echovar

I thought it prudent to write something about Jeffrey Rosen’s Sunday NY Times essay, The Web Means The End Of Forgetting, before it slipped into the past and we’d all forgotten about it. Scott Rosenberg was disappointed in Rosen’s essay and wrote about how it didn’t live up to the large themes it outlined. The essence of Rosen’s piece is that the public information we publish to the web through social network systems like Facebook are permanent markers that may come back to haunt us in unanticipated contexts. Rosenberg’s critique seems to be that there’s not too much evidence of this happening, and that a greater concern is link rot, preservation of the ephemera of the web and general digital preservation.

Of course, there’s a sense in which we seem to have very poor memories indeed. Our universities feature a discipline called archeology in which we dig up our ancestors with the purpose of trying to figure who they were, what they did and how they lived. We lack the ability to simply rewind and replay the ancient past. As each day advances, another slips into time out of mind— or time immemorial as it’s sometimes called.

We use the metaphors memory and forgetting when talking about what computer systems do when they store and retrieve bits from a file system. The human activity of memory and forgetting actually has very little in common with a computer’s storage and retrieval routines. When we say that the Web doesn’t forget, what we mean is that if something is stored in a database, unless there’s a technical problem, it can be retrieved through some kind of search query. If the general public has access to that data store, then information you’ve published will be available to any interested party. It’s not a matter of human remembering or forgetting, but rather one of discovery and random access through querying a system’s indexed data.

At issue in Rosen’s piece, isn’t the fact of personal data retrieved through a search query, but rather the exposure of personal transgressions. Lines that were crossed in the past, behavior from one context made inappropriate by placing it into a new context, some departure from the Puritan norm detected and added into a summary valuation of a person. Rosen even describes this mark as a “scarlet letter in your digital past.” The technical solutions he explores have to do with changing the data or the context of the data to prevent retrieval: the stains of data are scrubbed and removed from relevant databases; additional data is piled in to divert attention from the offending bits; or an expiration policy is enforced on bits that make them unreadable after a set period of time. There’s an idea that at some future point you will own all your personal data (that you’ve published into publicly networked systems) and will have granular access controls over it.

Absent a future of totalitarian personal data control, Rosen moves on to the act of forgiveness. Can we forgive each other in the presence of permanent reminders? I wrote a post about this on the day that MSNBC replayed the events of morning of September 11, 2001. Sometimes we can rewind the past and press play, but wounds cannot heal if we’re constantly picking at them.

While we’re enraptured by the metaphors of memory and forgetting, intelligence and thinking, as we talk about computers, when we speak of forgiveness we tamp down the overtones and resonance of the metaphor. It’s in the cultural practice of western religion that we have the mechanisms for redemption, forgiveness, indulgences and absolution. In the secular rational context of computerized networks of data there’s no basis for forgiveness. It’s all ones or zeros, it’s in the database or it’s not.

Perhaps in our digital secular world we need a system similar to carbon offsets. When we’ve sinned against the environment by virtue of the size of our carbon footprint, we purchase indulgences from TerraPass to offset our trespass. Rather than delete, obscure or divert attention from the bits in question, we might simply offset them with some act of kindness. While the Catholic Church frowns on the idea of online confession, in this model, there would be no person listening to your confession and assigning penance. The service would simply authenticate your good deeds and make sure they were visible as a permanent marker on the Network. It would be up to you to determine the size of the offset, or perhaps you could select from a set of standard offset sizes.

The problem that Rosen describes is not one of technology, but rather one of humanity and human judgment. The question of how we treat each other is fundamental and has been with us since the beginning.

A film is described as cinematic when the story is told primarily through the visuals. The dialogue only fills in where it needs to, where the visuals can’t convey the message. It was watching Jean-Pierre Melville’s Le Samourai that brought these thoughts into the foreground. Much of the film unfolds in silence. All of the important narrative information is disclosed outside of the dialogue.

While there’s some controversy about what percentage of human-to-human communication is non-verbal, there is general agreement that it’s more than half. The numbers are as low as 60% and as high as 93%. What happens to our non-verbal communication when a human-to-human communication is routed through a medium? A written communique, a telephone call, the internet: each of these media have a different capacity to carry the non-verbal from one end to the other.

The study of human-computer interaction examines the relationship between humans and systems. More and more, our human-computer interaction is an example of computer-mediated communications between humans; or human-computer network-human interaction. When we design human-computer interactions we try to specify everything to the nth degree. We want the interaction to be clear and simple. The user should understand what’s happening and what’s not happening. The interaction is a contract purged of ambiguity and overtones. A change in the contract is generally disconcerting to users because it introduces ambiguity into the interaction. It’s not the same anymore; it’s different now.

In human-computer network-human interactions, it’s not the clarity that matters, it’s the fullness. If we chart the direction of network technologies, we can see a rapid movement toward capturing and transmitting the non-verbal. Real-time provides the context to transmit tone of voice, facial expression, hand gestures and body language. Even the most common forms of text on the Network are forms of speech— the letters describe sounds rather than words.

While the non-verbal can be as easily misinterpreted as the verbal, the more pieces of the picture that are transmitted, the more likely the communication will be understood. But not in the narrow sense of a contract, or machine understanding. But rather in the full sense of human understanding. While some think the deeper levels of human thought can only be accessed through long strings of text assembled into the form of a codex, humans will always gravitate toward communications media that broadcast on all channels.

As we consider machines that may think, we turn toward our own desires. We’d like a machine that understands what we mean, even what we intend, rather than what we strictly say. We don’t want to have to spell everything out. We’d like the machine to take a vague suggestion, figure out how to carry on, and then return to us with the best set of options to choose from. Or even better, the machine should carry out our orders and not bother us with little ambiguities or inconsistencies along the way. It should work all those things out by itself.

We might look to Shakespeare and The Tempest for a model of this type of relationship. Prospero commands the spirit Ariel to fulfill his wishes; and the sprite cheerfully complies:

ARIEL
Before you can say ‘come’ and ‘go,’
And breathe twice and cry ‘so, so,’
Each one, tripping on his toe,
Will be here with mop and mow.
Do you love me, master? no?

But The Tempest also supplies us with a counter-example in the character Caliban, who curses his servitude and his very existence:

CALIBAN
You taught me language; and my profit on’t
Is, I know how to curse. The red plague rid you
For learning me your language!

Harold Bloom, in his essay on The Tempest in Shakespeare: Invention of the Human, connects the character of Prospero with Christopher Marlowe’s Dr. Faustus. Faustus also had a spirit who would do his bidding, but the cost to the good doctor, was significant.

For the most part we no longer look to the spirit world for entities to do our bidding. We now place our hopes for a perfect servant in the realm of the machine. Of course, machines already do a lot for us. But frankly, for a long time now, we’ve thought that they could be a little more intelligent. Artificial intelligence, machines that think, the global brain: we’re clearly under the impression that our lot could be improved by such an advancement in technology. Here we aren’t merely thinking of an augmentation of human capability in the mode of Doug Engelbart, but rather something that stands on its own two feet.

In 2002, David Gelernter wrote a book called The Muse in the Machine: Computerizing the Poetry of Human Thought. Gelernter explored the spectrum of human thought from tightly-focused task-driven thought to poetic and dream thoughts. He makes the case that we need both modes, the whole spectrum, to think like a human does. Recently, Gelernter updated his theme in an essay for Edge.org called Dream-Logic, The Internet and Artificial Thought. He returns to the theme that most of the advocates for artificial intelligence have a defective understanding of what makes up human thought:

Many people believe that the thinker and the thought are separate.  For many people, “thinking” means (in effect) viewing a stream of thoughts as if it were a PowerPoint presentation: the thinker watches the stream of his thoughts.  This idea is important to artificial intelligence and the computationalist view of the mind.  If the thinker and his thought-stream are separate, we can replace the human thinker by a computer thinker without stopping the show. The man tiptoes out of the theater. The computer slips into the empty seat.  The PowerPoint presentation continues.

But when a person is dreaming, hallucinating — when he is inside a mind-made fantasy landscape — the thinker and his thought-stream
are not separate.  They are blended together. The thinker inhabits his thoughts.  No computer will be able to think like a man unless it, too, can inhabit its thoughts; can disappear into its own mind.

Gelernter makes the case that thinking must include the whole spectrum of the thought. He extends this idea of the thinker inhabiting his thoughts by saying that when we make memories, we create alternate realities:

Each remembered experience is, potentially, an alternate reality. Remembering such experiences in the ordinary sense — remembering “the beach last summer” — means, in effect, to inspect the memory from outside.   But there is another kind of remembering too: sometimes remembering “the beach last summer” means re-entering the experience, re-experiencing the beach last summer: seeing the water, hearing the waves, feeling the sunlight and sand; making real the potential reality trapped in the memory.

(An analogy: we store potential energy in an object by moving it upwards against gravity.  We store potential reality in our minds by creating a memory.)

Just as thinking works differently at the top and bottom of the cognitive spectrum, remembering works differently too.  At the high-focus end, remembering means ordinary remembering; “recalling” the beach.  At the low-focus end, remembering means re-experiencing the beach.  (We can re-experience a memory on purpose, in a limited way: you can imagine the look and fragrance of a red rose.  But when focus is low, you have no choice.  When you remember something, you must re-experience it.)

On the other side of the ledger, you have the arguments for a technological singularity via recursive self-improvement. One day, a machine is created that is more adept at creating machines than we are. And more importantly, it’s a machine who’s children will exceed the capabilities of the parent. Press fast forward and there’s an exponential growth in machine capability that eventually far outstrips a human’s ability to evolve.

In 2007, Gelernter and Kurzweil debated the point:

When Gelernter brings up the issue of emotions, poetic thought and the re-experiencing of memory as fundamental constituents of human thought, I can’t help but think of the body of the machine. Experience needs a location, a there for its being. Artificial intelligence needs an artificial body. To advance even a step in the direction of artificial intelligence, you have to endorse the mind/body split and think of these elements as replaceable, extensible, and to some extent, arbitrary components. This move begs a number of questions. Would a single artificial intelligence be created or would many versions emerge? Would natural selection cull the herd? Would an artificial intelligence be contained by the body of the machine in which it existed? Would each machine body contain a unique artificial intelligence with memories and emotions that were solely its own? The robot and the android are the machines we think of as having bodies. In Forbidden Planet, the science fiction update of Shakespeare’s The Tempest, we see the sprite Ariel replaced with Robby the Robot.

In Stanley Kubrick’s film 2001: A Space Odyssey, the HAL 9000 was an artificial intelligence who’s body was an entire space ship. HAL was programmed to put the mission above all else, which violated Asimov’s three laws of robotics. HAL is a classic example of an artificial intelligence that we believe has gone a step too far. A machine who has crossed a line.

When we desire to create machines that think; we want to create humans who are not fully human. Thoughts that don’t entirely think. Intelligence that isn’t fully intelligent. We want to use certain words to describe our desires, but the words express so much more than we intend. We need to hold some meaning back, the spark that makes humans, thought and intelligence what they are.

Philosophy is a battle against the bewitchment of our intelligence by means of language.
- Ludwig Wittgenstein

Clearly some filters, algorithms and agents will be better than others, but none of them will think, none will have intelligence. If part of thinking is the ability to make new analogies, then we need to think about what we do when we create and use these software machines. It becomes an easier task when we start our thinking with augmentation rather than a separate individual intelligence.

Google and Twitter have filed a amicus brief with the appeals court on TheFlyOnTheWall.com case. Briefly, at issue is FlyOnTheWall’s near real-time redistribution of investment bank research ratings. Investment bank research departments spend time, money and resources creating stock ratings and price targets. The purpose of this effort is to create an information asymmetry in the market to the advantage of the i-bank’s clients. FlyOnTheWall does not employ analysts and has no research capability, it discovers stock ratings, aggregates and redistributes them in near real time. Since their cost of production only includes real-time redistribution infrastructure, and therefore they can offer their high-value information feeds at a lower cost than investment banks. Subscribers to FlyOnTheWall pay for these aggregated news feeds, they aren’t free. In their testimony, FlyOnTheWall claimed they only gathered information from publicly available sources and only published tweet-sized snippets summarizing the reports.

Google and Twitter make the following argument in their brief:

News reporting always has been a complex ecosystem, where what is ‘news’ is often driven by certain influential news organizations, with others republishing or broadcasting those facts — all to the benefit of the public,

and further

How, for example, would a court pick a time period during which facts about the recent Times Square bombing attempt would be non-reportable by others?”

At issue is the re-emergence of the hot news doctrine, which was originally put in place in 1918 to stop William Randolf Hearst’s International News Service from taking Associated Press wire news stories and redistributing them as their own. The court set forth five criteria to determine whether ‘hot news’ has been misappropriated:

(i) a plaintiff generates or gathers information at a cost;

(ii) the information is time-sensitive;

(iii) a defendant’s use of the information constitutes free riding on the plaintiff’s efforts;

(iv) the defendant is in direct competition with a product or service offered by the plaintiffs;

(v) the ability of other parties to free-ride on the efforts of the plaintiff or others would so reduce the incentive to produce the product or service that its existence or quality would be substantially threatened.

In the case of TheFlyOnTheWall.com the court ruled for the plaintiffs, Barclays, Merrill Lynch and Morgan Stanley, and decided that a 2 hour embargo was a reasonable amount of latency to build into the Network. In the fast-paced world of equity trading, two hours is an eternity. These days trades are often executed in a matter of milliseconds. The enforcement of this kind of rule, however, is problematic. In the brave new world of social media, both individuals and news organizations have interconnected real-time distribution networks. Once bits of information touch this public social network they can spread with breathtaking speed. Twitter, Google and Facebook are currently the media through which this information is dispersed. And each of them can be said to profit by the circulation of high-value information through their networks.

Over the last few days we’ve seen the drama of General Stanley A. McChrystal play out. The events were put into play by a story written by Michael Hastings, a freelancer for Rolling Stone Magazine. The story about McChrystal’s comments began leaking out Monday night. Both Politico and Time magazine posted a PDF of the Rolling Stone article to their web sites before Rolling Stone. Rolling Stone asked the sites to remove the PDF. The New York Times reports:

Will Dana, the magazine’s managing editor, said that the magazine did not always post articles online because it could make more money at the newsstand and that when it did, the articles were typically not posted until Wednesday. But other news organizations made that decision for him.

The McChrystal story is an interesting example of the ‘hot news’ doctrine. Rolling Stone magazine puts out 26 issues of its print magazine per year. Even before the issue hit the newsstands, it dominated cable news, has been fully reported in the New York Times and resulted in McChrystal’s resignation and replacement by General David Petraeus. One could argue that Rolling Stone should have a business model that allows them to benefit from these kind of real-time events. And it’s quite possible that the broad dissemination of this story will lead to a significant increase in newsstand sales and web site traffic.

In this case the ‘hot news’ was so hot that the story itself became a story. Major government policies regarding the conduct of the war in Afghanistan had to be decided in real time. There was no hesitation, no waiting for Rolling Stone’s newsstand business model to play out. By the time we finally see the printed magazine it will have become an artifact of history. With the advantage of hindsight, we may even wonder why the headline writer put McChrystal’s story third after Lady Gaga’s tell all and the final days of Dennis Hopper.

The question about the ‘hot news’ doctrine isn’t going away; and the decision of the appeals court will be closely watched. In the meanwhile, the marketplace is searching for a solution to the fact of real-time aggregation and relay of digitally-copied work product. The return of the pay wall is an attempt by producers of stories about the news to create a firewall around their work product. Most corporations employ a firewall to keep their valuable internal discussion from reaching the public networks. Limiting access of your product to paying customers isn’t a new idea. However, when your work product is a story about news events or ideas encoded in digital media, creating reliable access controls is problematic. Where in the early days of the Network the focus was on direct access and disintermediation of the middle man; now the economics favor the man-in-the-middle. Meta-data can be sold at a fraction of the price of the data to which it points. The complex ecosystem of ‘the news’ is looking for a new equilibrium in which both data and meta-data can flourish.

June 16th is known as Bloomsday; it’s the single day, in 1904, on which James Joyce’s novel Ulysses occurs. The day is commemorated around with the world with readings of the book and the hoisting of a pint or two.

Stately, plump Buck Mulligan came from the stairhead, bearing a bowl of lather on which a mirror and a razor lay crossed. A yellow dressinggown, ungirdled, was sustained gently behind him by the mild morning air. He held the bowl aloft and intoned:

— Introibo ad altare Dei.

Halted, he peered down the dark winding stairs and called up coarsely:

— Come up Kinch. Come up , you fearful jesuit.

Solemnly he came forward and mounted the round gunrest. He faced about and blessed gravely thrice the tower, the surrounding country and the awakening mountains. Then, catching sight of Stephen Dedalus, he bent towards him and made rapid crosses in the air, gurgling in his throat and shaking his head. Stephen Dedalus, displeased and sleepy, leaned his arms on the top of the staircase and looked coldly at the shaking, gurgling face that blessed him, equine in its length, and at the light untonsured hair, grained and hued like pale oak.

Buck Mulligan peeped an instant under the mirror and then covered the bowl smartly.

Joyce’s book brought to popular notice the idea of stream of consciousness literature. The term “stream of consciousness” was coined by the philosopher William James in an attempt to describe the mind-world connection as it relates the concept of truth. As a literary technique, it involves writing as a kind of transcription of the inner thought process of a character. In Ulysses, we find that stream rife with puns, allusions and parodies. Joyce was trying to capture another aspect of truth.

What challenged the reader of the day as avant garde and daring has become a relatively normal part of our network-connected lives.

Twitter has become a part of my daystream
- Roger Ebert

The stream of tweets flowing out of Twitter could aptly be described as a stream of collective consciousness. And so today, we think a great deal about various real-time streams and how they wend their way through networks of social connection. The water metaphors we use to speak about these things have roots in our shared history; they describe another kind of network of connections.

Stephen B. Johnson, in his book The Invention of Air, makes the case for the London Coffee House as an early prototype for the internet:

With the university system languishing amid archaic traditions, and corporate R&D labs still on the distant horizon, the public space of the coffeehouse served as the central hub of innovation in British society. How much of the Enlightenment do we owe to coffee? Most of the epic developments in England between 1650 and 1800 that still warrant a mention in the history textbooks have a coffeehouse lurking at some crucial juncture in their story. The restoration of Charles II, Newton’s theory of gravity, the South Sea Bubble— they all came about, in part, because England had developed a taste for coffee, and a fondness for the kind of informal networking and shoptalk that the coffeehouses enabled. Lloyd’s of London was once just Edward Lloyd’s coffeehouse, until the shipowners and merchants started clustering there, and collectively invented the modern insurance company. …coffeehouse culture was cross-disciplinary by nature, the conversations freely roaming from electricity, to the abuses of Parliament, to the fate of dissenting churches.

But the coffeehouse as a nexus of debate was only half of the picture. Cultural practice at the time was to drink beer and wine, and maybe a little gin, at every opportunity. Water was not safe to drink, and so alcoholic alternatives were fondly embraced. The introduction of coffee and tea as popular beverages had a significant impact on the flow of valuable ideas. Again here’s Johnson:

The rise of coffeehouse culture influenced more than just the information networks of the Enlightenment; it also transformed the neurochemical networks in the brains of all those newfound coffee-drinkers. Coffee is a stimulant that has been clinically proven to improve cognitive function— particularly for memory related tasks— during the first cup or two. Increase the amount of “smart” drugs flowing through individual brains, and the collective intelligence of the culture will become smarter, if enough people get hooked.

In our day, the coffee house connected to a wifi network has been an accelerant to the businesses populating the Network. When Starbucks announced that they would be introducing free 1-click wifi in their stores, it reminded me of Stephen Johnson’s descriptions of the London coffeehouses. The coffeehouse provided a physical meeting place and the caffeine in the coffee provided a force multiplier for the ideas flowing through the people. There was a noticeable change in the rhythm of the age. By layering a virtual real-time social medium over a physical meeting place that serves legal stimulants, Starbucks replays a classic formula. Oddly, there’s a kind of collaborative energy that exists in the coffeehouse that has been completely expunged from the corporate workplace. Starbucks ups the ante by running a broadcast web service network through the connection. Here we see wifi emerging as the new backbone for narrowcasted television.

As we try to weave value-laden real-time message streams through the collaborative groupware surgically attached to the corporate balance sheet, we may do well to look back toward Bloomsday and also ask for a stream of unconsciousness. It’s in those empty moments between the times when we focus our attention that daydreams and poetic thought creep into the mix. Those “empty moments” are under attack as a kind of system latency. However it’s in those day dreams, poetic thoughts and napkin scribbles that we find the source of the non-linear jump. Without those moments in our waking life, we’re limited to only those things deemed “possible.”

A few thoughts about the iPhone 4 and why technology does or doesn’t catch on. I’ve yet to hold one in my hand, but like everyone else I’ve got opinions. The typical gadget review takes the device’s feature list and compares using technical measures to other devices deemed competitive. Using this methodology, it would be fairly simple to dismiss the iPhone as introducing no new features. The other lines of attack involve dropped calls on the AT&T network and the App Store approval process. For some people these two items trump any feature or user experience.

Google talks about their mission as organizing the world’s information. When I think of Apple’s mission, at least their mission for the last five years or so, it revolves around getting closer to the user in real time. The technology they build flows from that principle.

I’d like to focus on just two new iPhone 4 features. The first is the new display, here’s John Gruber’s description:

It’s mentioned briefly in Apple’s promotional video about the design of the iPhone 4, but they’re using a new production process that effectively fuses the LCD and touchscreen — there is no longer any air between the two. One result of this is that the iPhone 4 should be impervious to this dust-under-the-glass issue. More importantly, though, is that it looks better. The effect is that the pixels appear to be painted on the surface of the phone; instead of looking at pixels under glass, it’s like looking at pixels on glass. Combined with the incredibly high pixel density, the overall effect is like “live print”.

The phrase that jumped out at me was “the pixels appear to be painted on the surface of the phone; instead of looking at pixels under glass.” While it seems like a small distance, a minor detail, it’s of the utmost importance. It’s the difference between touching something and touching the glass that stands in front of something. Putting the user physically in touch with the interaction surface is a major breakthrough in the emotional value of the user experience. Of course the engineering that made this kind of display is important, but it’s the design decision to get the device ever closer to the user that drove the creation of the technology. Touch creates an emotional relationship with the device, and that makes it more than just a telephone.

In a 2007 interview at the D5 conference, Steve Jobs said:

And, you know, I think of most things in life as either a Bob Dylan or a Beatles song, but there’s that one line in that one Beatles song, “you and I have memories longer than the road that stretches out ahead.

You could say that Apple’s strategy is encapsulated in the Beatles song: I Want To Hold Your Hand.

The lines that describe the feeling Jobs wants the iPhone and iPad to create are:

And when I touch you i feel happy, inside
It´s such a feeling
That my love
I can’t hide
I can’t hide
I can’t hide

The other new feature is FaceTime. Since the launch of the iPhone 3GS it’s been possible to shoot a video of something and then email it to someone, or post it to a network location that friends and family could access. Other phones had this same capability. That’s a real nice feature in an asynchronous sort of way. One of the problems with it is it has too many steps and it doesn’t work the way telephones work. Except when things are highly dysfunctional, we don’t send each other recorded audio messages to be retrieved later at a convenient time. We want to talk in real time. FaceTime allows talk + visuals in real time.

FaceTime uses phone numbers as the identity layer and works over WiFi with iPhone 4 devices only. That makes it perfectly clear under what circumstances these kind of video calls will work. Device model and kind of connectivity are only things a user needs to know. These constraints sound very limiting, but they dispel any ambiguity around the question of whether the user will be able to get video calls to work or not.

We often look to the network effect to explain the success of a product or a new platform. Has the product reached critical mass, where by virtue of its size and connectedness it continues to expand because new users gain immediate value from its scale. The network must absolutely be in place, but as we look at this window into our new virtual world, the question is: does the product put us in touch, in high definition, in real time? The more FaceTime calls that are made, the more FaceTime calls will be made. But the system will provide full value at the point when a few family members can talk to each other. Critical mass occurs at two.

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?

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.