What Price Privacy?

As promised, I’m picking up the thread from last week’s column on why we seem okay with trading privacy for convenience. The simple – and most plausible – answer is that we’re really not being given a choice.

As Mediapost Senior Editor Joe Mandese pointed out in an very on-point comment, what is being creating is an transactional marketplace where offers of value are exchanged for information.:

“Like any marketplace, you have to have your information represented in it to participate. If you’re not “listed” you cannot receive bids (offers of value) based on who you are.”

Amazon is perhaps the most relevant example of this. Take Alexa and Amazon Web Services (AWS). Alexa promises to “make your life easier and more fun.” But this comes at a price. Because Alexa is voice activated, it’s always listening. That means that privacy of anything we say in our homes has been ceded to Amazon through their terms of service. The same is true for Google Assist and Apple Siri.

But Amazon is pushing the privacy envelope even further as they test their new in-home delivery service – Amazon Key. In exchange for the convenience of having your parcels delivered inside your home when you’re away, you literally give Amazon the keys to your home. Your front door will have a smart door lock that can be opened via the remote servers of AWS. Opt in to this and suddenly you’ve given Amazon the right to not only listen to everything you say in your home but also to enter your home whenever they wish.

How do you feel about that?

This becomes the key question. How do we feel about the convenience/privacy exchange. But it turns out that our response depends in large part on how that question is framed. In a study conducted in 2015 by the Annenberg School for Communications at the University of Pennsylvania, researchers gathered responses from participants probing their sensitivity around the trading of privacy for convenience. Here is a sampling of the results:

  • 55% of respondents disagreed with the statement: “It’s OK if a store where I shop uses information it has about me to create a picture of me that improves the services they provide for me.”
  • 71% disagreed with: “It’s fair for an online or physical store to monitor what I’m doing online when I’m there, in exchange for letting me use the store’s wireless internet, or Wi-Fi, without charge.
  • 91% disagreed that: “If companies give me a discount, it is a fair exchange for them to collect information about me without my knowing”

Here, along the spectrum of privacy pushback, we start to see what the real problem is. We’re willing to exchange private information, as long as we’re aware of all that is happening and feel in control of it. But that, of course, is unrealistic. We can’t control it. And even if we could, we’d soon learn that the overhead required to do so is unmanageable. It’s why Vint Cerf said we’re going to have to learn to live with transparency.

Again, as Mr. Mandese points out, we’re really not being given a choice. Participating in the modern economy required us anteing up personal information. If we choose to remain totally private, we cut ourselves off from a huge portion of what’s available. And we are already at the point where the vast majority of us really can’t opt out. We all get pissed off when we hear of a security breach a la the recent Equifax debacle. Our privacy sensitivities are heightened for a day or two and we give lip service to outrage. But unless we go full out Old Order Amish, what are our choices?

We may rationalize the trade off by saying the private information we’re exchanging for services is not really that sensitive. But that’s where the potential threat of Big Data comes in. Gather enough seemingly innocent data and soon you can start predicting with startling accuracy the aspects of our lives that we are sensitive about. We run headlong into the Target Pregnant Teen dilemma. And that particular dilemma becomes thornier as the walls break down between data siloes and your personal information becomes a commodity on an open market.

The potential risk of trading away our privacy becomes an escalating aspect here – it’s the frog in boiling water syndrome. It starts innocently but can soon develop into a scenario that will keep most anyone up at night with the paranoiac cold sweats. Let’s say the data is used for targeting – singling us out of the crowd for the purpose of selling stuff to us. Or – in the case of governments – seeing if we have a proclivity for terrorism. Perhaps that isn’t so scary if Big Brother is benevolent and looking out for our best interests. But what if Big Brother becomes a bully?

There is another important aspect to consider here, and one that may have dire unintended consequences. When our personal data is used to make our world more convenient for us, that requires a “filtering” of that world by some type of algorithm to remove anything that algo determines to be irrelevant or uninteresting to us. Essentially, the entire physical world is “targeted” to us. And this can go horribly wrong, as we saw in the last presidential election. Increasingly we live in a filtered “bubble” determined by things beyond our control. Our views get trapped in an echo chamber and our perspective narrows.

But perhaps the biggest red flag is the fact that in signing away our privacy by clicking accept, we often also sign away any potential protection when things do go wrong. In another study called “The Biggest Lie on the Internet,” researchers found that when students were presented with a fictitious terms of service and privacy policy, 74% skipped reading it. And those that took the time to read didn’t take very much time – just 73 seconds on average. What almost no one caught were “gotcha clauses” about data sharing with the NSA and giving up your first-born child. While these were fictitious, real terms of service and privacy notifications often include clauses that include total control over the information gathered about you and giving up your right to sue if anything went bad. Even if you could sue, there might not be anyone left to sue. One analyst calculated that even if all the people who had their financial information stolen from Equifax won a settlement, it would actually amount to about $81 dollars.

 

Why We’re Trading Privacy for Convenience

In today’s world, increasingly quantified and tracked by the Internet of Things, we are talking a lot about privacy. When we stop to think about it, we are vociferously for privacy. But then we immediately turn around and click another “accept” box on a terms and conditions form that barters our personal privacy away, in increasingly large chunks. What we say and what we do are two very different things.

What is the deal with humans and privacy anyway? Why do we say is it important to us and why do we keep giving it away? Are we looking at the inevitable death of our concept of privacy?

Are We Hardwired for Privacy?

It does seem that – all things being equal – we favor privacy. But why?

There is an evolutionary argument for having some “me-time”. Privacy has an evolutionary advantage both when you’re most vulnerable to physical danger (on the toilet) or mating rivalry (having sex). If you can keep these things private, you’ll both live longer and have more offspring. So it’s not unusual for humans to be hardwired to desire a certain amount of privacy.

But our modern understanding of privacy actually conflates a number of concepts. There is protective privacy, the need for solitude and finally there’s our moral and ethical privacy. Each of these has different behavioral origins, but when we talk about our “right to privacy” we don’t distinguish between them. This can muddy the waters when we dig deep into our relationship with our privacy.

Blame England…

Let’s start with the last of these – our moral privacy. This is actually a pretty modern concept. Until 150 years ago, we as a species did pretty much everything communally. Our modern concept of privacy had its roots in the Industrial Revolution and Victorian England. There, the widespread availability of the patent lock and the introduction of the “private” room quickly led to a class-stratified quest for privacy. This was coupled with the moral rectitude of the time. Kate Kershner from howstuffworks.com explains:

“In the Victorian era, the “personal” became taboo; the gilded presentation of yourself and family was critical to social standing. Women were responsible for outward piety and purity, men had to exert control over inner desires and urges, and everyone was responsible for keeping up appearances.”

In Victorian England, privacy became a proxy for social status. Only the highest levels of the social elite could afford privacy. True, there was some degree of personal protection here that probably had evolutionary behavioral underpinnings, but it was all tied up in the broader evolutionary concept of social status. The higher your class, the more you could hide away the all-too-human aspects of your private life and thoughts. In this sense, privacy was not a right, but a status token that may be traded off for another token of equal or higher value. I suspect this is why we may say one thing but do another when it comes to our own privacy. There are other ways we determine status now.

Privacy vs Convenience

In a previous column, I wrote about how being busy is the new status symbol. We are defining social status differently and I think how we view privacy might be caught between how we used to recognize status and how we do it today. In 2013, Google’s Vint Cerf said that privacy may be a historical anomaly. Social libertarians and legislators were quick to condemn Cerf’s comment, but it’s hard to argue his logic. In Cerf’s words, transparency “is something we’re gonna have to live through.”

Privacy might still be a hot button topic for legislators but it’s probably dying not because of some nefarious plot against us but rather because we’re quickly trading it away. Busy is the new rich and convenience (or our illusion of convenience) allows us to do more things. Privacy may just be a tally token in our quest for social status and increasingly, we may be willing to trade it for more relevant tokens.  As Greg Ferenstein, author of the Ferenstein Wire, said in an exhaustive (and visually bountiful) post on the birth and death of privacy,

“Humans invariably choose money, prestige or convenience when it has conflicted with a desire for solitude.”

If we take this view, then it’s not so much how we lose our privacy that becomes important but who we’re losing it to. We seem all too willing to give up our personal data as long as two prerequisites are met: 1) We get something in return; and, 2) We have a little bit of trust in the holder of our data that they won’t use it for evil purposes.

I know those two points raise the hackles of many amongst you, but that’s where I’ll have to leave it for now. I welcome you to have the next-to-last word (because I’ll definitely be revisiting this topic). Is privacy going off the rails and, if so, why?

Why I Go to a Store

I hate shopping. Let me clarify. I hate the physical experience of shopping. I find no joy in a mall. I avoid department stores like the plague. If I can buy it online, I will.

Except..I don’t, always.

Why is that? I should be the gold standard of e-commerce targets. And most of the time, I am. Except when I’m not. Take home improvement stuff, for instance. I still drive down to my local Home Depot, even though I can order online.

As prognosticators of the online space, we’ve been busy hammering the nails in the coffin of bricks and mortar retail for a while. In a recent story in the Atlantic, E-tail was called the perfect match for the emerging sloth of the first world consumer: “E-commerce is soaring and food-delivery businesses are taking off because human beings are fundamentally lazy and they don’t want to leave the couch to buy stuff.”

That makes sense. But while the smart bets seem to be placed on a consumer stampede heading towards e-tail, Amazon just invested 13.7 billion in buying Whole Foods Market. So if bricks and mortar retail is dead, why the hell did Amazon buy almost 500 more physical stores? That same Atlantic article does a pretty thorough job of answering this question, offering three compelling reasons:

  • To dominate the food delivery market
  • To create an instant fulfillment network
  • To broaden Amazon’s footprint within the consumption habits of affluent Americans

I can buy that. The second point in particular seems to make eminent sense. If I know something is in stock at my local store and I need it right now, I’ll make the trip. And Amazon is currently struggling to deliver the last mile of fulfillment. But I keep going back to my original question: why do I – a man who detests the physical act of shopping – still decide to go to a store more often than I probably want to?

There has been various strategies put forward for the salvation. In a recent post on Mediapost, Mahesh Krishna said Personalization was the answer – use data to tailor an in-store experience. I myself wrote something similar in a previous post about Amazon testing the waters of a bricks and mortar retail environment. But there’s nothing personalized about Home Depot. I’m anonymous til I get to the till. So for me, anyway, that doesn’t seem to explain why.

Experiential shopping is another proffered recipe for the salvation of retail. A recent article from Wharton cited an Italian culinary themed retail success story: “Another experiential success… is Eataly, a chain of Italian marketplaces that combines restaurants, grocery stores and cooking schools. It capitalizes on the appeal of Italian culture and sophistication. ‘It all works together like a little universe,’ she says. ‘There’s a nice synergy there; you can taste the foods in the restaurant … you might then go to the grocery store to buy it so you can make it at home.’

But how much “experience” do I really need in my shopping? The answer is not a lot. As undeniably fantastico as Eataly is, for me it would be a 3 to 4 times a year visit. And let’s face it – the retail niches that suit this over-the-top experiential approach are limited. No, there needs to be a more pragmatic reason why I’ll actually drag my butt away from a screen and down to the local mercantile.

I realized, when I really examined the reasons why I usually go to the store, they all had to do with risk. I go to the store when I’m afraid that stuff could go wrong:

  1. When I’m unsure what I need
  2. When I’m afraid I may have to return what I bought
  3. When I have to ask a question about use of something I want to buy

For me, bricks and mortar shopping is usually nothing more than a risk-mitigation strategy, pure and simple. And I suspect I’m not alone. Apple Stores are often cited as an example of experiential shopping, but I believe the real genius of this retail success story is the Genius Bar. The jigsaw puzzle integration of the All Things Apple universe can be a daunting prospect. Having an actual human to guide you through the process is reassuring, and reassurance is most effective when it’s face-to-face. That’s why I go to a store.

 

Attention: Divided

I’d like you to give me your undivided attention. I’d like you to – but you can’t. First, I’m probably not interesting enough. Secondly, you no longer live in a world where that’s possible. And third, even if you could, I’m not sure I could handle it. I’m out of practice.

The fact is, our attention is almost never undivided anymore. Let’s take talking for example. You know; old-fashioned, face-to-face, sharing the same physical space communication. It’s the one channel that most demands undivided attention. But when is the last time you had a conversation where you were giving it 100 percent of your attention? I actually had one this past week, and I have to tell you, it unnerved me. I was meeting with a museum curator and she immediately locked eyes on me and gave me the full breadth of her attention span. I faltered. I couldn’t hold her gaze. As I talked I scanned the room we were in. It’s probably been years since someone did that to me. And nary a smart phone was in sight.

If this is true when we’re physically present, imagine the challenge in other channels. Take television, for instance. We don’t watch TV like we used to. When I was growing up, I would be verging on catatonia as I watched the sparks fly between Batman and Catwoman (the Julie Newmar version – with all due respect to Eartha Kitt and Lee Meriwether.) My dad used to call it the “idiot box.” At the time, I thought it was a comment on the quality of programming, but I now know realize he was referring to my mental state. You could have dropped a live badger in my lap and not an eye would have been batted.

But that’s definitely not how we watch TV now. A recent study indicates that 177 million Americans have at least one other screen going – usually a smartphone – while they watch TV. According to Nielsen, there are only 120 million TV households. That means that 1.48 adults per household are definitely dividing their attention amongst at least two devices while watching Game of Thrones. My daughters and wife are squarely in that camp. Ironically, I now get frustrated because they don’t watch TV the same way I do – catatonically.

Now, I’m sure watching TV does not represent the pinnacle of focused mindfulness. But this could be a canary in a coalmine. We simply don’t allocate undivided attention to anything anymore. We think we’re multi-tasking, but that’s a myth. We don’t multi-task – we mentally fidget. We have the average attention span of a gnat.

So, what is the price we’re paying for living in this attention deficit world? Well, first, there’s a price to be paid when we do decided to communicate. I’ve already stated how unnerving it was for me when I did have someone’s laser focused attention. But the opposite is also true. It’s tough to communicate with someone who is obviously paying little attention to you. Try presenting to a group that is more interested in chatting to each other. Research studies show that our ability to communicate effectively erodes quickly when we’re not getting feedback that the person or people we’re talking to are actually paying attention to us. Effective communication required an adequate allocation of attention on both ends; otherwise it spins into a downward spiral.

But it’s not just communication that suffers. It’s our ability to focus on anything. It’s just too damned tempting to pick up our smartphone and check it. We’re paying a price for our mythical multitasking – Boise State professor Nancy Napier suggests a simple test to prove this. Draw two lines on a piece of paper. While having someone time you, write “I am a great multi-tasker” on one, then write down the numbers from 1 to 20 on the other. Next, repeat this same exercise, but this time, alternate between the two: write “I” on the first line, then “1” on the second, then go back and write “a” on the first, “2” on the second and so on. What’s your time? It will probably be double what it was the first time.

Every time we try to mentally juggle, we’re more likely to drop a ball. Attention is important. But we keep allocating thinner and thinner slices of it. And a big part of the reason is the smart phone that is probably within arm’s reach of you right now. Why? Because of something called intermittent variable rewards. Slot machines use it. And that’s probably why slot machines make more money in the US than baseball, moves and theme parks combined. Tristan Harris, who is taking technology to task for hijacking our brains, explains the concept: “If you want to maximize addictiveness, all tech designers need to do is link a user’s action (like pulling a lever) with a variable reward. You pull a lever and immediately receive either an enticing reward (a match, a prize!) or nothing. Addictiveness is maximized when the rate of reward is most variable.”

Your smartphone is no different. In this case, the reward is a new email, Facebook post, Instagram photo or Tinder match. Intermittent variable rewards – together with the fear of missing out – makes your smartphone as addictive as a slot machine.

I’m sorry, but I’m no match for all of that.

Will We Ever Let Robots Shop for Us?

Several years ago, my family and I visited Astoria, Oregon. You’ll find it at the mouth of the Columbia River, where it empties into the Pacific. We happened to take a tour of Astoria and our guide pointed out a warehouse. He told us it was filled with canned salmon, waiting to be labeled and shipped. I asked what brand they were. His answer was “All of them. They all come from the same warehouse. The only thing different is the label.”

Ahh… the power of branding…

Labels can make a huge difference. If you need proof, look no further than the experimental introduction of generic brands in grocery stores. Well, they were generic to begin with, anyway. But over time, the generic “yellow label” was replaced with a plethora of store brands. The quality of what’s inside the box hasn’t changed much, but the packaging has. We do love our brands.

But there’s often no rational reason to do so. Take the aforementioned canned salmon for example. Same fish, no matter what label you may stick on it. Brands are a trick our brain plays on us. We may swear our favorite brand tastes better than it’s competitors, but it’s usually just our brain short circuiting our senses and our sensibility. Neuroscientist Read Montague found this out when he redid the classic Pepsi taste test using a fMRI scanner. The result? When Coke drinkers didn’t know what they were drinking, the majority preferred Pepsi. But the minute the brand was revealed, they again sweared allegiance to Coke. The taste hadn’t changed, but their brains had. As soon as the brain was aware of the brand, some parts of it suddenly started lighting up like a pinball machine.

In previous research we did, we found that the brain instantly responded to favored brains the same way it did to a picture of a friend or a smiling face. Our brains have an instantaneous and subconscious response to brands. And because of that, our brains shouldn’t be trusted with buying decisions. We’d be better off letting a robot do it for us.

And I’m not saying that facetiously.

A recent post on Bloomberg.com looked forward 20 years and predicted how automation would gradually take over ever step of the consumer product supply chain, from manufacturing to shipping to delivery to our door. The post predicts that the factory floor, the warehouse, ocean liners, trucks and delivery drones will all be powered by Artificial intelligence and robotic labor. The first set of human hands that might touch a product would be those of the buyer. But maybe we’re automating the wrong side of the consumer transaction. The thing human hands shouldn’t be touching is the buy button. We suck at it.

We have taken some steps in the right direction. Itamar Simonson and Emanuel Rosen predicted a death of branding in their book Absolute Value:

“In the past the marketing function “protected” the organization in some cases. When things like positioning, branding, or persuasion worked effectively, a mediocre company with a good marketing arm (and deep pockets for advertising) could get by. Now, as consumers are becoming less influenced by quality proxies, and as more consumers base their decisions on their likely experience with a product, this is changing.”

But our brand love dies hard. If our brain can literally rewire the evidence from our own senses – how can we possibly make rational buying decisions? True, as Simonson and Rosen point out, we do tend to favor objective information when it’s available, but at the end of the day, our buying decisions still rely on an instrument that has proven itself unreliable in making optimal decisions under the influence of brand messaging.

If we’re prepared to let robots steer ships, drive trucks and run factories, why won’t we let them shop for us? Existing shopping bots stop well short of actually making the purchase. We’ll put our lives in the hands of A.I. in a myriad of ways, but we won’t hand our credit card over. Why is that?

It seems ironic to me. If there were any area where machines can beat humans, it would be in making purchases. They’re much better at filtering based on objective criteria, they can stay on top of all prices everywhere and they can instantly aggregate data from all similar types of purchases. Most importantly, machines can’t be tricked by branding or marketing. They can complete the Absolute Value loop Simonson and Rosen talk about in their book.

Of course, there’s just one little problem with all that. It essentially ends the entire marketing and advertising industry.

Ooops.

Bias, Bug or Feature?

When we talk about artificial intelligence, I think of a real time Venn diagram in motion. One side is the sphere of all human activity. This circle is huge. The other side is the sphere of artificial intelligent activity. It’s growing exponentially. And the overlap area between the two is also expanding at the same rate. It’s this intersection between the two spheres that fascinates me. What are the rules that govern interplay between humans and machines?

Those rules necessarily depend on what the nature of the interplay is. For the sake of this column, let’s focus on those researchers and developers that are trying to make machines act more like humans. Take Jibo, for example. Jibo is “the first social robot for the home.” Jibo tells jokes, answers questions, understands nuanced language and recognizes your face. It’s just one more example of artificial intelligence that’s intended to be a human companion. And as we’re building machines that are more human, we’re finding is that many of the things we thought were human foibles are actually features that have developed for reasons that were at one time perfectly valid.

Trevor Paglin is a winner of the MacArthur Genius Grant. His latest project is to see what AI sees when it’s looking at us: “What are artificial intelligence systems actually seeing when they see the world?” What is interesting about this is that when machines see the world, they use machine-like reasoning to make sense of it. For example, Paglin fed hundreds of images of fellow artist Hito Steyerl into a face-analyzing algorithm. In one instance, she was evaluated as “74% female”.

This highlights a fundamental difference in how machines and humans see the world. Machines calculate probabilities. So do we, but that happens behind the scenes and it’s only part of how we understand the world. Operating a level higher than that we use meta-signatures; categorization for example – to quickly compartmentalize and understand the world. We would know immediately that Hito was a woman. We wouldn’t have to crunch the probabilities. By the way, we do the same thing with race.

But is this a feature or a bug? Paglin has his opinion, “I would argue that racism, for example, is a feature of machine learning—it’s not a bug,” he says. “That’s what you’re trying to do: you’re trying to differentiate between people based on metadata signatures and race is like the biggest metadata signature around. You’re not going to get that out of the system.”

Whether we like it or not, our inherent racism was a useful feature many thousands of years ago. It made us naturally wary of other tribes competing for the same natural resources. As much as it’s abhorrent to most of us now, it’s still a feature that we can’t “get out of the system.”

This highlights a danger in this overlap area between humans and machines. If we want machines to think as we do, we’re going to have to equip them with some of our biases. As I’ve mentioned before, there are some things that humans do well, or, at least; that we do better than machines. And there are things machines do infinitely better than we. Perhaps we shouldn’t to try to merge these two. If we’re trying to get machines to do what humans do, are we prepared to program racism, misogyny, intolerance, bias and greed into the operating system? All these things are part of being human, whether we like to admit it or not.

But there are other areas that are rapidly falling into the overlap zone of my imaginary Venn diagram. Take business strategy, for example. A recent study from CapGemini showed that 79% of organizations implementing AI feel it’s bringing new insights and better data analysis, 74% that it makes their organizations more creative and 71% feel it’s helping make better management decisions. A friend of mine recently brought this to my attention along with what was for him an uncharacteristic rant: “I really would’ve hoped senior executives might’ve thought creativity and better management decisions were THEIR GODDAMN JOB and not be so excited about being able to offload those dreary functions to AI’s which are guaranteed to be imbued with the biases of their creators or, even worse, unintended biases resulting from bad data or any of the untold messy parts of life that can’t be cleanly digitized.”

My friend hit the proverbial nail on the proverbial head – those “untold messy parts of life” are the things we have evolved to deal with, and the way we deal with them are not always admirable. But in the adaptive landscape we all came from, they were proven to work. We still carry that baggage with us. But is it right to transfer that baggage to algorithms in order to make them more human? Or should we be aiming for a blank slate?

When Technology Makes Us Better…

I’m always quick to point out the darker sides of technology. So, to be fair, I should also give credit where credit is due. That’s what today’s column is about. Technology, we collectively owe you one. Why? Because without you, we wouldn’t be slowly chipping away at the massive issue of sexual predation. #Metoo couldn’t have happened without you.

I’ve talked before of Mark Granovetter’s threshold model of crowd behavior. In the past, I’ve used it to explain how it can tip collective behavior towards the negative; turning crowds into mobs. But it can also work the other way; turning crowds into movements. Either way, the threshold model depends on connection and technology makes that connecting possible. What’s more, it makes it possible in a very specific way that is important to understand.

Technological connection is often ideological connection. We connect in ad hoc social networks that center around an idea. We find common ground that is not physical but conceptual. In the process, we forge new social connections that are freed from the typical constraints that introduce friction in the growth of social networks. We create links that are unrestricted by how people look, where they live, how much they earn or what church they worship at. All we need is to find resonance within ideas and we can quickly create a viral wave. The cost of connection is reduced.

This is no way diminishes the courage required to post the #metoo hashtag. I have been in the digital world for almost three decades now and in that time I have met many, many remarkable women. I hope I have judged them as fellow human beings and have treated them as equals. It has profoundly saddened me to see most of them join the #metoo movement in the past few weeks. It has been painful to learn just how pervasive the problem is and to see this light creep into a behavioral basement of which we are becoming more aware. But it is oh-so-necessary. And I must believe that technology and the comfort it affords by letting you know you’re not alone has made it just a little bit easier to type those six characters.

As I have always said – technology erases friction. It breaks down those sticking points that used to allow powerful individuals to exert control. Control is needed to maintain those circles of complicity that allows the Harvey Weinsteins of the world to prey on others. But with technology, all we need is one little crack in that circle to set in motion a chain reaction that blasts it apart.

I believe that the Weinstein example will represent a sea-change moment in how our society views sexual predation. These behaviors are always part of a power game. For it to continue to exist, the perpetrator must believe in their own power and their ability to maintain it. Once the power goes, so does the predation. #Metoo has shown that your power can disappear immediately and permanently if you get publically tagged. “If it happened to Harvey, it could happen to me” may become the new cautionary tale.

But I hope it’s not just the fear of being caught that pushes us to be better. I also hope that we have learned that it’s not okay to tolerate this. In the incredibly raw and honest post of screenwriter Scott Rosenberg, we had our worst fears confirmed: “Everybody f—ing knew!” And everybody who knew is being sucked into the whirlpool of Harvey’s quickly sinking bulk. I have to believe this is tipping the balance in the right direction. We good men (and women) might be less likely to do nothing next time.

Finally, technology has made us better, whether we believe it or not. In 1961, when I was born, Weinstein’s behavior would have been accepted as normal. It would have even been considered laudable in some circles (predominately male circles – granted). As a father of two daughters, I am grateful that that’s not the world we live in today. The locker room mentality that allows the Harvey Weinsteins, Robert Scobles, and Donald Trumps of the world to flourish is being chipped away – #metoo post by #metoo post.

And we have technology to thank for that.

157 Shades of Grey…

Design is important. Thinking through how people will respond to the aesthetics of your product is an admirable thing. I remember once having the pleasure of sharing a stage with JetBlue’s VP of Marketing – Amy Curtis-McIntyre. She was explaining how important good design was to the airline’s overall marketing strategy. A tremendous amount of thought went into the aesthetics of all their printed materials – even those cards explaining the safety features of the airplane that none of us ever read. But on JetBlue, not only did passengers read them – they stole them because they were so cleverly designed. Was this a problem for management? Not according to Amy:

“You know you’re doing something right when people steal your marketing shit”

So, I’m a fan of good design. But according to a recent story on Fastcodesign.com, Google is going at least 156 shades too far. They seem obsessed with color – or – at least, testing for colors. The design team for Google’s new home assistant – the Mini – had to pick three different colors for the home appliance. They wanted one to make a personal statement and apparently that statement is best made by the color “Coral.” Then they needed a color that would sit unobtrusively next to your TV set and that turned out to be “Charcoal.” Finally, they needed a “floater” color that could go anywhere in the house, including the kitchen. And that’s when the design team at Google may have gone off the tracks. They tested 157 shades of grey – yes – 157 – before they settled on “Chalk,” which is said to be the most inoffensive shade imaginable. They even worked with a textile firm to create their own custom cloth for the grill on top.

That beats Google’s previous obsessive-compulsive testing disorder record, set by then VP of Search Marissa Mayer when she ordered the design team to test 42 different shades of blue for search links to see which got the most clicks. At Google, good design seems to equal endless testing. But is there anything wrong with that?

Well, for one thing, you can test yourself into a rabbit hole, running endless tests and drowning in reams of data looking for the optimal solution – completely missing global maxima while myopically focused on the local. Google tests everything – and I mean everything – truly, madly and deeply. Even Google insiders admit this penchant for testing often gets them focused on the trees rather than the forest. This is particularly true for design. Google has a long history of obsessively turning out ho-hum designs.

Personally, when it comes to pure design magic, I much prefer the Apple approach. Led by Steve Job and Jon Ive’s unerring sense for the aesthetic – it’s hard to think of a longer run of spectacular product designs. Yes, they too sweated the small stuff. But those details were always in service of a higher vision – an empathetic, elegantly simple, friendly approach to product design that somehow magically connected with the user, leaving that user somewhat awed and consistently impressed. One might quibble with the technology that lies inside the package, but no one has put together a more beautiful package that the Apple design team at the height of their powers.

When you look at a Google product, you have the result of endless testing and data crunching. When you look at a classic Apple design, you sense that this came from more than simple testing. This came from intuition and creativity.

 

Together We Lie

Humans are social animals. We’ve become this way because – evolutionarily speaking – we do better as a group than individually. But there’s a caveat here. If you get a group of usually honest people together, they’re more likely to lie. Why is this?

Martin Kocher and his colleagues from LMU in Munich set up a study where participants had to watch a video of a single roll of a die and then report on the number that came up. Depending on what they reported, there was a payoff. Researchers asked both individuals and small groups who had the opportunity to chat anonymously with each other before reporting. The result,

“Our findings are unequivocal: People are less likely to lie if they decide on their own.”

Even individuals who answered honestly independently started lying when they got in a group.

The researchers called this a “dishonesty shift.” They blame it on a shifting weight placed on the norm of honesty. Norms are those patterns we have that guide us in our behaviors and beliefs. But those norms may be different individually than they are when we’re part of a group.

“Feedback is the decisive factor. Group-based decision-making involves an exchange of views that may alter the relative weight assigned to the relevant norm.”

Let’s look at how this may play out. Individually, we may default to honesty. We do so because we’re unsure of the consequences of not being honest. But when we get in a group, we start talking to others and it’s easier to rationalize not being honest – “Well, if everyone’s going to lie, I might as well too.”

Why is this important? Because marketing is done in groups, by groups, to groups. The dynamics of group-based ethics are important for us to understand. It could help to explain the most egregious breaches of ethics we see becoming more and more commonplace, either in corporations or in governments.

Four of the seminal studies in psychology and sociology shed further light on why groups tend to shift towards dishonesty. Let’s look at them individually.

In 1955, Solomon Asch showed that even if individually we believe something to be incorrect, if enough people around us have a different option, we’ll go with the group consensus rather than risk being the odd person out. In his famous study, he would surround a subject with “plants” who, when shown cards with three black lines of obviously differing lengths on it, would insist that three lines were equal. The subjects were then asked their opinion. In 75% of the cases, they’d go with the group rather than risk disagreement. As Asch said in his paper – quoting sociologist Gabriel Tarde – “Social man in a somnambulist.” We have about as much independent will as your average sleepwalker.

Now, let’s continue with Stanley Milgram’s Obedience to Authority study, perhaps the most controversial and frightening of the group. When confronted with an authoritative demeanor, a white coat and a clipboard, 63% of the subjects meekly followed directions and delivered what were supposed to be lethal levels of electrical shock to a hapless individual. The results were so disheartening that we’ve been trying to debunk them ever since. But a follow up study by Stanford psychology professor Philip Zimbardo – where subjects were arbitrarily assigned roles as guards and inmates in a mock prison scenario – was even more shocking. We’re more likely to become monsters and abandon our personal ethics when we’re in a group than when we act alone. Whether it’s obedience to authority – as Milgram was trying to prove – or whether it’s social conformity taken to the extreme, we tend to do very bad things when we’re in bad company.

But how do we slip so far so quickly from our own personal ethical baseline? Here’s where the last study I’ll cite can shed a little light. Sociologist Mark Granovetter – famous for his Strength of Weak Ties study – also looked at the viral spreading of behaviors in groups. I’ve talked about this in a previous column, but here’s the short version: If we have the choice between two options, with accompanying social consequences, which option we choose may be driven by social conformity. If we see enough other people around us picking the more disruptive option (i.e. starting a riot) we may follow suit. Even if we all have different thresholds – which we do – the nature of a crowd is such that those with the lowest threshold will pick the disruption option, setting into effect a bandwagon effect that eventually tips the entire group over the threshold.

These were all studied in isolation, because that’s how science works. We study variables in isolation. But it’s when factors combine that we get the complexity that typifies the real world – and the real marketplace. And there’s where predictability goes out the window. The group dynamics in play can create behavioral patterns that make no sense to the average person with the average degree of morality. But it’s happened before, it’s happening now, and it’s sure to happen again.

 

 

To Buy or Not to Buy: The Touchy Subject of Mobile ECommerce

A recent report from Akamai indicates that users have little patience when it comes to making purchases on a mobile device. Here are just a few of the stats:

  • While almost half of all consumers browse via their phones, only 1 in 5 complete transactions on mobile
  • Optimal load times for peak conversions ranged from 1.8 to 2.7 seconds across device types
  • Just a 100-millisecond delay in load time hurt conversion rates by up to 7%
  • Bounce rates were highest among mobile shoppers and lowest among those using tablets

But there may be more behind this than just slow load times. We also have to consider what modes we’re in when we’re interacting with our mobile device.

In 2010, Microsoft did a fascinating research project that looked at how user behaviors varied from desktop to tablet to smart phone. The research was headed by Jacquelyn Krones, who was a Search Product Manager at the time. Search was the primary activity examined, but there was a larger behavioral context that was explored. While the study is 7 years old, I think the core findings are still relevant. The researchers found that we tend to have three large buckets of behaviors: missions, explorations and excavations. Missions were focused tasks that were usually looking for a specific piece of information – i.e. looking for an address or phone number. Explorations where more open ended and less focused on a given destination – i.e. seeing if there was any thing you wanted to do this Friday night. Excavations typically involved multiple tasks within an overarching master task – i.e. researching an article. In an interview with me, Krones outlined their findings:

“There’s clearly a different profile of these activities on the different platforms. On desktops and laptops, people do all three of the activities – they conduct missions and excavations and explorations.

“On their phones we expected to see lots of missions – usually when you use your mobile phone and you’re conducting a search, whatever you’re doing in terms of searching is less important than what’s going on with you in the real world – you’re trying to get somewhere, you’re having a discussion with somebody and you want to look something up quick or you’re trying to make a decision about where to go for dinner.

“But we were surprised to find that people are using their mobile phones for exploration. But once we saw the context, it made sense – people have a low tolerance for boredom. Their phone is actually pretty entertaining, much more entertaining than just looking at the head in front of you while you’re waiting in line. You can go check a sports score, read a story, or look at some viral video and have a more engaged experience.

“On tablets, we found that people are pretty much only using them for exploration today. I had expected to see more missions on tablets, and I think that that will happen in the future, but today people perceive their mobile phone as always with them, very personal, always on, and incredibly efficient for getting information when they’re in mission mode.”

Another study, coming out The University of British Columbia Okanagan, also saw a significant difference in behavioral modality when it came to interacting with touch screens. Assistant Professor Ying Zhu was the principal author:

“The playful and fun nature of the touchscreen enhances consumers’ favour of hedonic products; while the logical and functional nature of a desktop endorses the consumers’ preference for utilitarian products,” explains Zhu.

“Zhu’s study also found that participants using touchscreen technology scored significantly higher on experiential thinking than those using desktop computers. However, those on desktops scored significantly higher on rational thinking.”

I think what we have here is an example of thinking: fast and slow. I suspect we’re compartmentalizing our activities, subconsciously setting some aside for completion on the desktop. I would suspect utilitarian type purchasing would fall into this category. I know that’s certainly true in my case. As Dr. Zhu noted, we have a very right brain relationship with touchscreens, while desktops tend to bring out our left-brain. I have always been amazed at how our brains subconsciously prime us based on anticipating an operating environment. Chances are, we don’t even realize how much our behaviors change when we move from a smart phone to a tablet to a desktop. But I’d be willing to place a significant wager that it’s this subconscious techno-priming that’s causing some of these behavioural divides between devices.

Slow load times are never a good thing, on any device, but while they certainly don’t help with conversions, they may not be the only culprit sitting between a user and a purchase. The device itself could also be to blame.