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Author: cgerrish

Unemployed philosopher

XMPP Tribes: Have You Ever Been Experienced?

Published July 23, 2008 by cgerrish

Jimi Hendrix and Buddy Miles

As we start to gather in tribes across the real-time web, dimensions of the value that is created begin to surface. How can the tribe help the individual where The Google can’t? I’m starting to read Richard Thaler and Cass Sunstein’s Nudge, a book about behavioral economics. In the introduction of the book, they discuss the idea of Choice Architecture. And it was immediately apparent that this concept needs to be included in Vendor Relationship Management. There are many aspects to choice architecture, but I’d like to focus on a common false assumption:

…that almost all people, almost all of the the time, make choices that are in their best interest or at the very least are better than the choices that would be made by someone else.

Imagine yourself buying a digital camera, selecting a health plan or planning a diet. How much experience do you have in each of these areas? Do you have what it takes to make the optimal decision?

In many areas, ordinary consumers are novices, interacting in a world inhabited by experienced professionals trying to sell them things. More generally, how well people choose is an empirical question, one whose answer is likey to vary across domains. It seems reasonable to say that people make good choices in contexts in which they have experience, good information and prompt feedback–say, choices among ice cream flavors.

How can I augment my experience in any specific transaction context? My XMPP Tribe can help me right now, in real time, through my iPhone. So why is asking the tribe better than reading user reviews? Because the more you read online reviews, the less you know. If there are a large volume of reviews, you can be certain that almost every possible viewpoint will be represented. My real-time tribe can even help me properly filter anonymous reviewers.

The normal sales transaction context involves a high degree of information asymmetry. VRM attempts to turn the signaling context around. Rather than the vendor signaling the customer, the customer signals the vendor– but this does nothing with regard to the uneven distribution of experience within the transaction. VRM can’t just be about signaling and paying for what you like. It’s also about creating a consideration set and making a choice that leads to a transaction. And if domain experience is lacking, the real-time tribe makes up the difference and augments the customer’s knowledge– an instant injection of experience.

Have you ever been experienced? Well I have…

If you can just get your mind together
Uh-then come on across to me
We’ll hold hands and then we’ll watch the sunrise
From the bottom of the sea
But first, are you experienced? 
Uh-have you ever been experienced-uh? 
Well, I have
(well) I know, I know, youll probably scream and cry
That your little world won’t let you go
But who in your measly little world, (-uh)
Are you tryin’ to prove to that you’re
Made out of gold and-uh, can’t be sold
So-uh, are you experienced? 
Have you ever been experienced? (-uh)
Well, I have
Uh, let me prove it to you, yeah
Trumpets and violins I can-uh, hear in the distance
I think they’re callin our name
Maybe now you can’t hear them,
But you will, ha-ha, if you just
Take hold of my hand
Ohhh, but are you experienced? 
Have you ever been experienced? 
Not necessarily stoned, but beautiful

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Twitter’s Stunted Growth: An Inference from Muybridge’s Photos

Published July 21, 2008 by cgerrish

Eadweard Muybridge Camel

Eadweard Muybridge presaged a kind of moving picture with his use of multiple cameras to capture motion. The zoopraxiscope, also invented by Muybridge, brought the images to life in a primitive way. You can think of the web version of Twitter as a bit like a series of Muybridge’s still photos on a page.

The zooproxiscope is comparable to Twitter’s polling method of simulating a live flow of real-time movement. It’s movement done with mirrors.

Twitter (as in Kleenex) with a real-time XMPP flow is a genuine moving picture. It’s hardly surprising that looking at a series of still pictures, the users of Twitter deduce real-time flow of messages and a method of tracking one-to-one and one-to-many conversations. 

By choking off independent developer access to the XMPP flavor of Twitter and attempting to place monetization at this point in the network, Twitter faces a turning point. The service grew like a weed when it embraced the rhizomatic ethic. Now Twitter hesitates, and seems to turn to a classic arborescent play. They turn from the economics of abundance to the economics of scarcity– and scarcity must be created and enforced by contract. By stunting their own growth, Twitter gives Plan B the opportunity to grow like wildfire.

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TwitterVision: Generative Infotainment

Published July 20, 2008 by cgerrish

Signal Path for Producing Discreet Music: Eno

I downloaded the TwitterVision app for the iPhone last week. But I didn’t really get a chance to look at it until I had an in-between moment last night while visiting a friend’s new house up on a hill in Fairfax. Left to my own devices for a few minutes, I pulled out my iPhone and touched the TwitterVision icon. Suddenly I was seeing a stream of Tweets from people I didn’t know from all over the world. Seeing those personal moments, many of them in-between moments, brought a smile to my lips– and, of course, started a train of thought.

This kind of engagement brought to mind what’s variously been called furniture music, discreet music or ambient music. This kind of music has many origins, I first became aware of it through the music of Erik Satie and Brian Eno. Eno first discussed the concept in the liner notes to his album Discreet Music.

In January this year I had an accident. I was not seriously hurt, but I was confined to bed in a stiff and static position. My friend Judy Nylon visited me and brought me a record of 18th century harp music. After she had gone, and with some considerable difficulty, I put on the record. Having laid down, I realized that the amplifier was set at an extremely low level, and that one channel of the stereo had failed completely. Since I hadn’t the energy to get up and improve matters, the record played on almost inaudibly. This presented what was for me a new way of hearing music – as part of the ambience of the environment just as the colour of the light and the sound of the rain were parts of that ambience. It is for this reason that I suggest listening to the piece at comparatively low levels, even to the extent that it frequently falls below the threshold of audibility.

In the liner notes to Music for Airports, the concepts had become more refined:

Ambient Music must be able to accomodate many levels of listening attention without enforcing one in particular; it must be as ignorable as it is interesting.

TwitterVision strikes me as this same kind of engagement. It accommodates many different levels of engagement. There’s a sense in which it’s always on, and always changing, much in the way that generative music can create music algorithmically that can have a duration of 1 year or 10,000 years. It’s a kind of engagement that works very well for our in-between moments, the moments where the system puts us in a holding pattern. We provide our own hold music.

The pertinent correlation is the input that Twitter provides and the way that it’s incorporated into the loop. This area of exploration was opened by Terry Riley and his Time Lag Accumulator and by Brian Eno’s Frippertronics, signal delay processor. The cowpaths and paved roads from experimental music seem to point to the future layers that will be built out on top of Twitter. Stay tuned.

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