Our Brain on Reviews

There’s an interesting new study that was just published about how our brain mathematically handles online reviews that I wanted to talk about today. But before I get to that, I wanted to talk about foraging a bit.

The story of how science discovered our foraging behaviors serves as a mini lesson in how humans tick. The economists of the 1940’s and 50’s discovered the world of micro-economics, based on the foundation that humans were perfectly rational – we were homo economicus. When making personal economic choices in a world of limited resources, we maximized utility. The economists of the time assumed this was a uniquely human property, bequeathed on us by virtue of the reasoning power of our superior brains.

In the 60’s, behavior ecologists knocked our egos down a peg or two. It wasn’t just humans that could do this. Foxes could do it. Starlings could do it. Pretty much any species had the same ability to seemingly make optimal choices when faced with scarcity. It was how animals kept from starving to death. This was the birth of foraging theory. This wasn’t some homo-sapien-exclusive behavior that was directed from the heights of rationality downwards. It was an evolved behavior that was built from the ground up. It’s just that humans had learned how to apply it to our abstract notion of economic utility.

Three decades later, two researchers at Xerox’s Palo Alto Research Center found another twist. Not only had our ability to forage been evolved all the way through our extensive family tree, but we seemed to borrow this strategy and apply it to entirely new situations. Peter Pirolli and Stuart Card found that when humans navigate content in online environments, the exact same patterns could be found. We foraged for information. Those same calculations determined whether we would stay in an information “patch” or move on to more promising territory.

This seemed to indicate three surprising discoveries about our behavior:

  • Much of what we think is rational behavior is actually driven by instincts that have evolved over millions of years
  • We borrow strategies from one context and apply them in another. We use the same basic instincts to find the FAQ section of a website that we used to find sustenance on the savannah.
  • Our brains seem to use Bayesian logic to continuously calculate and update a model of the world. We rely on this model to survive in our environment, whatever and wherever that environment might be.

So that brings us to the study I mentioned at the beginning of this column. If we take the above into consideration, it should come as no surprise that our brain uses similar evolutionary strategies to process things like online reviews. But the way it does it is fascinating.

The amazing thing about the brain is how it seamlessly integrates and subconsciously synthesizes information and activity from different regions. For example, in foraging, the brain integrates information from the regions responsible for wayfinding – knowing our place in the world – with signals from the dorsal anterior cingulate cortex – an area responsible for reward monitoring and executive control. Essentially, the brain is constantly updating an algorithm about whether the effort required to travel to a new “patch” will be balanced by the reward we’ll find when we get there. You don’t consciously marshal the cognitive resources required to do this. The brain does it automatically. What’s more – the brain uses many of the same resources and algorithm whether we’re considering going to McDonald’s for a large order of fries or deciding what online destination would be the best bet for researching our upcoming trip to Portugal.

In evaluating online reviews, we have a different challenge: how reliable are the reviews? The context may be new – our ancestors didn’t have TripAdvisor or AirBNB ratings for choosing the right cave to sleep in tonight – but the problem isn’t. What criteria should we use when we decide to integrate social information into our decision making process? If Thorlak the bear hunter tells me there’s a great cave a half-day’s march to the south, should I trust him? Experience has taught us a few handy rules of thumb when evaluating sources of social information: reliability of the source and the consensus of crowds. Has Thorlak ever lied to us before? Do others in the tribe agree with him? These are hardwired social heuristics. We apply them instantly and instinctively to new sources of information that come from our social network. We’ve been doing it for thousands of years. So it should come as no surprise that we borrow these strategies when dealing with online reviews.

In a neuro-scanning study from the University College of London, researchers found that reliability plays a significant role in how our brains treat social information. Once again, a well-evolved capability of the brain is recruited to help us in a new situation. The dorsomedial prefrontal cortex is the area of the brain that keeps track of our social connections. This “social monitoring” ability of the brain worked in concert with ventromedial prefrontal cortex, an area that processes value estimates.

The researchers found that this part of our brain works like a Bayesian computer when considering incoming information. First we establish a “prior” that represents a model of what we believe to be true. Then we subject this prior to possible statistical updating based on new information – in this case, online reviews. If our confidence is high in this “prior” and the incoming information is weak, we tend to stick with our initial belief. But if our confidence is low and the incoming information is strong – i.e. a lot of positive reviews – then the brain overrides the prior and establishes a new belief, based primarily on the new information.

While this seems like common sense, the mechanisms at play are interesting. The brain effortlessly pattern matches new types of information and recruits the region that is most likely to have evolved to successfully interpret that information. In this case, the brain had decided that online reviews are most like information that comes from social sources. It combines the interpretation of this data with an algorithmic function that assigns value to the new information and calculates a new model – a new understanding of what we believe to be true. And it does all this “under the hood” – sitting just below the level of conscious thought.

We’re Becoming Intellectually “Obese”

Humans are defined by scarcity. All our evolutionary adaptations tend to be built to ensure survival in harsh environments. This can sometimes backfire on us in times of abundance.

For example, humans are great at foraging. We have built-in algorithms that tell us which patches are most promising and when we should give up on the patch we’re in and move to another patch.

We’re also good at borrowing strategies that evolution designed for one purpose and applying them for another purpose. This is called exaptation. For example, we’ve exapted our food foraging strategies and applied them to searching for information in an online environment. We use these skills when we look at a website, conduct an online search or scan our email inbox. But as we forage for information – or food – we have to remember, this same strategy assumes scarcity, not abundance.

Take food for example. Nutritionally we have been hardwired by evolution to prefer high fat, high calorie foods. That’s because this wiring took place in an environment of scarcity, where you didn’t know where your next meal was coming from. High fat, high calorie and high salt foods were all “jackpots” if food was scarce. Eating these foods could mean the difference between life and death. So our brains evolved to send us a reward signal when we ate these foods. Subsequently, we naturally started to forage for these things.

This was all good when our home was the African savannah. Not so good when it’s Redondo Beach, there’s a fast food joint on every corner and the local Wal-Mart’s shelves are filled to overflowing with highly processed pre-made meals. We have “refined” food production to continually push our evolutionary buttons, gorging ourselves to the point of obesity. Foraging isn’t a problem here. Limiting ourselves is.

So, evolution has made humans good at foraging when things are scarce, but not so good at filtering in an environment of abundance. I suspect the same thing that happened with food is today happening with information.

Just like we are predisposed to look for food that is high in fats, salt and calories, we are drawn to information that:

  1. Leads to us having sex
  2. Leads to us having more than our neighbors
  3. Leads to us improving our position in the social hierarchy

All those things make sense in an evolutionary environment where there’s not enough to go around. But, in a society of abundance, they can cause big problems.

Just like food, for most of our history information was in short supply. We had to make decisions based on too little information, rather than too much. So most of our cognitive biases were developed to allow us to function in a setting where knowledge was in short supply and decisions had to be made quickly. In such an environment, these heuristic short cuts would usually end up working in our favor, giving us a higher probability of survival.

These evolutionary biases become dangerous as our information environment becomes more abundant. We weren’t built to rationally seek out and judiciously evaluate information. We were built to make decisions based on little or no knowledge. There is an override switch we can use if we wish, but it’s important to know that just like we’re inherently drawn to crappy food, we’re also subconsciously drawn to crappy information.

Whether or not you agree with the mainstream news sources, the fact is that there was a thoughtful editorial process, which was intended to improve the quality of information we were provided. Entire teams of people were employed to spend their days rationally thinking about gathering, presenting and validating the information that would be passed along to the public. In Nobel laureate Daniel Kahneman’s terminology, they were “thinking slow” about it. And because the transactional costs of getting that information to us was so high, there was a relatively strong signal to noise ratio.

That is no longer the case. Transactional costs have dropped to the point that it costs almost nothing to get information to us. This allows information providers to completely bypass any editorial loop and get it in front of us. Foraging for that information is not the problem. Filtering it is. As we forage through potential information “patches” – whether they be on Google, Facebook or Twitter – we tend to “think fast” – clicking on the links that are most tantalizing.

I would have never dreamed that having too much information could be a bad thing. But most of the cautionary columns that I’ve written about in the last few years all seem to have the same root cause – we’re becoming intellectually “obese.” We’ve developed an insatiable appetite for fast, fried, sugar-frosted information.


Searching for Leaders

I was planning on writing a very erudite column on how our consumption of news has drastically changed when I decided to do a research check on Google Trends and found something interesting. It should come as no surprise to learn that Donald Trump is dominating news searches on Google. But what was surprising was that the number one audience with an appetite for “Trumpie Tidbits” is Canadians. That’s right, my fellow countrymen can’t get enough of the guy. We, as a nation, search more for news on Donald Trump than any other place on earth, even the U.S. We out search you Americans on Google by margin of almost 25% (mind you, that margin reverses for web searches for Trump, but we’re still number 2 in the world).


I could offer some psychologically plausible reasons having to do with morbid curiosity, voyeurism, schadenfreude or even the Stockholm Syndrome, but honestly I have no idea why we’re submitting ourselves to this. Maybe it’s giving us something to do during our abnormally long winters and seeing as we’re already miserable as hell, we feel we have nothing to lose?

This is somewhat ironic, given that according to several highly reputable online polls, we have the hottest leader in the world right now – one Monsieur Trudeau. But even as photogenic as Justin is, when it comes to launching a Google search, our vote still goes to Trump. When you compare searches for Trump during his election to searches for Trudeau during his election – in Canada, no less – Trump wins by a margin of 2 to 1.

But it’s not just us. Trump’s domination of the search zeitgeist is historic. Google shows relative volumes – with 100 representing the peak popularity. For Trump, this peak corresponded with his election, in November. A second peak, at 65, came with his inauguration. Never in the entire length of Barack Obama’s presidency did he ever come close to this. The nearest was during his first election in 2008, when he peaked at 55. So, in one category at least, Trump would be accurate in claiming a historic win.

I thought I’d see if this pattern holds up globally. Angela Merkel is barely a blip on Google’s search radar. Worldwide she has never peaked above 1 compared to Trump’s peak score of 100. Perhaps that’s why he refused to shake her hand. Even in Deutschland itself, she peaked at a paltry 17 in the last 5 years against the Trump standard of 100.

Poor Theresa May, the new leader of the United Kingdom, can’t catch a break either. Even on the week she assumed power Donald Trump gained more searches worldwide by a solid 3 to 1 margin.

So let’s put this to the acid test. Trump vs Putin. Worldwide over the past 5 years it was no contest. Trump: 100, Putin: 3 (scored the week of March 2 – 8, 2014, when Putin was making noises about reclaiming Crimea). And yes, even if we restrict the searches to those coming only from Russia, Trump’s best outscored Putin’s best (in June of 2013) by a margin of 2 to 1.

This probably shouldn’t surprise me. According to Google, Donald Trump outscored everyone when it came to searches in 2016. In fact, he came third on Google’s list of most popular searches of any kind, just after Pokémon Go and iPhone 7. The world is locked in a morbid fascination with all that is Trump.

I’d love to wrap up this column with something philosophical and enlightened. It would be good to pass on some tidbit of behavioral wisdom that would put all this search activity into perspective. But that’s not going to happen. All I know is that I’m as guilty as anyone. Since November 8, I search almost daily for ‘Trump” just to see what the last 24 hours hath wrought. I call it my Daily WTF Round Up.

Apparently I’m not alone.

Too Many Fish in the Sea: The Search for Brand Love

I still see – in a number of MediaPost articles and in other places – a lot of talk about “brand-love.” So let’s talk about that.

My grandfather Jack, who farmed on the Canadian Prairies for most of his life, loved John Deere tractors.

And I mean L-O-V-E-D. Deep love. A love that lasted 50 some years and never – not once – did he ever consider a rival for his affection. You could have given him a brand new shiny red Massey Ferguson and it would have sat untouched behind the barn. The man bled green and yellow. He wore a John Deere ball cap everywhere. He had his grime encrusted one for every day wear and a clean one for formal occasions – things like the christening of new grandchildren and 50th wedding anniversaries. He wasn’t buried with one, but if he had his way, he would have been.

My grandpa Jack loved John Deere tractors because he loved one tractor – his tractor. And there was absolutely no logic to this love.

I’ve heard stories of Jack’s rocky road to farm equipment romance. His tractor was a mythically cantankerous beast. It often had to be patiently cajoled into turning over. It was literally held together with twine and bailing wire. At the end of its life, there was little of it that originally issued from the John Deere factory floor in Welland, Ontario. Most of it was vintage Jury-rigged Jack.

But Jack didn’t love this tractor in spite of all that. He loved it because of it. Were there better tractors than the ones John Deere made? Perhaps. Were there better tractors than this particular John Deere? Guaranteed. But that wasn’t the point. Over the years there was a lot of Jack in that tractor. It got to the point where he was the only one who was sufficiently patient to get it to run. But there was also a lot of that tractor in Jack. It made him a more patient man, more resourceful and – much to my grandmother’s never ending frustration – much more stubborn.

This is the stuff that love is made of. The tough stuff. The maddening stuff. The stuff that ain’t so pretty. A lot of times, love happens because you don’t have an alternative. I suspect love – true love – may be inversely correlated to choice. Jack couldn’t afford a new tractor. And by the time he could, he was too deeply in love to consider it.

This may be the dilemma for brands looking for love in today’s world. We may be attracted to a brand, we may even become infatuated with it, but will we fall in true love? What I call “Jack-love?”

Let me lay out some more evidence of this Love/Choice paradox.

If you believe the claims of online dating sites like Match.com and eHarmony, your odds of ending up in a happy relationship have never been better than when you put yourselves in the hands of their matching algorithm. This just makes sense. If you increase the prospects going in the front end and are much smarter about filtering your options, you should come out the winner in the end. But according to an article from the Association for Psychological Science, this claim doesn’t really stand up when subjected to academic rigor. “Regarding matching, no compelling evidence supports matching sites’ claims that mathematical algorithms work— that they foster romantic outcomes that are superior to those fostered by other means of pairing partners.”

A study, by Dr. Aditi Paul, found that couples that meet through online dating sites are less likely to enter marriage than those that meet through offline channels and; if they do wed, are more likely to split up down the road. Another study (D’Angelo and Toma) showed that the greater the number of options at the beginning, the more likely it was that online daters would question and probably reverse their choice.

What dating sites have done have turned looking for love into an exercise in foraging. And the rule of thumb in foraging is: The more we believe there are options that may be better, the less time we will be willing to invest in the current choice. It may seem sacrilegious to apply something so mundane as foraging theory to romance, but the evidence is starting to mount up. And if the search for a soul mate has become an exercise in efficient foraging, it’s not a great leap to conclude that everything else that can be determined by a search and matching algorithm has suffered the same fate. This may not be a bad thing, but I’m placing a fairly large bet that we’re looking at a very different cognitive processing path here. The brain simply wouldn’t use the same mechanisms or strategies to juggle a large number of promising alternatives as it would do fall deeply in love, like Jack and his John Deere (or my grandmother, for that matter).

The point is this. Infatuation happens quickly and can fade just as quickly. Love develops over time and it requires shared experiences. That’s something that’s pretty tough for an algorithm to predict. As the authors of the APS article said, “these sites are in a poor position to know how the two partners will grow and mature over time, what life circumstances they will confront and coping responses they will exhibit in the future, and how the dynamics of their interaction will ultimately promote or undermine romantic attraction and long-term relationship well-being.”

I’ve always felt uncomfortable with the phrase “brand-love” but I think it did provide a convenient and mostly accurate label for some brand relationships. I’m not so sure this is still true today. As I said in a previous column, branding is still aiming to engender love by latching on to our emotions but I suspect they may just be sparking infatuation.

You’ve got a Friend in Me – Our Changing Relationship with A.I.

Since Siri first stepped into our lives in 2011, we’re being introduced to more and more digital assistants. We’ve met Amazon’s Alexa, Microsoft’s Cortana and Google’s Google Now. We know them, but do we love them?

Apparently, it’s important that we bond with said digital assistants and snappy comebacks appear to be the surest path to our hearts. So, if you ask Siri if she has a boyfriend, she might respond with, “Why? So we can get ice cream together, and listen to music, and travel across galaxies, only to have it end in slammed doors, heartbreak and loneliness? Sure, where do I sign up?” It seems to know a smart-assed digital assistant is to love her – but just be prepared for that love to be unrequited.

Not to be outdone, Google is also brushing up on its witty repartee for it’s new Digital Assistant – thanks to some recruits from the Onion and Pixar. A recent Mediapost article said that Google had just assembled a team of writers from those two sources – tapping the Onion for caustic sarcasm and Pixar for a gentler, more human touch.

But can we really be friends with a machine, even if it is funny?

Microsoft thinks so. They’ve unveiled a new chatbot in China called Xiaoice (pronounced Shao-ice). Xiaoice takes on the persona of a 17 year old girl that responds to questions like “How would you like others to comment on you when you die one day?” with the plaintiff “The world would not be much different without me.” Perhaps this isn’t as clever as Siri’s comebacks, but there’s an important difference: Siri’s responses were specifically scripted to respond to anticipated question; while Xiaoice actually talks with you by using true artificial intelligence and linguistic processing.

In a public test on WeChat, Xiaoice received 1.5 million chat group invitations in just 72 hours. As of earlier this year, she had had more than 10 billion conversations. In a blog post, Xiaoice’s “father”, Yongdong Wang, head of the Microsoft Application and Services Group East Asia, said, “Many see Xiaoice as a partner and friend, and are willing to confide in her just as they do with their human friends. Xiaoice is teaching us what makes a relationship feel human, and hinting at a new goal for artificial intelligence: not just analyzing databases and driving cars, but making people happier.”

When we think of digital assistants, we naturally think of the advantages that machines have over humans: unlimited memory, access to the entire web, vastly superior number crunching skills and much faster processing speeds. This has led to “cognitive offloading” – humans transferring certain mental processing tasks to machines. We now trust Google more than our own memory for retrieving information – just as we trust calculators more than our own limited mathematical abilities. But there should be some things that humans are just better at. Being human, for instance. We should be more empathetic – better able to connect with other people. A machine shouldn’t “get us” better than our spouse or best friend.

For now, that’s probably still true. But what if you don’t have a spouse, or even a best friend? Is having a virtual friend better than nothing at all? Recent studies have shown that robotic pets seem to ease loneliness with isolated seniors. More research is needed, but it’s not really surprising to learn that a warm, affectionate robot is better than nothing at all. What was surprising was that in one study, seniors preferred a robotic dog to the real thing.

The question remains, however: Can we truly have a relationship with a machine? Can we feel friendship – or even love – when we know that the machine can’t do the same? This goes beyond the high-tech flirtation of discovering Siri’s or Google’s “easter egg” responses to something more fundamental. It’s touching on what appears to be happening in China, where millions are making a chatbot their personal confident. I suspect there are more than a few lonely Chinese who would consider Xiaoice their best friend.

And – on many levels – that scares the hell out of me.


Why Millennials are so Fascinating

When I was growing up, there was a lot of talk about the Generation Gap. This referred to the ideological gap between my generation – the Baby Boomers, and our parent’s generation – The Silent Generation (1923 – 1944).

But in terms of behavior, there was a significant gap even amongst early Baby Boomers and those that came at the tail end of the boom – like myself. Generations are products of their environment and there was a significant change in our environment in the 20-year run of the Baby Boomers – from 1945 to 1964. During that time, TV came into most of our homes. For the later boomers, like myself, we were raised with TV. And I believe the adoption of that one technology created an unbridgeable ideological gap that is still impacting our society.

The adoption of ubiquitous technologies – like TV and, more recently, connective platforms like mobile phones and the Internet – inevitable trigger massive environmental shifts. This is especially true for generations that grow up with this technology. Our brain goes through two phases where it literally rewires itself to adapt to its environment. One of those phases happens from birth to about 2 to 3 years of age and the other happens during puberty – from 14 to 20 years of age. A generation that goes through both of those phases while exposed to a new technology will inevitably be quite different from the generation that preceded it.

The two phases of our brain’s restructuring – also called neuroplasticity – are quite different in their goals. The first period – right after birth – rewires the brain to adapt to its physical environment. We learn to adapt to external stimuli and to interact with our surroundings. The second phase is perhaps even more influential in terms of who we will eventually be. This is when our brain creates its social connections. It’s also when we set our ideological compasses. Technologies we spend a huge amount of time with will inevitably impact both those processes.

That’s what makes Millennials so fascinating. It’s probably the first generation since my own that bridges that adoption of a massively influential technological change. Most definitions of this generation have it starting in the early 80’s and extend it to 1996 or 97.   This means the early Millennials grew up in an environment that was not all that different than the generation that preceded it. The technologies that were undergoing massive adoption in the early 80’s were VCRs and microwaves – hardly earth shaking in terms of environmental change. But late Millennials, like my daughters, grew up during the rapid adoption of three massively disruptive technologies: mobile phones, computers and the Internet. So we have a completely different environment for which the brain must adapt not only from generation to generation, but within the generation itself. This makes Millennials a very complex generation to pin down.

In terms of trying to understand this, let’s go back to my generation – the Baby Boomers – to see how environment adaptation can alter the face of society. Boomers that grew up in the late 40’s and early 50’s were much different than boomers that grew up just a few years later. Early boomers probably didn’t have a TV. Only the wealthiest families would have been able to afford them. In 1951, only 24% of American homes had a TV. But by 1960, almost 90% of Americans had a TV.

Whether we like to admit it or not, the values of my generation where shaped by TV. But this was not a universal process. The impact of TV was dependent on household income, which would have been correlated with education. So TV impacted the societal elite first and then trickled down. This elite segment would have also been those most likely to attend college. So, in the mid-60’s, you had a segment of a generation who’s values and world view were at least partially shaped by TV – and it’s creation of a “global village” – and who suddenly came together during a time and place (college) when we build the persona foundations we will inhabit for the rest of our lives. You had another segment of a generation that didn’t have this same exposure and who didn’t pursue a post-secondary education. The Vietnam War didn’t create the Counter-Cultural revolution. It just gave it a handy focal point that highlighted the ideological rift not only between two generations but also within the Baby Boomers themselves. At that point in history, part of our society turned right and part turned left.

Is the same thing happening with Millennials now? Certainly the worldview of at least the younger Millennials has been shaped through exposure to connected media. When polled, they inevitably have dramatically different opinions about things like religion, politics, science – well – pretty much everything. But even within the Millennial camp, their views often seem incoherent and confusing. Perhaps another intra-generational divide is forming. The fact is it’s probably too early to tell. These things take time to play out. But if it plays out like it did last time this happened, the impact will still be felt a half century from now.

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.