Automatic Motion and the Gestures of Social Media
The Attention Economy is based on human behavior, behavior which includes the full range of physical gestures that we use to express our inner intentions. These gestures could be saying something, stretching our arms, walking past a group of people, or reading a book.
Many gestures end in themselves, as discrete actions. Other gestures trigger subsequent gestures: for the person who performs the gesture (such as throwing a ball into the air and then catching it on the way down) or for the one that receives the gesture (such as calling somebody on the phone who then picks up their phone). Since its introduction as mass consumer platform over ten years ago, the Internet has attracted an increasing amount of the latter: electronic gestures that use keyboards and mice (and increasing voice and video) to trigger subsequent gestures from others across the Internet. It is not simply that more human behavior is being expressed through the Internet; entirely new kinds of human behavior are being created by virtue of the medium. Many of these gestures are able to authenticate intentions with great subtlety so as to increase the ratio of signal to noise.
These are the gestures of social media, where influence is measured by the amount of Attention one gets relative to the amount of information one gives The most influential online individuals combine a high pagerank that lands them above the Google fold (ie their unique algorithm) and a rich personal stream of syndicatable "what makes me me"-ness: ie their natural API.
The Turing test measures whether a computational response is mistakable for an actual human being. George Dyson’s recent essay Turing’s Cathedral imagined this test to be central to Brin and Page’s agenda for Google. They are trying to build an artificial intelligence whose automatic responses to queries seem natural and humanistic. In order to experience the rich social media of a post-Web 2.0 landscape, however, we need to venture beyond the shadow of the Google page-rank Golem. How can we trust an electronic reality based solely on the single perspective of pagerank (ie the link model), when our actual behavior seems more like, in the words of William James, a “blooming, buzzing confusion” of human electronic gestures.
"Egosystems, not Ecosystems"
Stallman, Torvalds, Doc Searls, R0ml and many others have established the underlying value of an Open Source ecosystem. At the first public meeting of AttentionTrust.org in October 2005, Tim O’Reilly suggested that the next generation of the Web (3.0?) was going to be about "Data Inside". And so if you apply the discipline of a truly Open system to all of the behavioral data that is expressed by these electronic gestures, you end up with a new organizing framework- a framework of egosystems which, for the first time, bind human behavior to the transport policies of Open Source ecosystems. My wife Tina Sharkey came up with this brilliant expression, "egosystems, not ecosystems." in which the notion of an egosystem can be used to express the rich variety of our interactions across the Internet: email, search, browsing, buying, tagging, chatting, and other electronic activities. One egosystem may interact with other egosystems in infinitely different ways. And so even at maximum resolution, this social media fabric appears richly woven and densely textured: tiny threads of gestribution bundled transparently around eachother.
Enter the worms (which happen to be the subject of the last section of the last chapter on Arbitrage). These little creatures that both consume and produce in equal measures provide the best model for understanding the physics of the Attention Economy.
Hamlet explains that:
We fat all creatures else to fat us,
and we fat ourselves for maggots. Your fat king and your lean beggar is
but variable service- two dishes, but to one table.
So Hamlet 2.0 might say:
We encourage others to participate so that we may consume them
and we make ourselves interesting for the blogosphere. Your Internet CEO and your Joe Blogger are just different algorithms- two APIs, but to one network.
What distinguishes social media from other forms of media is this worm-like behavior, where production and consumption occur simultaneously. You can look at it as a form of therapy, where individual data is constantly being reorganized (quantitatively) to generate richer (qualititative) meaning. This is the Gillmor moment, when the naval-gazing gesture of an individual’s Attention feeds back, anonymously, into crystal-clear affinity pools of metadata. Inference and influence reverberate off of eachother, turning a mess of discrete gestures into a continuous Gesture stream.
Attention has forever been described as an absence in terms of distractions, deficits and obligations. Media Futures is a model for talking about Attention as something more; as an active substance that we create, express, share and remember. This Attention substance- let’s call them attentrons- operates at a size and frequency that makes it invisible to our naked eye. Fortunately, none of us need travel very far to reach the Attention super collider, where we can test for traces of these attentrons. The mashups that emerge on Digg are powerful reactions of data and people. From the new dance clubs in Second Life ripple new patterns of social networks. How can we analyze these seemingly spontaneous phenomena so as to make visible the elements and interactions that drive their behavior?
This is the project of Media Futures: to come up with a conceptual
schema that synthesizes the constructivist aspects of social media
and the analytical rigor of the Attention Economy. It is a
language game: as complex as Chess, and as fleeting as Chutes and
Ladders. Computer scientists in the 1950’s gave us the building blocks of Input, Store, View and Output; MS-DOS gave us operations like copy, file, print and run; Unix gave us root access. In the Attention OS, it’s the 5 A’s: Automata, Algorithm, API, Alchemy and Arbitrage.
Maggie Dillon has done a great job aggregating brief histories of each topic, both to establish its historical credibility and to expose the subtleties of its use over time. This syntax of Media Futures is valuable, however, only in so far as it is applied to real social media use cases. These new services require active minds, creative imaginations and lots of quality code. What’s missing is the sense of continuity between early computing history and the widget design for next week’s release. And that is what we are working on here. Enjoy.
Next: History of Automata