The Decentralization of Trust

Forget Bitcoin. It’s a symptom. Forget even Blockchain. It’s big – but it’s technology. That makes it a tool. Which means it’s used at our will. And that will is the real story. Our will is always the real story – why do we build the tools we do? What is revolutionary is that we’ve finally found a way to decentralize trust. That runs against the very nature of how we’ve defined trust for centuries.

And that’s the big deal.

Trust began by being very intimate – ruled by our instincts in a face-to-face context. But for the last thousand years, our history has been all about concentration and the mass of everything – including whom we trust. We have consolidated our defense, our government, our commerce and our culture. In doing so, we have also consolidated our trust in a few all-powerful institutions.

But the past 20 years have been all about decentralization and tearing down power structures, as we invent new technologies to let us do that. In that vien, Blockchain is a doozy. It will change everything. But it’s only a big deal because we’re exerting our will to make it a big deal. And the “why” behind that is what I’m focusing on.

For right or wrong, we have now decided we’d rather trust distribution than centralization. There is much evidence to support that view. Concentration of power also means concentration of risk. The opportunity for corruption skyrockets. Big things tend to rot from the inside out. This is not a new discovery on our part. We’ve known for at least a few centuries that “absolute power corrupts absolutely.”

As the world consolidated it also became more corrupt. But it was always a trade off we felt we had to make. Again, the collective will of the people is the story thread to follow here. Consolidation brought many benefits. We wouldn’t be where we are today if it wasn’t for hierarchies, in one form or another. So we willing subjugated ourselves to someone – somewhere – hoping to maintain a delicate balance where the risk of corruption was outweighed by a personal gain. I remember asking the Atlantic’s noted correspondent, James Fallows, a question when I met him once in China. I asked how the average Chinese citizen could tolerate the paradoxical mix of rampant economical entrepreneurialism and crushing ideological totalitarianism. His answer was, “As long as their lives are better today than they were yesterday, and promise to be even better tomorrow, they’ll tolerate it.”

That pretty much summarizes our attitudes towards control. We tolerated it because if we wanted our lives to continue to improve, we really didn’t have a choice. But perhaps we do now. And that possibility has pushed our collective will away from consolidated power hubs and towards decentralized networks. Blockchain gives us another way to do that. It promises a way to work around Big Money, Big Banks, Big Government and Big Business. We are eager to do so. Why? Because up to now we have had to place our trust in these centralized institutions and that trust has been consistently abused. But perhaps Blockchain technology has found a way to distribute trust in a foolproof way. It appears to offer a way to make everything better without the historic tradeoff of subjugating ourselves to anyone.

However, when we move our trust to a network we also make that trust subject to unanticipated network effects. That may be the new trade-off we have to make. Increasingly, our technology is dependent on networks, which – by their nature – are complex adaptive systems. That’s why I keep preaching the same message – we have to understand complexity. We must accept that complexity has interaction affects we could never successfully predict.

It’s an interesting swap to consider – control for complexity. Control has always offered us the faint comfort of an illusion of predictability. We hoped that someone who knew more than we did was manning the controls. This is new territory for us. Will it be better? Who can say? But we seem to building an irreversible head of steam in that direction.

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?

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.

We Don’t Need More Athletes and Models – We Do Need More People Who Understand Complexity

Have you seen the Verizon ad?

 

The one that starts with LeBron James walking towards the camera. He tells us “We don’t need more LeBrons” He’s followed in quick succession by other celebrities, including model Adriana Lima, quarterback Drew Brees and soccer star David Villa, all saying we don’t need more of their kind. The ad wraps up by saying what we do need is more people in science and technology to fill the 4 million jobs available. Verizon is pitching in by supporting education in STEM subjects (Science, Technology, Engineering and Math). The world, apparently, needs a lot more engineers.

Fair enough. The world runs on science and technology. But there’s an unintended consequence that comes with that. Technology is making the world a more complex place. And what we really need is more people that understand what complexity means.

By complexity, I don’t mean complicated. Those are two different things. I mean complexity in its classic sense – coming from the Latin “com” – meaning “together” – and “plex” – meaning “woven”. “Woven together” is a pretty good starting point for understanding complexity. It’s a concept that depends on connection, and we are more connected than ever before. Whether we like it or not, with connection comes complexity. And when we’re talking about complexity, we’re talking about a whole new ball game where all traditional bets are off.

There’s another funny thing about complexity. It’s nothing new. The world has always been complex. Biology has long been the domain of complex adaptive systems. This is true of all of the physical sciences. Benoit Mandelbrot found fractal complexity in leaves and the coastline of England. Quantum physics has always been around. It wasn’t invented at the beginning of the last century by Max Plank, Albert Einstein and Niels Bohr. It just took us most of our history as a species to discover it, hiding there beneath the deceptively simple rules of Isaac Newton. Complexity has always been part of nature. We’ve just been ignoring it for a long, long time, believing with all our hearts in a simpler, more comprehensible world.

Humans hate complexity, because complexity brings with it unpredictability and an inherent lack of control. It leads naturally into chaos. We much prefer models with foreseeable outcomes. We have been trying for many years to predict the weather, with very limited success. Why? Because weather is complex and often chaotic. And it’s getting more so, not less.

But the extreme weather we’re seeing more and more of is analogous to many parts of our world. Complexity is rearing its head in more and more places. It lies beneath everything. In the words of the Santa Fe Institute, the self-proclaimed world headquarters for complexity science — “(they) endeavor to understand and unify the underlying, shared patterns in complex physical, biological, social, cultural, technological, and even possible astrobiological worlds”

Which means complexity is everywhere. It impacts everything. And almost none of us understand it. But we’ve got to figure this stuff out, because the stakes are huge.

Let’s take something as important to us as democracy, for instance.

There is nothing especially complex about the idea of democracy. But the model of democracy is a different beast, because it relies on the foundation of our society, which is incredibly complex. Democracy is dependent on unwritten rules, which are in turn dependent on conventions and controls that have been inherent in our society. These are what have been called the “soft guardrails of democracy”. And they are being eroded by our newly connected complexity. A few weeks ago, some of America’s top political scientists got together at Yale University to talk about democracy and almost all of them agreed – democracy is in deep trouble. Yascha Mounk, from Harvard, summed up their collective thoughts succinctly: “If current trends continue for another 20 or 30 years, democracy will be toast.”

So complexity is something we should be learning about. But where to start? And when? Currently, if people do study complexity science, it’s generally at the post-grad level. And that’s just a handful of people, at a few universities. We need to start understanding complexity and it’s implications much sooner. It should be covered in grade school. But there’s no one to teach it, because the majority of teachers have no idea what I’m talking about. In a recent dissertation, a researcher from the University of Pennsylvania asked science teachers in a number of schools in Singapore if they were familiar with complexity. The findings were disheartening, “a large sample of ninety Grades 11 and 12 science teachers in six randomly- selected schools across Singapore revealed as many as 80% of the teachers reported that they did not have prior knowledge or heard of complex systems.” By the way, Singapore is consistently rated best in the world for science education. Here in North America, we trail by a significant margin. If this is a problem there, it’s a bigger problem here.

If you’re old enough to remember the movie the Graduate, there was a scene where “the Graduate” – played by Dustin Hoffman – was wandering around his parent’s cocktail party when he was cornered by a family friend; Mr McGuire. McGuire offered a word of career advice. Literally – one word:

“I just want to say one word to you – just one word. Are you listening? Plastics.”

That was 50 years ago. Today, my word is “complexity.”

Are you listening?

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.

 

I, Robot….

Note: No Artificial Intelligence was involved in the creation of this column.

In the year 1942, science fiction writer Isaac Asimov introduced the 3 Rules of Robotics in his collection of short stories, I, Robot..

  1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
  2. A robot must obey the orders given it by human beings except where such orders would conflict with the First Law.
  3. A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws.

Asimov had the rules as coming from the Handbook of Robotics, 56th Edition, 2058 A.D. What was once an unimaginably distant time in the future is now knocking with increasing intensity on the door of the present. And Elon Musk, for one, is worried. “AI is a fundamental risk to the existence of human civilization.” Musk believes, Rules of Robotics or no, we won’t be able to control this genie once it gets out of its bottle.

Right now, the genie looks pretty benign. In the past year, the Washington Post has used robot reporters to write over 850 stories. The Post believes this is a win/win with their human reporters, because the robot, named Heliograf, can:

  • Cover stories that wouldn’t have been covered due to lack of human resources
  • Do the factual heavy lifting for human reporters
  • Alert humans to possible news stories in big data sets

So, should we fear or cheer robots? I think the Post’s experiment highlights two areas that AI excels at, and indicates how we might play nice with machines.

For AI to work effectively, the dots have to be pretty well sketched out. When they are, AI can be tireless in scouting out relevant facts and data where humans would tend to get bored easily. But humans are still much better at connecting those dots, especially when no obvious connection is apparent. We do it through something called intuition. It’s at least one area where we can still blow machines away.

Machines are also good at detecting patterns in overwhelming amounts of data. Humans tend to overfit…make the data fit our narratives. We’ll come back to this point in a minute, but for now, let’s go back to intuition. It’s still the trump card we humans hold. In 2008, Wired editor Chris Anderson prematurely (and, many believe, incorrectly) declared the Scientific Method dead, thanks to the massive data sets we now have available:

“We can analyze the data without hypotheses about what it might show. We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.”

Anderson gets it partly right, but he also unfairly gives intuition short shrift. This is not a zero sum game. Intuition and A.I. can and should play nicely together. As I mentioned a few weeks ago, human intuition was found to boost the effectiveness of an optimization algorithm by 25%.

Evolutionary biologist Richard Dawkins recently came to the defense of intuition in Science, saying:

“Science proceeds by intuitive leaps of the imagination – building an idea of what might be true, and then testing it”

The very human problem comes when we let our imaginations run away from the facts, bending science to fit our hypotheses:

“It is important that scientists should not be so wedded to that intuition that they omit the very important testing stage.”

There is a kind of reciprocation here – an oscillation between phases. Humans are great at some stages – the ones that require intuition and imagination -and machines are better at others – where a cold and dispassionate analysis of the facts is required. Like most things in nature that pulse with a natural rhythm, the whole gains from the opposing forces at work here. It is a symphony with a beat and a counterbeat.

That’s why, for the immediate future anyway, machines should bend not to our will, but to our imagination.