve always thought search data could reveal much about how we think. That’s why John Motavalli’s recent column, Google Looks Into Your Brain And Figures You Out, caught my eye. Here, it seemed, fiction was indeed becoming fact. And that fact is, when we use one source for a significant chunk of our online lives, we give that source the ability to capture a representative view of our related thinking. Google and our searching behaviors or Facebook and our social behaviors both come immediately to mind.

Motavalli’s reference to Dan Ariely’s post about micro-moments is just one example of how Google can peak under the hood of our noggins and start to suss out what’s happening in there. What makes this either interesting or scary as hell, depending on your philosophic bent, is that Ariely’s area of study is not our logical, carefully processed thoughts but our subconscious, irrational behaviors. And when we’re talking artificial intelligence, it’s that murky underbelly of cognition that is the toughest nut to crack.

I think Ex Machina’s writer/director Alex Garland may have tapped something fundamental in the little bit of dialogue quoted above. If the data we willingly give up in return for online functionality provides a blue print for understanding human thought, that’s a big deal. A very big deal. Ariely’s blog post talks about how a better understanding of micro-moments can lead to better ad targeting. To me, that’s kind of like using your new Maserati to drive across the street and visit your neighbor – it seems a total waste of horsepower. I’m sure there are higher things we can aspire to than figuring out a better way to deliver a hotels.com ad. Both Google and Facebook are full of really smart people. I’m pretty sure someone there is capable of connecting the dots between true artificial intelligence and their own brand of world domination.

At the very least, they could probably whip up a really sexy robot.

 

 

 

 

 

 

 

 

 

 

 

 

Decoupling Our Hunch Making Mechanism

Humans are hunch-making machines. We’re gloriously good at it. In fact, no one and no thing is better at coming up with a hunch. It’s what sets up apart on our planet and, thus far, nothing we’ve invented has proven to be better suited to strike the spark of intuition.

We can seemingly draw speculative guesses out of thin air – literally. From all the noise that surrounds us, we recognize potential patterns and infer significance. Scientists call them hypotheses. Artists call them artistic inspirations. Entrepreneurs call them innovations.

Whatever the label, we’re not exactly sure what happens. Mihaly Czikszentmihaly (which, in case you’re wondering, is pronounced Me-high Cheek-sent-me-high) explored where these hunches come from in his fascinating book, Creativity, The Psychology of Discovery and Invention. But despite the collective curiosity about the source of human creativity – the jury remains out. The mechanism that turns these very human gears and sparks the required connections between our synapses remains a mystery.

We’re good at making hunches. But we suck at qualifying those hunches. The reason is that we rush a hunch straight into becoming a belief. And that’s where things go off the rails. A hunch is a guess about what might be true. A belief is what we deem to be true. We go straight from what is one of many possible scenarios to the only scenario we execute against. The entire scientific method was created to counteract this very human tendency – forcing rational analysis of the hunches we churn out.

Philip Tetlock’s work on expertise in prediction shows how fragile this tendency to go from hunch to belief can make us. After all, a prediction is nothing more than a hunch of what might be. He referred to Isaiah Berlin’s 1950 essay, “The Hedgehog and the Fox.” In the essay, Berlin quotes the ancient Greek poet Archilochus, “”a fox knows many things, but a hedgehog one important thing.” Taking some poetic license, you could said that a hedgehog is more prone to moving straight from hunch to belief, where a fox tends to evaluate her hunches against multiple sources. Tetlock found that when it came to the accuracy of predictions, it was better to be a fox than a hedgehog. In some cases, much better.

But Tetlock also found that when it comes down to “crunching hunches”, machines tend to bet man hands down. It’s because humans have been programmed for thousands of generations to trust our hunches and no matter how much we fight it, we are born to treat our hunches as fact. Machines bear no such baggage.

This is an example of Moravec’s Paradox – the things that seem simple for humans are amazingly complex for machines. And vice versa. As artificial intelligence pioneer Marvin Minsky once recognized, it’s the things we do unconsciously that represent the biggest challenges for artificial intelligence, “In general, we’re least aware of what our minds do best.” Machines may never be as good as humans at creating a hunch – or, at least – we’re certainly not there yet. But machines have already outstripped humans in the ability to empirically analyze and validate multiple options.

Fellow Online Spin columnist Kaila Colbin posited this in her last column, “When Watson Comes for Your Job, Give it to Him.” As she points out, IBM’s Watson can kick any human ass when it comes to reviewing case law – or plowing through the details required for an accurate medical diagnosis – or assisting students prepare for an upcoming exam. But Watson isn’t very good at coming up with hunches. It’s because hunches aren’t rational. They’re inspirational. And machines aren’t fluent in inspiration. Not yet, anyway.

Maybe that’s why – even in something as logical as chess – the current champion isn’t a machine, or a human. It’s a combination of both. As American economist and author (Average is Over) Tyler explained in a blog post, a “striking percentage of the best or most accurate chess games of all time have been played by man-machine pairs.” Cowen shows four ways a man-machine team can outperform and they all have to do with leveraging the respective strengths of each. Humans use intuition to create hunches, and then harness the power of the machine to analyze relevant options.

Hunches have served humans very well. They will continue to do so. The trick is to decouple those hunches from the belief making mechanism that has historically accompanied it. That’s where we should let machines take over.

 

 

We’re Informed. But Are We Thoughtful?

I’m a bit of a jerk when I write. I lock myself behind closed doors in my home office. In the summer, I retreat to the most remote reaches of the back yard. The reason? I don’t want to be interrupted with human contact. If I am interrupted, I stare daggers through the interrupter and answer in short, clipped sentences. The house has to be silent. If conditions are less than ideal, my irritation is palpable. My family knows this. The warning signal is “Dad is writing.” This can be roughly translated as “Dad is currently an asshole.” The more I try to be thoughtful, the bigger the ass I am.

I suspect Henry David Thoreau was the same.  He went even further than my own backyard exile. He camped out alone for two years in Ralph Waldo Emersen’s cabin on Walden Pond. He said things like,

“I never found a companion that was so companionable as solitude.”

But Thoreau but was also a pretty thoughtful guy, who advised us that,

“As a single footstep will not make a path on the earth, so a single thought will not make a pathway in the mind. To make a deep physical path, we walk again and again. To make a deep mental path, we must think over and over the kind of thoughts we wish to dominate our lives.”

But, I ask, how can we be thoughtful when we are constantly distracted by information? Our mental lives are full of single footsteps. Even if we intend to cover the same path more than once, there are a thousand beeps, alerts, messages, prompts, pokes and flags that are beckoning us to start down a new path, in a different direction. We probably cover more ground, but I suspect we barely disturb the fallen leaves on the paths we take.

I happen to do all my reading on a tablet. I do this for three reasons; first, I always have my entire library with me and I usually have four books on the go at the same time (currently 1491, Reclaiming Conversation, Flash Boys and 50 Places to Bike Before You Die) – secondly, I like to read before I go to sleep and I don’t need to keep a light on that keeps my wife awake – and thirdly, I like to highlight passages and make notes. But there’s a trade-off I’ve had to make. I don’t read as thoughtfully as I used to. I can’t “escape” with a book anymore. I am often tempted to check email, play a quick game of 2048 or search for something on Google. Maybe the fact that my attention is always divided amongst four books is part of the problem. Or maybe it’s that I’m more attention deficit than I used to be.

There is a big difference between being informed and being thoughtful. And our connected world definitely puts the bias on the importance of information. Being connected is all about being informed. But being thoughtful requires us to remove distraction. It’s the deep paths that Thoreau was referring too. And it requires a very different mindset. Our brains are a single-purpose engine. We can either be informed or be thoughtful. We can’t be both at the same time.

090313-RatMaze

At the University of California, San Francisco, Mattiass Karlsson and Loren Frank found that rats need two very different types of cognitive activity when mastering a maze. First, when they explore a maze, certain parts of their brain are active as they’re being “informed” about their new environment. But they don’t master the maze unless they’re allowed downtime to consolidate the information into new persistent memories. Different parts of the brain are engaged, including the hippocampus. They need time to be thoughtful and create a “deep path.”

In this instance, we’re not all that different than rats. In his research, MIT’s Alex “Sandy” Pentland found that effective teams tend to cycle through two very different phases: First, they explore, gathering new information. Then, just like the thoughtful rats, they engage as a group, taking that information, digesting it and synthesizing it for future execution. Pentland found that while both are necessary, they don’t exist at the same time,

“Exploration and engagement, while both good, don’t easily coexist, because they require that the energy of team members be put to two different uses. Energy is a finite resource.”

Ironically, research is increasingly showing that are previous definitions of cognitive activity may have been off-the mark. We always assumed that “mind-wandering” or “day-dreaming” was a non-productive activity. But we’re finding out that it’s an essential part of being thoughtful. We’re actually not “wandering.” It’s just the brain’s way of synthesizing and consolidating information. We’re wearing deeper paths in the by-ways of our mind. But a constant flow of new information, delivered through digital channels, keeps us from synthesizing the information we already have. Our brain is too busy being informed to be able to make the switch to thoughtfulness. We don’t have enough cognitive energy to do both.

What price might we pay for being “informed” at the expense of being “thoughtful?” It appears that it might be significant. Technology distraction in the classroom could lower grades by close to 20 percent. And you don’t even have to be the one using the device. Just having an open screen in the vicinity might distract you enough to drop your report card from a “B” to a “C.”

Having read this, you now have two choices. You could click off to the next bit of information. Or, you could stare into space for a few minutes and be lost in your thoughts.

Chose wisely.

Consumers in the Wild

Once a Forager, Always a Forager

Your world is a much different place than the African Savanna. But over 100,000 generations of evolution that started on those plains still dictates a remarkable degree of our modern behavior.

Take foraging, for example. We evolved as hunters and gatherers. It was our primary survival instinct. And even though the first hominids are relatively recent additions to the biological family tree, strategies for foraging have been developing for millions and millions of years. It’s hardwired into the deepest and most inflexible parts of our brain. It makes sense, then, that foraging instincts that were once reserved for food gathering should be applied to a wide range of our activities.

That is, in fact, what Peter Pirolli and Stuart Card discovered two decades ago. When they looked at how we navigated online sources of information, they found that humans used the very same strategy we would have used for berry picking or gathering cassava roots. And one of the critical elements of this was something called Marginal Value.

Bounded Rationality & Foraging

It’s hard work being a forager. Most of your day – and energy – is spent looking for something to eat. The sparser the food sources in your environment, the more time you spend looking for them. It’s not surprising; therefore, that we should have some fairly well honed calculations for assessing the quality of our food sources. This is what biologist Eric Charnov called Marginal Value in 1976. It’s an instinctual (and therefore, largely subconscious) evaluation of food “patches” by most types of foragers, humans included . It’s how our brain decides whether we should stay where we are or find another patch. It would have been a very big deal 2 million – or even 100,000 – years ago.

Today, for most of us, food sources are decidedly less “patchy.” But old instincts die hard. So we did what humans do. We borrowed an old instinct and applied it to new situations. We exapted our foraging strategies and started using them for a wide range of activities where we had to have a rough and ready estimation of our return on our energy investment. Increasingly, more and more of these activities asked for an investment of cognitive processing power. And we did all this without knowing we were even doing it.

This brings us to Herbert Simon’s concept of Bounded Rationality. I believe this is tied directly to Charnov’s theorem of Marginal Value. When we calculate how much mental energy we’re going to expend on an information-gathering task, we subconsciously determine the promise of the information “patches” available to us. Then we decided to invest accordingly based on our own “bounded” rationality.

Brands as Proxies for Foraging

It’s just this subconscious calculation that has turned the world of consumerism on its ear in the last two decades. As Itamar Simonson and Emanuel Rosen explain in their book Absolute Value, the explosion of information available has meant that we are making different marginal value calculations than we would have thirty or forty years ago. We have much richer patches available, so we’re more likely to invest the time to explore them. And, once we do, the way we evaluate our consumer choices changes completely. Our modern concept of branding was a direct result of both bounded rationality and sparse information patches. If a patch of objective and reliable information wasn’t apparent, we would rely on brands as a cognitive shortcut, saving our bounded rationality for more promising tasks.

Google, The Ultimate “Patch”

In understanding modern consumer behavior, I think we have to pay much more attention to this idea of marginal value. What is the nature of the subconscious algorithm that decides whether we’re going to forage for more information or rely on our brand beliefs? We evolved foraging strategies that play a huge part in how we behave today.

For example, the way we navigate our physical environment appears to owe much to how we used to search for food. Women determine where they’re going differently than men because women used to search for food differently. Men tend to do this by orientation, mentally maintaining a spatial grid in their minds against which they plot their own location. Women do it by remembering routes. In my own research, I found split-second differences in how men and women navigated websites that seem to go back to those same foundations.

Whether you’re a man or a woman, however, you need to have some type of mental inventory of information patches available to you to in order to assess the marginal value of those patches. This is the mental landscape Google plays in. For more and more decisions, our marginal value calculation starts with a quick search on Google to see if any promising patches show up in the results. Our need to keep a mental inventory of patches can be subjugated to Google.

It seems ironic that in our current environment, more and more of our behavior can be traced back millions of years to behaviors that evolved in a world where high-tech meant a sharper rock.