How We got To “Hyperlogic”: Lessons From Hacking the Human Mind Via Social BookMarking

[originally posted at Social Synergy weblog]

[bliki|what is a bliki?]

In a recent previous post, I gave a critique of Marc Fawzi’s “The Unwisdom of Crowds” post to his Evolving Trends blog.  Lots of discussion and healthy debate ensued with Marc both here and via email. I still stand by my criticisms, but I think that they tell only part of the story of the blogging adventures of Marc Fawzi. So in this post, instead of just criticizing Marc, I am going to try to outline what I see as being valuable in different ideas that Marc is conveying on his blog.

From what I can tell, Marc has planned and performed an important experiment. Examining his experiment and it’s results can help inform us about the nature of the EcosystemOfNetworks, and how people create and use different peer production social software systems, and the nature of the blogosphere in general. And, it can help inform teaching, learning and communicating online.
Marc’s experiment began with his post back in Jun 24 2006, titled From Mediocre to Visionary. In that post, Marc wrote:

“There are many examples of “Web 2.0” celebrities (both companies and individuals) who are currently surfing some big waves (pretty much on their behind as I did in Puerto Rico) without any insight on how to properly surf the hype wave they’re riding, yet they seem to be magically levitating above it on a carpet of thin air (again, like I did in Puerto Rico.) When they finally land, and land they will, we’ll all rush to the scene of their landing and yell “loco! loco!”

But for those of us who cannot delegate our success to a statistically odd event (as in being at the right place, the right time and being carried miraculously by a massive wave of hype simply due to curiosity and good luck) we must strive to understand how to find the big hype waves across time and hype space and how to properly surf them.”

Basically, in quote above, Marc is talking about how he discovered in one way or another, that the power law of the network we call the “blogosphere”, described by Clay Shirkey, by nature tends to amplify certain messages, even if only for a short time.

Shirkey’s now widely familiar “Power Laws, weblogs, and Inequality” article describes how there is a “Predictable Imbalance” in the readership of blogs. A small set of webloggers account for a majority of the traffic in the weblog world. His article contains graphs that show this Power law phenomenon. (Of course, Chris Anderson has now popularized this, and connected it to many other phenomenon in his great book, The Long Tail). Shirkey’s article also suggests that the network system we call the “blogosphere” will tend to stay this way, to stay in a state of “homeostasis”, that the few popular people will tend to stay popular. He also states that “freedom of choice makes stars inevitable”. So, in an open system where no one is forced to link to or read anyone else, Shirkey is saying it is inevitable that a few people will come to gain the majority of links to their sites, and readers.

Now, what I have noticed myself in my few years of blogging experience is that bloggers at all levels of the power law distribution have utilized different channels to both find and promote content.

Even prior to the widespread rise of blogging, community channels like Usenet and later Slashdot existed. Slashdot, of course, has a group of editors who submit news stories. The news stories are usually just a short blurb about a link to an article on a site somewhere else. The Slashdot community then will comment and discuss and debate the article. They also rate each others comments. Slashdot became so popular that people coined the term “The Slashdot Effect” to describe a phenomenon where “a popular website link[s] to a smaller site, causing the smaller site to slow down or even temporarily close due to the increased traffic.” Slashdot also allows users to submit ideas for stories. But what actually goes on the site is controlled by a few people.

When Social Bookmarking first emerged, many sites emulated the del.icio.us model, which is basically to take browser based personal knowledge bases and put them into one shared site,and allow users to share them in different ways. This is has turned out to be a very effective way for people to share knowledge in a quick and decentralized way. In del.icio.us in particular, users can look at what is popular, but the emphasis in del.icio.us is more on the individual first, and giving the individual useful tools to contextualize knowledge and information in ways that are meaningful to the individual.

In contrast, one social bookmarking site, called digg, tends to focus more on the popularity of a link. digg doesn’t let you tag what you post with whatever it means to you. Instead, it has a predefined set of topics. digg is actually similar to Slashdot in many ways, except that digg allows anyone to submit a link to something online. Then, digg lets everyone in the digg community vote on the the items submitted. digg also lets you comment on items submitted, and lets you rate other’s comments similar to Slashdot. Blog content from both popular and obscure bloggers makes it’s way onto digg regularly.

So, what does this all have to do with Marc Fawzi’s blogging experiment? Well, Marc guessed that if he looked at what was being talked about in the blog community, and on digg, he could use the mechanisms of digg and the uneven distribution of attention and linking in the networks of blogs to at least temporarily move “up” the power curve in a very fast manner.

So, Marc set out to create a controversial message that tied together two already controversial subjects, and suggested that they would battle each other. His message was Wikipedia 3.0: The End of Google?. Marc guessed that this message would grab the attention of people because it used the trick of presupposing that there is only one side or the other to take on the issue. Polarizing the debate from the start. Wikipedia 3.0 argument was for a controversial subject called the “semantic web“. Marc then submitted a link for this to digg. The trick of polarizing the debate worked, and his submission received many diggs. Both popular and obscure bloggers pay attention to digg, and use it as a source for fresh content, and possibly also as a “barometer” of what their audiences are interested in. So, Marc’s post began to spread quite fast through the networks of popular-to-obscure blogs.

A few days later, Marc posted an autopsy of his experiment, titled “For Great Justice, Take Off Every Digg“. He also reported that he had received 55,000 hits to his site in just a few days. In “For Great Justice…”, Marc writes:

“Since digg is an open system where anyone can submit anything, user behavior has to be carefully monitored to make sure that people do not abuse the system. But given that the number of stories submitted each second is much larger than what Digg’s own staff can monitor, digg has given the power to the users to decide what is good content and what is bad (e.g. spam, miscategorized content, lame stuff, etc.)”

Marc had exposed that at least one possible way to “game” the system by appealing to our human nature. The human mind likes to take complex reality and split it into dichotomies, to make it “black and white”. Broadcast media and political propaganda have taken advantage of this aspect of human nature for years. We are largely entertained and informed by these dichotomies. Charles Cameron actually created a tool to map diagrammatically these dichotomies (see: HipBone Analytics). He calls them “symmetries”. Charles writes:

The central analytic approach used here is the recognition of      symmetries – homologies, parallelisms, and oppositions between      positions. This has long been the natural, almost instinctive way in      which humans have evaluated “fairness”

So, Marc tapped into this instinctive nature in people. But he also showed that systems designed the way that digg is designed, if left wide open, can amplify it. He also showed that a system that is focused on popularity above meaning, like digg, will amplify human nature to be impulsive. Today’s digg superstar is often tomorrows digg dustbin relic. digg as collective system moves on to the next trend at rapid pace.

Marc’s experiment was actually also apparently designed in part to be an argument for semantic web principles. Marc’s idea is that Artificial Intelligence could enhance Semantic web approaches. Whether or not it turns out that his specific mechanics end up working, I agree with him that if we are contextualizing knowledge and information first in personal knowledge bases, then sharing these online, eventually we will be able to attach so many individual meanings and so many dimensions and facets to so many things, that we we’ll need AI assistance just to keep up with all of the variables, and to make things findable in any useful way. When we take into account that we will also be able to extend this meaning and searchability to virtually “everyware”, these ideas start to make more and more sense. Of course, we should also consider the possible problems that could emerge from creating a Socio-cybernetic society.

In debating with Marc via email, I was initially very much against the idea of forcing a “split” or polarization, as he did, to grab people’s attention. However, I also can see that it can be useful to help people understand the larger picture who already thinking in a polarized way, provided that you actually give that larger picture, and don’t just reinforce the polarizations.

Also, I wanted to mention that although I had criticized Marc’s metaphor of “tribalism”, which he used to describe the behavior of people using digg, I discussed with Marc that I didn’t think the he was off base overall. I wrote to Marc:

“…Now, McLuhan actually agrees with you, for the most part. He ALSO used the metaphor of a new tribalism do describe what he thought the new connected future might look like. Here is what McLuhan said in 1961:

“The electronically induced technological extensions of our central nervous systems, which I spoke of earlier, are immersing us in a world-pool of information movement and are thus enabling man to incorporate within himself the whole of mankind. The aloof and dissociated role of the literate man of the Western world is succumbing to the new, intense depth participation engendered by the electronic media and bringing us back in touch with ourselves as well as with one another. But the instant nature of electric-information movement is decentralizing–rather than enlarging–the family of man into a new state of multitudinous tribal existences. Particularly in countries where literate values are deeply institutionalized, this is a highly traumatic process, since the clash of the old segmented visual culture and the new integral electronic culture creates a crisis of identity, a vacuum of the self, which generates tremendous violence–violence that is simply an identity quest, private or corporate, social or commercial.”

So, McLuhan also used the metaphor of “tribal” to describe what he saw emerging in our time. He was really accurate on his prediction of the direction of technology. But he saw new types of tribes. his tribes were “electronic culture” tribes. McLuhan knew, even before there was anything like the internet, that the direction of technology as an “extension of man” was going towards what he called a “global village”. What he meant by a global village was that people in our time were going to become highly connected to the point that distance between us would eventually be largely erased. We are now headed towards that direction. So, McLuhan guessed that people connected in this global village would start to “retribalize” into new groups.

But these new types of “tribes” will not be like the tribes of pre-history.

They will instead be “Global-local” tribes. Some of them will organize around a place, or around concepts or ideas or technology. Some people will be part of many of these groups. One example of a scenario like what I am talking about can be found at OrganizedCulture which is a page in the wiki community that I participate in.”

I do agree with Marc that the web gives us more space and more connections and ways to organize around different specialized interests. And he is right that these sometimes become sub cultures and they sometimes do insulate themselves or filter their information through “trusted sources”.

Hopefully, this post helped me “walk the talk” of trying to “show the larger picture”. Because, I actually employed Marc’s “splitting” polarizing tactic in my first post that was all negative criticism. So, this positive “support” is an attempt by me to display an example of how to go about doing what I am talking about (which Marc calls “Hyperlogic”).

So, thanks Marc. If your were trying to get people to think, it worked on me 🙂

1 Comment How We got To “Hyperlogic”: Lessons From Hacking the Human Mind Via Social BookMarking

  1. AvatarMarc

    LOL

    I like it.

    It’s funny but also informative.

    The problem with using the ‘split-and-recombine’ technique is that people are mobilized from their idle position to cross the divide between black and white and there’s a ‘wearing out’ effect on people as they take these polarized positions and then have to come back to the middle. The ‘wearing out’ effect means that you can do it only so many times before you lose your audience. But isn’t there an infinite supply of people to listen to polarized messages?

    Basically, I believe there is a way to achieve the same effect (i.e. generate a hype wave) without having to do what I did.

    It’s like the difference between Flash Memory and MRAM. In Flash electrons move from ne place to another and this wears out the junction (or whatever structure) so you can only store things on a Flash card 100,000 times. We’re talking elementary particles here, not human beings. With humans beings I can’t think of anyone who can take this wearing out effect more than 20, 50 times before they drop out.

    MRAM will eventually replace all RAM (when they can scale densities and production) and which will mean that your computer can be turned off (to save POWER/save us from oild dependence etc) and when you turn it on again everything, all your programs, will be just the way you left them. MRAM doesn’t wear out because the electrons don’t cross the junction back and forth, which is what happens in Flash. Thus, MRAM is more useful than Flash.

    So I want to study the mechanism in MRAM ata high level and see if any wisdom can be extracted from its design.

    Re: AI

    By “AI” I meant simply “Inference Engines” which exist today and which already have been used with domain specific ontologies to reason about domain specific information.

    I did not mean Mr. Data or HAL.

    Also, with respect to the Global Brain, the definition there is again not HAL. It’s the complex behavior that emerges from the interaction of all P2P Semantic Web Inference Engines. The complex behavior is not al algorithm. It’s the result of massively parallel interactions between nodes (or Engines) with relatively simple behavior. It doesn’t imply intelligence will emerge. I did not clarify that in the Wikipedia article and that got some people carried away … 🙂 May be I didn’t clarify it intentionally but I tend to believe that I just didn’t realize that people would assume I was talking about an AI that emerges out of the complex behavior. I might have wanted the vaguness so that people start thinking (there is a lot to learn from the New Kind of Science book by Wolfram if people wanted to stretch their imagination but I definitely did not mean AI.. I mean complex behavior that can be thought of as a Global Brain in metaphorical way)

    Yet, Inference Engines are considered AI Engines (expert systems use inference engines) and that is the kind and level of AI I meant.

    Thank you for doing a well rounded analysis. I know how hard it is to wrap our minds around the big ideas, especially the “to split or not to split” debate ‘)

    Marc

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