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

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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.

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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

Multiethnic Group of People Social Networking at Cafe

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

The brain.

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.

Sorry Folks – Blame it on Ed

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Just when you thought it was safe to assume I’d be moving on to another topic, I’m back. Blame it on Ed Papazian, who commented on last week’s column about the Rise of the Audience marketplace. I’ll respond to his comment in multiple parts. First, he said:

“I think it’s fine to speculate on “audience” based advertising, by which you actually mean using digital, not traditional media, as the basis for the advertising of the future.”

All media is going to be digital. Our concept of “traditional” media is well down its death spiral. We’re less then a decade away from all media being delivered through a digital platform that would allow for real time targeting of advertising. True, we have to move beyond the current paradigm of mass distributed, channel restricted advertising we seem stuck in, but the technology is already there. We (by which I mean the ad industry) just have to catch up. Ed continues in this vein:

“However, in a practical sense, not only is this, as yet, merely a dream for TV, radio and print media, but it is also an oversimplification.”

Is it an oversimplification? Let’s remember that more and more of our media consumption is becoming trackable from both ends. We no longer have to track from the point of distribution. Tracking is also possible at the point of consumption. We are living with devices that increasingly have insight into what we’re doing at any moment of the day. It’s just a matter of us giving permission to be served relevant, well targeted ads based on the context of our lives.

But what would entice us to give this permission? Ed goes on to say that…

“Even if a digital advertiser could actually identify every consumer in the U.S. who is interested—or “in the market” for what his ads are trying to sell and also how they are pitching the product/service—and send only these people “audience targeted ads”, many of the ads will still not be of interest…”

Papazian proposed an acid test of sorts (or, more appropriately – an antacid test):

“Why? Because they are for unpleasant or mundane products—toilet bowel cleansers, upset stomach remedies, etc.—-or because the ads are pitching a brand the consumer doesn’t like or has had a bad experience with.”

Okay, let me take up the challenge that Ed has thrown down (or up?). Are ads for stomach remedies always unwanted? Not if I have a history of heartburn, especially when my willpower drops and my diet changes as I’m travelling. Let’s take it one step further. I’ve made a dinner reservation for 7 pm at my favorite Indian food restaurant while I’m in San Francisco. It’s 2 pm. I’ve just polished off a Molinari’s sandwich and I’m heading back to my hotel. As I turn the corner at O’Farrell and Powell, an instant coupon is delivered to my phone with 50% off a new antacid tablet at the Walgreen’s ahead, together with the message: “Prosciutto, pepperoncinis and pakoras in the same day? Look at you go! But just in case…”

The world Ed talks about does have a lot of unwanted advertising. But in the world I’m envisioning, where audiences are precisely targeted, we will hopefully eliminate most of those unwanted ads. Those ads are the by-product of the huge inefficiencies in the current advertising marketplace. And it’s this inefficiency that is rapidly destroying advertising as we know it from both ends. The current market is built on showing largely ineffective ads to mainly disinterested prospects – hoping there is an anomaly in there somewhere – and charging the advertiser to do so. I don’t know about you, but that doesn’t sound like a sustainable plan to me.

When I talk about selecting audiences in a market, it’s this level of specificity that I’m talking about. There is nothing in the above scenario that’s beyond the reach of current Mar-Tech. Perhaps it’s oversimplified. But I did that to make a point. In paid search, we used to have a saying, “buy your best clicks first”. It meant starting with the obviously relevant keywords – the people who were definitely looking for you. The problem was that there just wasn’t enough volume on these “sure-bet” keywords alone. But as digital has matured, the amount of “sure-bet” inventory has increased. We’re still not all the way there – where we can rely on sure-bet inventory alone – but we’re getting closer. The audience marketplace I’m envisioning gets us much of the way there. When technology and data allow us to assemble carefully segmented audiences with a high likelihood of successful engagement on the fly, we eliminate the inefficiencies in the market.

I truly believe that it’s time to discard the jury-rigged, heavily bandaged and limping behemoth that advertising has become and start thinking about this in an entirely new way. Papazian’s last sentence in his comment was…

“You just can’t get around the fact that many ads are going to be unwanted, no matter how they are targeted….”

Do we have to accept that as our future? It’s certainly the present, but I would hate to think we can’t reach any higher. The first step is to stop accepting advertising the way we know it as the status quo. We’ll be unable to imagine tomorrow if we’re still bound by the limitations of today.

 

The Rise of the Audience Marketplace

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Far be it from me to let a theme go before it has been thoroughly beaten to the ground. This column has hosted a lot of speculation on the future of advertising and media buying and today, I’ll continue in that theme.

First, let’s return to a column I wrote almost a month ago about the future of advertising. This was a spin-off on a column penned by Gary Milner – The End of Advertising as We Know It. In it, Gary made a prediction: “I see the rise of a global media hub, like a stock exchange, which will become responsible for transacting all digital programmatic buys.”

Gary talked about the possible reversal of fragmentation of markets by channel and geographic area due to the potential centralization of digital media purchasing. But I see it a little differently than Gary. I don’t see the creation of a media hub – or, at least – that wouldn’t be the end goal. Media would simply be the means to the end. I do see the creation of an audience market based on available data. Actually, even an audience would only be the means to an end. Ultimately, we’re buying one thing – attention. Then it’s our job to create engagement.

The Advertising Research Foundation has been struggling with measuring engagement for a long time now. But it’s because they were trying to measure engagement on a channel-by-channel basis and that’s just not how the world works anymore. Take search, for example. Search is highly effective at advertising, but it’s not engaging. It’s a connecting medium. It enables engagement, but it doesn’t deliver it.

We talk multi-channel a lot, but we talk about it like the holy grail. The grail in this cause is an audience that is likely to give us their attention and once they do that – is likely to become engaged with our message. The multi-channel path to this audience is really inconsequential. We only talk about multi-channel now because we’re stopping short of the real goal, connecting with that audience. What advertising needs to do is give us accurate indicators of those two likelihoods: how likely are they to give us their attention and what is their potential proclivity towards our offer. The future of advertising is in assembling audiences – no matter what the channel – that are at a point where they are interested in the message we have to deliver.

This is where the digitization of media becomes interesting. It’s not because it’s aggregating into a single potential buying point – it’s because it’s allowing us to parallel a single prospect along a path of persuasion, getting important feedback data along the way. In this definition, audience isn’t a static snapshot in time. It becomes an evolving, iterative entity. We have always looked at advertising on an exposure-by-exposure basis. But if we start thinking about persuading an audience that paradigm needs to be shifted. We have to think about having the right conversation, regardless of the channel that happens to be in use at the time.

Our concept of media happens to carry a lot of baggage. In our minds, media is inextricably linked to channel. So when we think media, we are really thinking channels. And, if we believe Marshall McLuhan, the medium dictates the message. But while media has undergone intense fragmentation they’ve also become much more measurable and – thereby – more accountable. We know more than ever about who lies on the other side of a digital medium thanks to an ever increasing amount of shared data. That data is what will drive the advertising marketplace of the future. It’s not about media – it’s about audience.

In the market I envision, you would specify your audience requirements. The criteria used would not be so much our typical segmentations – demography or geography for example. These have always just been proxies for what we really care about; their beliefs about our product and predicted buying behaviors. I believe that thanks to ever increasing amounts of data we’re going to make great strides in understanding the psychology of consumerism. These  will be foundational in the audience marketplace of the future. Predictive marketing will become more and more accurate and allow for increasingly precise targeting on a number of behavioral criteria.

Individual channels will become as irrelevant as the manufacturer that supplies the shock absorbers and tie rods in your new BMW. They will simply be grist for the mill in the audience marketplace. Mar-tech and ever smarter algorithms will do the channel selection and media buying in the background. All you’ll care about is the audience you’re targeting, the recommended creative (again, based on the mar-tech running in the background) and the resulting behaviors. Once your audience has been targeted and engaged, the predicted path of persuasion is continually updated and new channels are engaged as required. You won’t care what channels they are – you’ll simply monitor the progression of persuasion.

 

Ex Machina’s Script for Our Future

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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.