echovar

It’s common to think of someone who refers to themselves in the third person as narcissistic. They’ve posited a third person outside of themselves, an entity who in some way is not fully identical with the one who is speaking. When we speak on a social network, we speak in the third person. We see our comment enter the stream not attributed to an “I”, but in the third person.

The name “narcissism” is derived from Greek mythology. Narcissus was a handsome Greek youth who had never seen his reflection, but because of a prediction by an Oracle, looked in a pool of water and saw his reflection for the first time. The nymph Echo–who had been punished by Hera for gossiping and cursed to forever have the last word–had seen Narcissus walking through the forest and wanted to talk to him, but, because of her curse, she wasn’t able to speak first. As Narcissus was walking along, he got thirsty and stopped to take a drink; it was then he saw his reflection for the first time, and, not knowing any better, started talking to it. Echo, who had been following him, then started repeating the last thing he said back. Not knowing about reflections, Narcissus thought his reflection was speaking to him. Unable to consummate his love, Narcissus pined away at the pool and changed into the flower that bears his name, the narcissus.

The problem of internet identity might easily be solved by having all people and systems use the third person. A Google identity would be referred to within Google in the third person, as though it came from outside of Google. Google’s authentication and authorization systems would be decentralized into an external hub, and Google would use them in the same way as a third party. Facebook, Twitter, Microsoft, Apple and Yahoo, of course, would follow suit. In this environment a single internet identity process could be used across every web property. Everyone is a stranger, everyone is from somewhere else.

When we think of our electronic identity on the Network, we point over there and say, “that’s me.” But “I” can’t claim sole authorship of the “me” at which I gesture. If you were to gather up and value all the threads across all the transaction streams, you’d see that self-asserted identity doesn’t hold a lot of water. It’s what other people say about you when you’re out of the room that really matters.

What does it matter who is speaking, someone said, what does it matter who is speaking?
Samuel Beckett, Texts for Nothing

Speaking in the third person depersonalizes speech. Identity is no longer my identity, instead it’s the set of qualities that can be used to describe a third person. And if you think about the world of commercial transactions, a business doesn’t care about who you are, they care if the conditions for a successful transaction are present. Although they may care about collecting metadata that allows them to predict the probability that the conditions for a transaction might recur.

When avatars speak to each other, the conversation is in the third person. Even when the personal pronoun “I” is invoked, we see it from the outside. We view the conversation just as anyone might.

Software is often designed with three “numbers” in mind: zero, one and infinity. In this case, infinity tends to mean that a value can be any number. There’s no reason to put random or artificial limits on what a number might be. This idea that any number might do is at the bottom of what some people call information overload. For instance, we can very easily build a User Managed Access (UMA) system with infinite reach and granularity. Facebook, while trying to respond to a broad set of use cases, produced an access control / authorization system that answered these use cases with a complex control panel. Facebook users largely ignored it, choosing instead to wait until something smaller and more usable came along.

Allow none of foo, one of foo, or any number of foo.

Privacy is another way of saying access control or authorization. We tend to think about privacy as personal information that is unconnected, kept in a vault that we control. When information escapes across these boundaries without our knowledge, we call this a data breach. This model of thinking is suitable for secrets that are physically encoded on paper or the surface of some other physical object. Drama is injected into this model when a message is converted to a secret code and transmitted. The other dramatic model is played out in Alfred Hitchcock’s The 39 Steps, where a secret is committed to human memory.

Personal information encoded in electronic communications systems on the Network is always already outside of your personal control. This idea of vaults and breaching boundaries is a metaphor imported from a alien landscape. When we talk about privacy in the context of the Network, it’s more a matter of knowing who or what has access to your personal information; who or what can authorize access to your personal information; and how this leg is connected to the rest of the Network. Of course, one need only Google oneself, or take advantage of any of the numerous identity search engines to see how much of the cat is already out of the bag.

The question arises, how much control do we want over our electronic personal information residing on the Network? Each day we throw off streams of data as we watch cable television, buy things with credit cards, use our discount cards at the grocery, transfer money from one account to another, use Twitter, Facebook and Foursquare. The appliances in our homes have unique electrical energy-use signatures that can be recorded as we turn on the blender, the toaster or the lights in the hallway.

In some sense, we might be attempting to recreate a Total Information Awareness (TIA) system that correlates all data that can be linked to our identity. Can you imagine managing the access controls for all these streams of data? It would be rather like having to consciously manage all the biological systems of our body. A single person probably couldn’t manage the task, we’d need to bring on a staff to take care of all the millions of details.

Total Information Awareness would be achieved by creating enormous computer databases to gather and store the personal information of everyone in the United States, including personal e-mails, social network analysis, credit card records, phone calls, medical records, and numerous other sources, without any requirement for a search warrant. This information would then be analyzed to look for suspicious activities, connections between individuals, and “threats”. Additionally, the program included funding for biometric surveillance technologies that could identify and track individuals using surveillance cameras, and other methods.

Here we need to begin thinking about human numbers, rather than abstract numbers. When we talk about human factors in a human-computer interaction, generally we’re wondering how flexible humans might be in adapting to the requirements of a computer system. The reason for this is that humans are more flexible and adapt much more quickly than computers. Tracing the adaptation of computers to humans shows that computers haven’t really made much progress.

Think about how humans process the visual information entering our system through our eyes. We ignore a very high percentage of it. We have to or we would be completely unable to focus on the tasks of survival. When you think about the things we can truly focus our attention on at any one time, they’re fewer than the fingers on one hand. We don’t want total consciousness of the ocean of data in which we swim. Much like the Total Information Awareness system, we really only care about threats and opportunities. And the reality, as Jeff Jonas notes, is that while we can record and store boundless amounts of data— we have very little ability to make sense of it.

Man continues to chase the notion that systems should be capable of digesting daunting volumes of data and making sufficient sense of this data such that novel, specific, and accurate insight can be derived without direct human involvement.  While there are many major breakthroughs in computation and storage, advances in sensemaking systems have not enjoyed the same significant gains.

When we admire simplicity in design, we enjoy finding a set of interactions with a human scale. We see an elegant proportion between the conscious and the unconscious elements of a system. The unconscious aspects of the system only surface at the right moment, in the right context. A newly surfaced aspect displaces another item to keep the size of focus roughly the same. Jeff Jonas advocates designing systems that engage in perpetual analytics, always observing the context to understand what’s changed, the unconscious cloud is always changing to reflect the possibilities of the conscious context.

We’re starting to see the beginnings of this model emerge in location-aware devices like the iPhone and iPad. Mobile computing applications are constantly asking about location context in order to find relevant information streams. Generally, an app provides a focused context in which to orchestrate unconscious clouds of data. It’s this balance between the conscious and the unconscious that will define the new era of applications. We’ll be drawn to applications and platforms, that are built with human dimensions— that mimic, in their structure, the way the human mind works.

Our lives are filled with infinities, but we can only live them because they are hidden.

“Just checking in.” It’s such a neutral phrase. It doesn’t imply any engagement or transaction— the connection has been opened and tested, but no activity is required or expected. From a Unix command line, the ping serves a similar function. The social geo-location services have brought the “check in” into common parlance on the Network. The FourSquare check in can be a neutral communication— no message attached, merely a statement that I’m at such-and-such a location.

The neutrality of the “check in” gesture began to interest me as I started thinking about the explicit gesture of giving a star rating to a restaurant. While I was recently visiting New York City, I decided to try and make use of the Siri and FourSquare apps on my iPhone. I could be observed sitting on a park bench saying ‘good pizza place near here’ into my iPhone and eagerly waiting for Siri to populate a list of restaurant options. I also checked in using FourSquare from several locations around Manhattan. When Siri returned its list of ‘good pizza places’ near me, it used the services of partner web sites that let users rate restaurants and other businesses on a one to five star system. When I asked for good pizza places that translated into the restaurants with the most stars.

The interesting thing about user ratings of businesses by way of the Network is that it’s completely unnecessary for the user to actually visit, or be a customer of, the business. The rating can be entirely fictional. Unless you personally know the reviewer and the context in which the review is proffered— a good, bad or ugly review may be the result of some alternate agenda. There’s no way to determine the authenticity of an unknown, or anonymous, reviewer. Systems like eBay have tried to solve this problem using reputation systems. Newspapers have tried to solve this problem by hiring food critics who have earned the respect of the restaurant ecosystem.

So, while Siri did end up recommending a good Italian restaurant, the Chinese restaurant it recommended was below par. Both restaurants had the same star ratings and number of positive reviews. This got me thinking about the securitization of the networked social gesture. Once a gesture has even a vaguely defined monetary value there’s a motivation to game the system. If more stars equals a higher ranking on Siri’s good pizza place list, then how can a business get more stars? What’s the cost?

I ran across a tweet that summed up the dilemma of wanting a list of ‘good pizza places’ rather than simply ‘pizza places.’ I use FriendFeed as a Twitter client, and while watching the real-time stream I saw an interesting item float by. Tara Hunt retweeted a micro-message from Deanna Zandt referring to a presentation by Randy Farmer at the Web 2.0 conference on Building Web Reputation systems. Deanna’s message read: “If you show ppl their karma, they abuse it.” When reputation is assigned a tradable value, it will be traded. In this case, ‘abuse’ means traded in an unintended market.

Another example of this dilemma cropped up in a story Clay Shirky told at the Gov 2.0 summit about a day care center. The day care center had a problem with parents who arrived late to pick up their children. Wanting to nip the problem in the bud, they instituted a fine for late pick up. What had been a social contract around respecting the value of another person’s time was transformed into a new service with a set price tag. “Late pick up” became a new feature of the day care center, and those parents who could afford it welcomed the flexibility it offered them. Late pick ups tripled, the new feature was selling like hot cakes. Assigning a dollar value to the bad behavior of late pick ups changed the context from one of mutual respect to a payment for service. Interestingly, even when the fines were eliminated, the higher rate of bad behavior continued.

Now let’s tie this back to the neutral gesture of the check in. While in some respect the reporting of geolocation coordinates is a mere statement of fact— there’s also the fact that you’ve chosen to go to the place from which you’ve checked in. There’s a sense in which a neutral check in from a restaurant is a better indicator of its quality than a star rating accompanied by explicit user reviews. If a person in my geo-social network checks in from a restaurant every two weeks, or so, I’d have to assume that they liked the restaurant. The fact that they chose to go there more than once is a valuable piece of information to me. However when game mechanics are assigned to the neutral check in gesture, a separate economics is overlaid. If the game play, rather than the food, provides the motivation for selecting a restaurant, then the signal has been diluted by another agenda.

By binding the check in to the place via the geolocation technology of the device, a dependable, authentic piece of information is produced. Social purchase publishing services, like Blippy, take this to the next level. Members of this network agree to publish a audit trail of their actual purchases. By linking their credit card transaction report in real time to a publishing tool, followers know what a person is actually deciding to purchase. A pattern of purchases would indicate some positive level of satisfaction with a product or service.

The pattern revealed in these examples is that the speech of the agent cannot be trusted. So instead we look to the evidence of the transactions initiated by the agent, and we examine the chain of custody across the wire. A check in, a credit card purchase— these are the authentic raw data from which an algorithm amalgamates some probability of the good. We try to structure the interaction data such that it has the form of a falsifiable proposition. The degree to which a statement of quality can be expressed as an on or off bit defines a machine’s ability to compute with it. A statement that is overdetermined, radiating multiple meanings across multiple contexts doesn’t compute well and results in ambiguous output. The pizza place seems to occupy multiple locations simultaneously across the spectrum of good to bad.

Can speech be rehabilitated as a review gesture? I had a short conversation with Randy Farmer at the recent Internet Identity Workshop (IIW 10) about what he calls the “to: field” in networked communications. The basic idea is that all speech should be directed to some individual or group. A review transmitted to a particular social group acquires the context of the social relations within the group. Outside of that context its value is ambiguous while purporting to be clear. Farmer combines restricted social networks and falsifiable propositions in his post ‘The Cake is a Lie” to get closer to an authentic review gesture and therefore a more trustworthy reputation for a social object.

Moving through this thought experiment one can see the attempt to reduce human behavior and social relations to falsifiable, and therefore computable, statements. Just as a highly complex digital world has been built up out of ones and zeros, the search for a similar fundamental element of The Good is unfolding in laboratories, research centers and start ups across the globe. Capturing the authentic review gesture in a bottle is the new alchemy of the Network.

What’s So Funny About Peace, Love and Understanding?
Nick Lowe

As I walk through
This wicked world
Searching for light in the darkness of insanity.

I ask myself
Is all hope lost?
Is there only pain and hatred, and misery?

And each time I feel like this inside,
There’s one thing I wanna know:
What’s so funny about peace love & understanding? ohhhh
What’s so funny about peace love & understanding?

And as I walked on
Through troubled times
My spirit gets so downhearted sometimes
So where are the strong
And who are the trusted?
And where is the harmony?
Sweet harmony.

Cause each time I feel it slipping away, just makes me wanna cry.
What’s so funny bout peace love & understanding? ohhhh
What’s so funny bout peace love & understanding?

So where are the strong?
And who are the trusted?
And where is the harmony?
Sweet harmony.

Cause each time I feel it slippin away, just makes me wanna cry.
What’s so funny bout peace love & understanding? ohhhh
What’s so funny bout peace love & understanding? ohhhh
What’s so funny bout peace love & understanding?

A couple of three things came together for me and I wanted to set them down next to each other.

The first was Jon Udell’s keynote at the Kynetx Impact Conference. There was a moment when he was talking about a meeting in local government where the agenda was managed using a web-based tool. Udell talked about wanting to be able to hyperlink to agenda items, he had a blog post that was relevant to one of the issues under discussion. The idea was that a citizen attending the meeting, in person or virtually, should be able to link those two things together, and that the link should be discoverable by anyone via some kind of search. And while the linking of these two things would be useful in terms of reference, if the link simply pulled Udell’s blog post into the agenda at the relevant spot, that might be even more useful.

The reason this kind of thing probably won’t happen is the local government doesn’t want to be held responsible for things a citizen may choose to attach to their agenda items. A whole raft of legal issues are stirred up by this kind of mixing. However, while the two streams of data can’t be literally mixed, they can be virtually mixed by the user. Udell was looking at this agenda and mixing in his own blog post, creating a mental overlay. A technology like Kynetx allows the presentation of a literal overlay and could provide access to this remix to a whole group of people interested in this kind of interaction with the agenda of the meeting.

The Network provides the kind of environment where two things can be entirely separate and yet completely mixed at the same time. And the mixing together can be located in a personal or group overlay that avoids the issues of liability that the local government was concerned about.

The second item was Apple’s acquisition of Siri. While I never made the connection before, the kind of interaction that Siri gives users is very similar to what Kynetx is doing. I can ask Siri with a voice command for the best pizza places around here. Siri orchestrates a number of data services to provide me with a list of local pizza joints. Siri collects identity information on an as needed basis to provide better results. While Kynetx is a platform for assembling these kinds of orchestrations, Siri is a roll up of our most common activities – find me the best mexican restaurant; where is this movie playing? What’s the weather like in New York City; Is my flight on time?

While I haven’t hooked my credit card up to Siri yet, it does have that capability so that a transaction can be taken all the way to completion. On the other hand, Apple’s iTunes has had my credit card information for years. Once the deal closes, Siri will have acquired my credit card.

Phil Windley, in his presentation to the Kynetx conference, discussed an application that could be triggered by walking in to, or checking in to, a Borders bookstore. The Kynetx app would push a message to me telling me that an item on my Amazon wishlist was available for purchase in the store. It strikes me that Siri might do the same thing by orchestrating my personal context data, my Amazon wishlist, which I’ve registered with it, a voice-based FourSquare check-in, and Border’s local inventory information.

The third and last item is Facebook’s open graph protocol. This is an attempt to use Facebook’s distribution power through it’s massive social graph to add “semantic” metadata to the public internet name space. This is an interesting example of the idea that the closed can include the open, but the open can’t include the closed. Jon Udell’s story about local government and blog posts has the same structure. The private network can include the public network, whereas the reverse isn’t true if each is to maintain its integrity.

While there’s a large potential for mischief in letting everyone make up their own metadata, it provides more fodder for the business of indexing, filtering and validating of data/metadata. Determining the authority of metadata is the same as determining the authority of data. The ‘meta’ guarantees syntax, but not semantics or value.

By setting these events next to each other, you can begin to see that to include both private and public data in an algorithm, you’ll have to do so from the stance of the personal and private. It makes me think that privacy isn’t dead, it’s the engine of the next evolution of the Network.

Thinking about what it might mean to stand at the intersection of technology and the humanities has resulted in an exploration with a very circuitous route.

The Network has been infused with humanity, with every aspect of human character— the bright possibilities and the tragic flaws.

On May 29, 1919, Arthur Stanley Eddington took some photographs of a total eclipse of the sun. Eddington had gone to Africa to conduct an experiment that might determine whether Newton’s or Einstein’s model was closer to physical reality.

During the eclipse, he took pictures of the stars in the region around the Sun. According to the theory of general relativity, stars with light rays that passed near the Sun would appear to have been slightly shifted because their light had been curved by its gravitational field. This effect is noticeable only during eclipses, since otherwise the Sun’s brightness obscures the affected stars. Eddington showed that Newtonian gravitation could be interpreted to predict half the shift predicted by Einstein.

My understanding of the physics is rather shallow, my interest is more in the metaphorics— in how the word-pictures we use to describe and think about the universe changed based on a photograph. Where the universe lined up nicely on a grid before the photograph, afterwards, space became curvaceous. Mass and gravity bent the space that light passed through. Assumed constants moved into the category of relativity.

The Network also appears to be composed of a neutral grid, its name space, through which passes what we generically call payloads of “content.” Each location has a unique identifier; the only requirement for adding a location is that its name not already be in use. You can’t stand where someone is already standing unless you displace them. No central authority examines the suitability of the node’s payload prior to its addition to the Network.

The universe of these location names is expanding at an accelerating rate. The number of addresses on the Network quickly outstripped our ability to both put them into a curated index and use, or even understand, that index. Search engines put as much of the Network as they can spider into the index and then use software algorithms to a determine a priority order of the contents of the index based on keyword queries. The search engine itself attempts to be a neutral medium through with the nodes of the Network are prioritized based on user query input.

Regardless of the query asked, the method of deriving the list of prioritized results is the same. The method and production cost for each query is identical. This kind of equal handling of Network nodes with regard to user queries is the search engine equivalent of freedom, opportunity and meritocracy for those adding and updating nodes on the Network. The algorithms operate without prejudice.

The differential value of the queries and prioritized link lists is derived through an auction process. The cost of producing each query/result set is the same—it is a commodity—but the price of buying advertising is determined by the intensity of the advertiser’s desire. The economics of the Network requires that we develop strategies for versioning digital commodities and enable pricing systems linked to desire rather than cost of production. Our discussions about “Free” have to do with cost-based pricing for digital information goods. However, it’s by overlaying a map of our desires on to the digital commodity that we start to see the contours, the curvaceousness of this space, the segments where versioning can occur.

We’ve posited that the search algorithm treats all nodes on the Network equally. And more and more, we take the Network to be a medium that can fully represent human life. In fact, through various augmented reality applications, human reality and the Network are sometimes combined into a synthetic blend (medium and message). Implicitly we also seem to be asserting a kind of isomorphism between human life and the Network. For instance, sometimes we’ll say that on the Network, we “publish everything, and filter later.” The gist of this aphorism is that where there are economics of low-or-no-cost production, there’s no need to filter for quality in advance of production and transfer to the Network. Everything can be re-produced on the Network and then sorted out later. But when we use the word “everything,” do we really mean everything?

The neutral medium of the Network allows us to disregard the payload of contents. Everything is equivalent. A comparison could be made to the medium of language— anything can be expressed. But as the Network becomes more social, we begin to see the shape of our society emerge within the graph of nodes. Sigmund Freud, in his 1913 book entitled Totem and Taboo, looks at the markers that we place on the border of what is considered socially acceptable behavior. Ostensibly, the book examines the resemblances between the mental life of savages and neurotics. (You’ll need to disregard the archaic attitudes regarding non-European cultures)

We should certainly not expect that the sexual life of these poor, naked cannibals would be moral in our sense or that their sexual instincts would be subjected to any great degree of restriction. Yet we find that they set before themselves with the most scrupulous care and the most painful severity the aim of avoiding incestuous sexual relations. Indeed, their whole social organization seems to serve that purpose or to have been brought into relation with its attainment.

Freud is pointing to the idea that social organization, while certainly containing positive gestures, reserves its use of laws, restrictions and mores for the negative gesture. The structure of societal organization to a large extent rests on what is excluded, what is not allowed. He finds this common characteristic in otherwise very diverse socio-cultural groups. Totems and taboos bend and structure the space that our culture passes through.

In the safesearch filters employed by search engines we can see the ego, id and superego play out their roles. When we search for transgressive content, we remove all filtering. But presumably, we do, as a member of a society, filter everything before we re-produce it on the Network. Our “unfiltered” content payloads are pre-filtered through our social contract. Part of the uncomfortableness we have with the Network is that once transgressive material is embodied in the Network, the algorithms disregard any difference between the social and the anti-social. A boundary that is plainly visible to the human— and is in fact a structural component of its identity and society, is invisible to the machine. Every node on the Network is processed identically through the algorithm.

This issue has also been raised in discussions about the possibility of artificial intelligence. In his book Mirror Worlds, David Gelernter discusses a key difference between human memory and machine memory:

Well for one thing, certain memories make you feel good. The original experience included a “feeling good” sensation, and so the tape has “feel good” recorded on it, and when you recall the memory— you feel good. And likewise, one reason you choose (or unconsciously decide) not to recall certain memories is that they have “feel bad” recorded on them, and so remembering them makes you feel bad.

But obviously, the software version of remembering has no emotional compass. To some extent, that’s good: Software won’t suppress, repress or forget some illuminating case because (say) it made a complete fool of itself when the case was first presented. Objectivity is powerful.

Objectivity is very powerful. Part of that power lies in not being subject to personal foibles and follies with regard to the handling, sorting, connecting and prioritizing of data. The dark side of that power is that the objectivity of the algorithm is not subject to social prohibitions either. They simply don’t register. To some extent technology views society and culture as a form of exception processing, a hack grafted on to the system. As the Network is enculturated, we are faced with the stark visibility of terrorism, perversity, criminality, and prejudice. On the Network, everything is just one click away. Transgression isn’t hidden in the darkness. On the Network, the light has not yet been divided from the darkness. In its neutrality there is a sort of flatness, a lack of dimensionality and perspective. There’s no chiaroscuro to provide a sense of volume, emotion, limit and mystery.

And finally here’s the link back to the starting point of this exploration. A kind of libertarian connection has been made between the neutral quality of the medium of the Network and our experience of freedom in a democratic republic. The machine-like disregard for human mores and cultural practices is held up as virtue and example for human behavior. No limits can be imposed on the payloads attached to any node of the Network. The libertarian view might be stated that the fewest number of limitations should be applied to payloads while still maintaining some semblance of society. Freud is instructive here: our society is fundamentally defined by what we exclude, by what we leave out, and by what we push out. While our society is more and more inclusive, everything is not included. Mass and gravity bend the space that light passes through.

The major debates on the Network seem to line up with the contours of this pattern. China excludes Google and Google excludes China. Pornographic applications are banished from Apple’s AppStore. Android excludes nothing. Closed is excluded by Open, Open is included by Closed. Spam wants to be included, users want to exclude spam. Anonymous commenters and trolls should be excluded. Facebook must decide what the limits of speech are within the confines of its domain. The open internet excludes nothing. Facebook has excluded the wrong thing. The open internet has a right to make your trade secrets visible. As any node on the Network becomes a potential node in Facebook’s social/semantic graph, are there nodes that should be taboo? How do we build a civil society within the neutral medium of the Network? Can a society exist in which nothing is excluded?

In the early days of the Network, it was owned and occupied by technologists and scientists. The rest of humanity was excluded. As the Network absorbs new tribes and a broader array of participants, its character and its social contract has changed. It’s a signal of a power shift, a dramatic change in the landscape. And if you happen to be standing at the crossroads of technology and the humanities, you might have a pretty good view of where we’re going.

There are natural and abstract surfaces onto which we overlay our stories. The sphere that we paint water and land masses on represents the natural shape of our small planet. For other endeavors we designate abstract work surfaces. One early example of this idea is the organizational scheme of Diderot’s encyclopedia. While subjects were laid out in alphabetical order, the book also contained conceptual maps and cross-linking to super-impose the natural shape of the history of ideas on to the abstract system of organization. This blending of the abstract and natural (GUI and NUI) that informed Diderot’s project is a theme that has returned as we build out the mobile interaction points of the Network.

The alphabet is ingrained at such an early age through the use of song, that we often feel it’s an artifact of the natural world. The fact that so many of us can recite a randomly ordered set of 26 symbols is a triumph of education and culture. The neutrality and static nature of the alphabetic sequence allows us to organize and find things across a community with little or no coordination. Although, the static nature of the alphabetic sequence is rather unforgiving. For instance, my book and CD collections are both alphabetically ordered. Or at least they were at one point in time. And although I understand why things get into a muddle, it doesn’t help me find the book that’s just flashed through my mind as I look at the shelves in front of me.

These maps, both natural and abstract, that we use to navigate our way through the world are becoming more and more significant. Especially as our ability to represent the physical world through the Network becomes more high definition. Just as with the alphabet, we’ll tend to forget that the map is not the territory. Borges’s story about the futility of a map scaled to exactly fit the territory has an important message for our digital age:

In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province. In time, those Unconscionable Maps no longer satisfied, and the Cartographers Guilds struck a Map of the Empire whose size was that of the Empire, and which coincided point for point with it. The following Generations, who were not so fond of the Study of Cartography as their Forebears had been, saw that that vast Map was Useless, and not without some Pitilessness was it, that they delivered it up to the Inclemencies of Sun and Winters. In the Deserts of the West, still today, there are Tattered Ruins of that Map, inhabited by Animals and Beggars; in all the Land there is no other Relic of the Disciplines of Geography.

Google spiders the Network for its search index and then presents algorithmically-processed search engine results pages in response to user queries. The larger map is not in plain view, just the slice that we request. It seems as though for any question we can imagine, Google will have some kind of an answer. The map appears to cover the territory point for point. Even the ragged edge of the real-time stream is framed in to the prioritized list of responses. The myth of completeness covers over the gap between the map and the territory, and the even the other maps and communications modes we might use within the territory.

If a tree falls in a forest in China, and there’s not a Google search result page linking to the event, does it make a sound?

Reading and writing to the maps of the Network has long been facilitated by Graphical User Interfaces. While the abstract metaphors of the GUI will never go away entirely, we’re seeing a new set of Natural User Interfaces emerge. Designing a better, simpler and clearer abstraction is giving way to finding the gestures that map to the natural contours of our everyday lived experience.

Natural interaction with high-definition representations via the Network has opened the door to what David Gelernter calls Mirror Worlds. Just as the fixed nature of the alphabet provided us with a set of coordinates on which to hang our collections of things, geo-coordinates will provide a similar framework for mirror worlds. Both Google and Microsoft have pasted together a complete base map of our entire planet from satellite photography and vector graphic drawings.

As with the search index, the base map provides us with a snapshot in time; we see the most recent pictures. The base is a series of photographs, not a real-time video stream. Even at this early phase of the mirror world we can see an overlay of real-time data and messages projected on to the base map. While we might expect the base map to move along a curve toward higher and higher fidelity and definition, it seems more likely that the valuable detail will find its home in the overlays.

The base map will be a canvas, or a skeleton, on which we will overlay meanings, views, opinions, transaction opportunities and conversations. While there will be a temptation to somehow ‘get it right.’ To present a compete and accurate representation of the territory— mapping each point, and each data point, with absolute fidelity and accuracy, it’s here where we wander off into Borges’s land of scientific exactitude and the library of babel. The base map only needs to be good enough to give us a reference point to hang our collections of things on. And, of course, realism is only one mode of expression.

The creation of overlays is the province of the mashup, the mixing of two distinct data sources in real time. Maps and twitter, apartment locations and craigslist, potholes and San Francisco streets, a place/time and photographs of a special event— all these implementations have demonstrated that geo-mashups are possible and happening continuously. But as this sea of real-time data washes across the surface of the map, we’d like a seat at the mixing board. A URL that pre-mixes two or more data sets has it’s use, but it’s a static implementation.

The framework of selectors and action cards may have the most promise here. Action cards are already engineered to work as overlays to base maps of any kind. When mixing and matching geo-location coordinates on the base map with streams of data, including identity-specific private data, is just a matter of throwing action cards from your selector on to a base map, you’ll have a natural user interface to a mirror world. And while the gap between the map and the territory will remain, as Baudrillard might say, the map begins to become a kind of territory of its own.

We see the shift beginning to play out as fragments of the picture leak out on to the Network. Presumably the strategy was set 4 or 5 years ago, but the artifacts of its implementation are now appearing in regular release cycles. As we fit more pieces into the puzzle, the picture is coming in to focus.

Most technology is only useful to the extent that people are around it. Some technical experiences are powerful enough to draw people to the technology. Recently we’ve seen a new landscape emerge where powerful technology is created that can follow people around wherever they might go. The big players are positioning themselves to flourish in this new world.

It may have been Ray Ozzie who most succinctly drew the boundaries of this new landscape by coining the phrase: “three screens and a cloud.”

“So, moving forward, again I believe that the world some number of years from now in terms of how we consume IT is really shifting from a machine-centric viewpoint to what we refer to as three screens and a cloud:  the phone, the PC, and the TV ultimately, and how we deliver value to them.�

Ozzie’s phrase assumes the transition from locally-installed software to mostly cloud computing. It equalizes, and puts into the same field, three devices with historically separate development and usage paths. It also reduces all of the physical characteristics of the devices to the virtual, by way of a screen. In addition, the specific historical uses of these devices is replaced with delivering value from the Network. This implies that the functionality of these separate channels has been absorbed, blended, and can be delivered over the Network.

Some assume all of these devices are being absorbed into the personal computer, but if you track the evolution of the PC’s form factor you can see that it’s been reduced to an input (keyboard, mouse, camera, microphone) and an output (screen). The CPU has largely disappeared from the experience, it’s been reduced to the primary user interaction points. This is just a preparation for its ultimate absorption into the new three screen ecosystem.

There’s a fixed screen that creates a large high-definition experience and draws the user to it. This screen is appropriate for individuals or social groups. There’s a small mobile screen that the user takes with her everywhere she goes. This is a private screen, mostly for individual use. And there’s a medium-sized screen that you bring along when there’s a specific work/play purpose requiring a larger interaction surface, or when you need a device that bridges the private and the public.

If you think about the mobile phone market prior to the release of the iPhone; the transition to a platform in which a “small screen delivers value from the Network” seemed an impossibility. The players were entrenched and the carriers controlled the device market. The deal that was cut with AT&T, along with the revaluation of all values in the mobile device market, created a new starting point. There was no evolutionary path from the old mobile telephone to the iPhone. Although technically, it’s a small computer, Jobs was specifically aiming at creating the small personal screen.

“I don’t want people to think of this as a computer,� he said. “I think of it as reinventing the phone.�

Apple dropped “Computer” from it’s name and placed a large bet on the post-PC future with the iPhone. They have publicly reset their strategic direction and now describe themselves as a ‘mobile devices company.” The iPad doubles down on mobility and bets that the netbook was a rough sketch of what would be useful as a second screen in a mobile computing context. Both the iPhone and iPad— through multi-touch— have continued to reduce the frame of interaction. The screen is transformed and becomes both the input and the output for the user’s experience.

A key development in the ‘three screens and a cloud’ vision is the elimination of input devices. The screen, and the gesture space around it, serves the user for both input and output.

Google has begun to design their products with a mobile-first sensibility, and has even made public statements indicating that within three years the mobile screen will be the user’s primary interaction point with the Network. Both Chrome and Android point to mobile technology. (It should be pointed out that Android isn’t an operating system, it’s a java-based runtime that sits on top of a Linux OS. In this sense, it’s more similar to Silverlight)

Microsoft made a hard pivot with the Windows Phone 7 product. The “Life in Motion” theme and the кухниtiles and hub user interface moves away from file systems and toward lifestream themes. Add to this the porting of Silverlight to the Symbian, Android and Windows Phone platforms, throw in a connection to Azure, and you have a massive developer pipeline to the small screen.

We all like to paraphrase William Gibson on the future, it’s here, it’s just not evenly distributed yet. Although this isn’t different from most things: the past, the present and any object you’d care to choose from the physical universe. None are distributed evenly. Time, as the old joke goes, is nature’s way of keeping everything from happening at once. And therefore it follows that Space, is nature’s way of keeping everything from being just one big smoothie.

Progress toward the vision of “three screens and a cloud” will be measured in the distribution power of the major technology/media players. Apple has developed a significant channel through its innovative devices, iTunes and its physical stores. Microsoft has a strong base in operating system and office applications, but has expanded their distribution portfolio with Silverlight and Azure. Google’s distribution power is contained in their search index, which is exposed through their search query page. Facebook and Twitter’s distribution power is located in their social graph and the fire hose of their real-time index. All of these players have created vibrant developer ecosystems. This future won’t be distributed evenly, but to break through to mass markets, it will require both distribution power and a high-touch service channel.

The convergence implied in the phrase “three screens and a cloud” will consume the personal computer as well. It will be transformed, blended, and its functionality and services made accessible through any of the three screens. Preparations have long been underway for the a Post-PC future. The productivity once available only through the old devices and channels has been migrating quickly to the new Network-connected screens. Google has now joined Microsoft and Apple in attending to the possibilities of the large screen. These changes aren’t taking place as a gradual evolution, there’s a dangerous leap required to reach this new platform. Not every company will have the strength, capital and will to make that leap. And as the old devices and channels are hollowed out, at some point there will be a major collapse of the old platforms.

In the war rooms around the technology world, there’s a conversation going on about what it will take to get to the other side.

We move from one metaphor to its opposite, swinging like the bob on a pendulum. As our daily activities start throwing off streams of data, and we aggregate the data of others into composite parallel streams for our consumption— we look across the great divide and gaze at the old metaphor of files, folders, explorer/finder and the desktop. We hop back and forth between the metaphors, juggling streams and file folders. Wondering at what point will we leap across the chasm— and be mostly here in the stream, instead of mostly there on the desktop.

Personal computing is largely a matter of time and where the user spends it. Using applications to manipulate files located in folders has dominated our computing experience for a long while. Perhaps it was the steady stream of emails filling up our inboxes that provided the bridge to the stream of tweets flowing through our selective view of the consolidated lifestream. The metaphor of a desktop, folders and files gave us a handle for managing digital things inside the world of personal computing. A user might have a messy desktop or clean one. One could use up energy keeping things organized, putting them away in the proper folder— or allow them to become messy and spend energy finding things amidst the chaos.

The Desktop, folder, file model corresponds to the outline. Other words we might use to describe this kind of formation include hierarchy, name space or tree structure. The problem with things is that they don’t seem to know where they belong. They don’t take the initiative, always have to be told what to do. But, as long as the numbers stay small— not too many files or folders; not too many streams, or too much velocity, we can manage on either side of chasm. However, to stay small in this context means to exclude possibility. And once the numbers get large, the amount of energy required to keep things organized in outlines exceeds the value derived from the organization.

As David Weinberger points out in his book Everything is Miscellaneous, search transformed the value of the outline as a system of organization. Once everything has been indexed, sorted and ranked by algorithm, the findability of a thing doesn’t depend on its place in a hierarchy of categorization. This was a transition from organization based on the metaphor of extension in physical space to the random access metaphor of computational space.

Moving from Space to Time is another kind of transition. David Gelernter is one of the few who has spent time thinking about organization based on time and stream. Why should we have to give names to digital files or assign them to folders? Can’t things just take the initiative?

Once we shift the axis of organization from Space to Time, we begin to think about how we could relate to dynamic flows of information. We glance again at outlines, files and folder systems. The numbers are too big, if we look a the problem through that lens we’re inevitably lead to the view that there’s information overload. Clay Shirky rebuts that claim, and calls it filter failure. But a filter is only one of the tools we’re missing. The spatial metaphor can’t even give us the basic steps to dance to the music of time. We need a different starting point. Gelernter, in his essay “Time to Start Taking the Internet Seriously” improvises on a theme:

17. There is no clear way to blend two standard websites together, but it’s obvious how to blend two streams. You simply shuffle them together like two decks of cards, maintaining time-order — putting the earlier document first. Blending is important because we must be able to add and subtract in the Cybersphere. We add streams together by blending them. Because it’s easy to blend any group of streams, it’s easy to integrate stream-structured sites so we can treat the group as a unit, not as many separate points of activity; and integration is important to solving the information overload problem. We subtract streams by searching or focusing. Searching a stream for “snow” means that I subtract every stream-element that doesn’t deal with snow. Subtracting the “not snow” stream from the mainstream yields a “snow” stream. Blending streams and searching them are the addition and subtraction of the new Cybersphere.

18. Nearly all flowing, changing information on the Internet will move through streams. You will be able to gather and blend together all the streams that interest you. Streams of world news or news about your friends, streams that describe prices or auctions or new findings in any field, or traffic, weather, markets — they will all be gathered and blended into one stream. Then your own personal lifestream will be added. The result is your mainstream: different from all others; a fast-moving river of all the digital information you care about.

19. You can turn a knob and slow down your mainstream: less-important stream-elements will flow past invisibly and won’t distract you, but will remain in the stream and appear when you search for them. You can rewind your lifestream and review the past. If an important-looking document or message sails past and you have no time to deal with it now, you can copy the document or message into the future (copy it to “this evening at 10,” say); when the future arrives, the document appears again. You can turn a different knob to make your fast-flowing stream spread out into several slower streams, if you have space enough on your screen to watch them all. And you can gather those separate streams back together whenever you like.

So, what does the toolset look like? Filters are a part of it. We’ll want to filter the stream based on keywords, selected social circles, location, time period, velocity of flow, media type of hyperlinked citation, authority of a person in particular slice and more. The results of a filtered stream will look like the surfacing of particular elements of the stream and the backgrounding of others. Stream splicing is a pre-requisite of filtering, blending together a bunch of streams doesn’t result in information overload if you have the right tools at your command. You’ll be able to filter and pause; go to super slo-motion; fast foward and even loop a section, manage public and private streams in the same workspace, mix recorded on-demand tracks with live real-time feeds and add in your own commentary in a live chat running alongside.

Music may provide the most developed set of metaphors to think this new landscape through. Here’s Thelonius Monk stream splicing:

Here’s Michael Tilson Thomas blending streams, pulling themes to the surface, modulating the information as it flows past:

The blends and modulations can be sophisticated and complex or rough and full of energy. Some lads from Liverpool get a little bit louder now:

When Gelernter describes the process of searching for ‘snow’ in the composite stream, he gets to the difference between search and track. Search was built on the ability to spider the corpus of web pages and links, build an index, and provide ranked results in response to queries. Track is a tool to help us manage and explore the real-time stream. The days of the world wide web conceived as a static set of hyperlinked pages are coming to an end. The file is a finished product, the stream is always unfinished. Gelernter describes the emergent new cyberstructure:

13. The traditional web site is static, but the Internet specializes in flowing, changing information. The “velocity of information” is important — not just the facts but their rate and direction of flow. Today’s typical website is like a stained glass window, many small panels leaded together. There is no good way to change stained glass, and no one expects it to change. So it’s not surprising that the Internet is now being overtaken by a different kind of cyberstructure.

14. The structure called a cyberstream or lifestream is better suited to the Internet than a conventional website because it shows information-in-motion, a rushing flow of fresh information instead of a stagnant pool.

Your connection to the item in a stream is open ended— the flow is open, or it is closed. If it is open, there’ll be a next item, and one after that. All these items are unfinished, they need response, routing, to be ignored, or decorated with gestures. We find ourselves in the in-between moment between the photograph and the motion picture. Our tools are at the level of the zoetrope, the praxinoscope, or the magic lantern. But once we start thinking in terms of Time instead of Space, the world looks very different.

At this moment of transition, we now have the tools to analyze our direction. Are we building tools for the static hierarchical namespace of the world wide web, or building tools for the real-time stream of the Network? If we look at Salesforce’s introduction of Chatter, Google’s introduction of Buzz, the expansions of Facebook and Twitter, FourSquare and GoWalla, the augmentation capabilities of Kynetx— we can see a shift in orientation from Space to Time. And while we might expect the leap across the chasm to require the bravery of the early adopter, I think we’ll be surprised at how natural most people find living in the stream of time to be.

Throwing all the pieces out on the table, we connect the dots to make pictures. It’s a child’s game, creating figures out what look like a random set of numbered points. We tend to visualize the network of our social graph as a series of connected points. The pictures that emerge from those connections tell a story about our lives and experiences.

One of the interesting things about random sets of dots is that we tend to group them based on proximity, similarity, closure and continuation. We project pictures on to the dots, and once we see a particular picture, sometimes it’s hard to realize that someone might put the same set of dots together into something entirely different. It could even be an image that has the exact opposite meaning as the picture we see.

There are a couple of words used to describe a word that can mean the opposite of itself. Here are some examples of Antagonyms (or Contranyms):

Overlook: to pay attention to, to inspect (“We had time to overlook the contract.”) vs. to ignore

Oversight: Watchful and responsible care vs. An omission or error due to carelessness

It’s the context that tilts the meaning of the word this way or that.

When you think about the set of people you may be connected to within a large company, you can overlay several kinds of connections. A person may be a colleague, they might be in the same division, have the same pay grade, be part of a project, be a friend, or even a relative. In fact, we make a virtue out of the idea that the people we work with could also be our friends. Many companies like to talk about their employees as being like a family.

Google tested their Buzz product inside the walls of their company. No doubt it was used for work, play and a whole range of unforeseen kinds of communication. After a while all those modes of communication began to blend together. The boundaries between them broke down. Just as email and IM are used for personal and business purposes, Buzz would naturally be used in the same way. From a business perspective, the dots were connected into a powerful image of collaboration and efficiency. Twitter/FriendFeed clearly worked great as an enterprise application.

The personal, public and business realms are overlapping images that can be mapped to the same set of dots. However, it’s the exclusive disjunction of these sets that defines the boundaries. In some cases, the boundaries need to be strong and impenetrable. These are the cases Google didn’t consider carefully enough in their launch scenario. Other times a co-worker becomes a friend, or someone you went to school with becomes a colleague. Or maybe you just decided to start following your company’s CEO on Twitter. The context of the interaction tilts the meaning of the connection. There’s not a bright line separating our private, public and business lives that can be applied as a definitive rule.

Google launched Buzz as a consumer product, but tested it as an enterprise product. Although they plan to quickly integrate it into their office application suite. But like all messaging tools it will have a public and a private mode. It will address and contain personal, public and business conversation threads. And by flowing data from a user’s social circle and the real-time flow of Buzz (effectively a ping server) into their search algorithm, results pages can be personalized by social graph in real time.

Meanwhile, SalesForce.com introduces Chatter to the enterprise and rolls it out at no extra charge to all employees on the internal network. And while it will start inside the enterprise, Chatter will quickly expand to the boundaries and begin to cross over. From a business perspective, it’ll be used to turbo-charge collaboration and create real-time communication for project teams and business units. But very quickly you’ll see friends sending messages to each other about meeting up for lunch, and a public-personal communications channel will be opened within the enterprise. And the circles will connect and widen from there.

Here are a couple more Contranyms:

clip (attach to)  - clip (cut off from)

cleave (to cut apart)  - cleave (to seal together)

Salesforce.com calls itself the leader in Customer Relationship Management and Cloud Computing. Chatter may just be the communication medium that ultimately contains both CRM and its opposite number, VRM. Vendor Relationship Management is a reaction to the data toolsets belonging to the enterprise and not to the individual customer.

In a narrow sense, VRM is the reciprocal — the customer side — of CRM (or Customer Relationship Management). VRM tools provide customers with the means to bear their side of the relationship burden. They relieve CRM of the perceived need to “capture,” “acquire,” “lock in,” “manage,” and otherwise employ the language and thinking of slave-owners when dealing with customers. With VRM operating on the customer’s side, CRM systems will no longer be alone in trying to improve the ways companies relate to customers. Customers will be also be involved, as fully empowered participants, rather than as captive followers.

If you were to think about what kind of infrastructure you’d want to run VRM on, Salesforce.com would be ideal. To run the mirror image of CRM, you need the same set of services and scale. The individual Chatter account could be the doorway to a set of VRM services. I can already see developers using the Force.com platform to populate a VRM app store.

Some corporations will attempt to maximize the business value of each individual worker, stripping out all the extraneous human factors. Chinese walls will be erected to keep the outside from the inside, the personal from the business, and the public from the private. But when you put messaging and communications tools into the hands of people they will find ways to talk to each other— about work, life, play, the project, and the joke they just heard at the water cooler.

I’ve been trying to understand what Twitter lists are good for. Both Twitter’s new retweet feature and the list feature are imports from FriendFeed. Even in its current state, FriendFeed continues to be the R&D department for social media.

The thing I find uninteresting about lists is the fact that they’re mostly static— they simply serve as a kind of personal taxonomy. These Twitter users belong in this category. This is where we begin to feel the loss of track + filters. The assembly of a network of connected micro-messages around a set of keywords and run through a filter does what lists do dynamically and in real time. With the release of Twitter’s streaming API, nicknamed birddog, it’s possible we’ll start to see track-like features return— at least for subsets of the firehose. Manually curated lists at the level of classification are just a replay of RSS readers.

There are those who will say that if you’re using Twitter in a one-to-many broadcast mode, you’re not doing it right. But I think it’s pretty well established that Twitter is ambiguous and flexible enough to accommodate many modes of use simultaneously. Twitter lists strike me as a particularly good tool for news organizations.

If the New York Times or CNN has a team of journalists, photographers, videographers and radio journalists covering a breaking story like the earthquake in Haiti, a Twitter list would be a compact way to deliver coverage. Hyperlinks within the tweets could send readers off to breaking news, in-depth backgrounders and ongoing live conversations. CNN’s list and the New York Times’s list would be differentiated by who was on each coverage team and the editorial approach of each news organization. The list would exist for the duration of the story.

Rather than serving as part of a taxonomy, or classification of Twitter users— the list would define individuals with a common purpose— covering the Haiti earthquake, or the Senate race in Massachusetts. Each news organization might have a set of active lists ongoing at any time. The more specific and real time the list, the more valuable it would be.

Of course, someone might create a list of all the news organizations covering a breaking story. But I think the effect of this would be to dilute the value of the stream rather than enhance it. You could also make the argument that the hashtag and the wisdom of the crowd would ultimately provide equal or better coverage. However, it’s not necessary to choose between one approach and the other. Each will ultimately include elements of the other.

The television medium is destabilizing and being absorbed into the real-time Network. While newspapers and television used to consider the Internet as a medium for the re-purposing and re-use of content, soon the reverse will be true. The real-time Network will be the primary publication vehicle with television and newspapers becoming containers for re-use.

And, of course, I use the word Twitter as a synecdoche. (A specific class name used to refer to a general set of associated things)