As Darren explained in his weblog, “The toughest part about developing an SE is returning pages that the user actually wants which simply using keywords and link popularity won't provide”. Before looking at google more thoroughly, I really thought it was an advanced search engine, which brought relevant searches back to the user. However, Google, is extremely limited, because it works on link popularity and keywords, things that disallow it to query relevant searches for anything else other then generic keywords. It has no way of understanding phrases or exactly what the user is looking for, not to mention it only provides the most ‘popular’ sites, which are for the most part commercial. From our earlier experiments, you saw just how important link popularity really is. Continuing, the sad truth is that google is by far the most popular search engine according to cnet.com here Google has become so popular, that if your site is not listed in google, you are unlikely to get high amounts of traffic.

“So powerful has Google become that many companies view it as the Web itself: If you're not listed on its indexes, they say, you might as well not exist”
“"If you're not ranked in Google, Yahoo won't list you. It's incestuous."

Looking at this with our previous knowledge of the history of the WWW, and what the creator Tim Berners Lee envisioned, is this what he wanted? Is the web the once free, equal source of information that it was supposed to be? Could you go as far as saying that google is monopolizing traffic? Probably not, but the simple truth is that its damn near impossible for small companies and websites to compete within the current state of the Internet. One of the most appealing aspects of the WWW was the fact that there was no governing body, anything goes, and it was on an equal, fair ground for everyone to compete. As you can see from the above, this isn’t happening anymore, and the WWW is changing to support the bigger business, something we’ve all seen to much of in other complex systems.

OK. So our original idea was to look at googles relationship to complex systems, networks, etc and find out what makes them similar. With that, we were going to use ‘experiments’ or different methods to understand the hidden attributes behind googles formula, and to try and relate that back to complex systems. Apparently, according to our presentation this is all been done before, and we have once again been directed towards Barabasi and linked. So instead of researching these ideas by use of our own methods and interests, we know have to summarize Barabasi and think back to the future of [x], which in our case is GOOGLE. Hrmm, seems like the choose your own future of x has turned out to be ‘choose a subject’ and ill tell you what I want you to do. Whatever. Anyway, here is a little summary of the main points about google and Barabasi. He points out that an inherent property of networks and google for that matter is that they are not random, but rather they follow the rich get richer scheme and everybody connects to the more connected nodes. Linking that to social networks and how some societies try to limit the amount of wealth certain individuals aspire, google has no limitation and the bigger sites really do get more connected over time. Couple other interesting points, the human body itself is a complex network that has evolved for millions of years, the internet and more specifically the WWW have been around for only a short amount of time. Can the current state of the human body give us ideas about the future of google [x] ? Or can looking at the current state of modern complex networks help us further understand the future of the internet and google? Are these the right questions that need to be asked or are we going to get directed to another topic again?

Basically what we are trying to do is experiment and analyze the way in which Google's complex system works, and how these patterns correlate to other systems. By looking at google through the filters and ideas we learned in this course, we can see how it relates and how it works. Utilizing experiments, we plan to find out the relationship between Google and Natural, Digital and Social systems.

For a quick example, we are finding out that one of the main variables in the page-rank system is link popularity. How many sites link to you, and how popular are those sites are the general ideas behind link popularity. Looking at that through a social system perspective, we can see it relates well. The more connected you are in the real world, the more powerful you become. We've all seen real world examples of how somebody you know gets you that job, or gives you that push you need in the industry, right? Who's to say these models aren't similar in that sense, they are both, complex systems that have the same underlying structure. Translating back to google, the more connected you are in terms of links, the more powerful you are to the SE(search engine) thus, giving you higher link placement.

Using experiments as our tool, we plan to find out and analyze the relationships between google as an electronic system and social, natural, digital systems.

So here goes the pessimistic view on the course .......

Basically the reason I believe I've had a 'bad' experience in the sense that I didn't really enjoy updating the web log(as you can see;x) was
because the way in which I had to communicate didn't suit me. I'm not used to writing journals, or updating things daily, because that's
not the schedule in which my life works in. Anyway, regardless of that, I think the framework of the course was flawed for a couple of reasons.


1) Web logs are inherently personalized pieces of writing/works
This is opposed to specific scientific data/research, analysis and conclusions that the course material suggests. What happens is that
the postings become to personal, moving away from scientific conclusions or analysis, so in that sense, web logs aren't fit for
academic purposes. The point of weblogging within this context would be a collaborative network in which progressive learning is occurring,
however, because it's so difficult to swift through real relevant issues and just personal rants/garbage this becomes difficult. I don't want
to hear about what happened about the mall, that doesn't help me, that's not learning to me.


2) The objectives were not defined to an extent where everyone was on the same page
Again, this could be a personal opinion, but I felt the objectives were too broad. The result was people going off
in completely different tangents often becoming irrelevant and just rehashing what they read in the books. It seemed
as if nothing was really collaborative in the sense that the natural progression didn't occur. IMHO it would be better
if the objectives were really defined, giving everybody an equal starting point, making the architecture of the units
ideal for learning. You could argue that this is a 4th year class, and at this point we shouldn't have objectives like this,
but, we are designers, that’s what we do -- design based on objectives to satisfy whatever (a market or course objectives)


I applaud the fact that we are using new emerging tools to discuss the course content, this is really cutting-edge stuff.
With a few changes and tweaks (some that should be introduced by students by this process) the class would become
engaging and appealing. Until then, I'll try to salvage as much as possible from the first-run of the course.

Here's the google images I forgot to upload... Basically showing 2 seperate searches of two very popular CS/gaming websites.
What it's showing is an example of the power law, more specifically related to networks. The sites and linkages between them
take the same formations of balance that the power law suggests.

Another benefit of understanding the Internet topology is for the search engines themselves. Not only to compete with other SE’s but if they better understand the Internet and come up with efficient algorithms it can help other industries as well. By understanding the topology they can better design software, not just for the Internet but software in general for things like banks, and large intuitions that also include these types of power distributions. The SE’s can be thought of as a training ground for understand the exact relationships within the power law and its properties can be spread over industries. Lastly, “The model also applies to natural and social networks like metabolic groups of cells and actor collaborations”. Basically, this is just furthering the concept of understanding the distributions across industries. These power laws can be found in a variety of different sectors, so utilizing software to understand the WWW will definitely help the understanding of other non electronic controlled properties. Understanding the body of course would be helpful using information from research about internet topology as well. The list can go on and on…. One thing is important this is a very new topic of understanding and there is much more research to be done and money to be made.

I’ve explained how the WWW is viewed as a scale free, power law-distributed network. The underlying question behind this is, why this is important, what are the implications of understanding these concepts? This can be answered in both a macro and micro level understanding; multiple levels of recognition serve as the motivation for further research. There are 3 major groups or scenarios that well benefit most from understanding the internet topology, and its causes/effects.


Firstly, there is the small business, or even the web entrepreneurs/marketers who want to understand how the internet is distributed. This is strictly from a financial perspective however, and they are more particularly interested in how they [their site] relates to the rest of the WWW. The power law can be used to measure the degree of competitiveness in a specific network. So, an internet entrepreneur that wants to enter a new market or niche on the internet can better understand their relationship towards the web as a whole. Understanding how they fit into the bigger picture is important to them, so they know how to build and market their site better.
This was the stage I’ve been working in for probably the last 3 years, understanding internet search engines and algorithms that are based on internet topology is SO IMPORTANT in online marketing. Since this is an extremely new field, the research is still being formed, and it’s becoming increasingly important. I’ve read literally hundreds of sites or articles that try to explain the extremely complex system of www algorithms in order to better understand how to increase SE(search engine positions). There is virtually a whole new industry on the Internet of understanding search engines, with many, many people claiming they have figured it out. As with the rest of the Internet, the understanding of these SE algorithms can be unbelievably profitable once achieved. An article I read once before stated that a savvy web entrepreneur was able to generate 700K-1M dollars a day from 1 HTML page selling ‘Viagra’. He was able to understand how google sorts pages and he just linked his page to a company selling Viagra, making him MILLIONS AND MILLIONS of dollars for literally 20 minutes of actual work (coding). Financial gain is probably the biggest motivational factor to understanding the internet topology and the power law distributions that accompany them.

So, the power law basically states that “there are a small number of big things, a medium number of medium-sized things, and a large number of small things.” As I explained above, the distribution of the power always stays constant whether the internet is 2X or 10X bigger then its current state. The distribution will stay constant whether you are analyzing 50 sites or 50,000 sites, the power law is a mathematical equation with constant variables. This is what makes the WWW a ‘scale free’ network, because zooming in and out of the content will still field the same results.

Even if the size of the Web mushrooms to 10 times its current size, the degrees of separation would only rise slightly, from 19 to 21. That is likely to increase the reliance on intelligence search techniques that can adroitly skip from site to site, seeking out the most relevant or most popular sites within the Web behemoth

I found this weeks material very interesting, because a lot of it deals with the topology or physical shape of the internet, and the interrelationships between the nodes. With experience in Internet marketing, one of my roles was to get a high placement in Search Engines, which is easier said then done. What’s important to note is just how important the discovery of the Internet’s topology is, both financially and culturally. The World Wide Web can be looked at using the power law, a mathematical law that has been used to describe networks and topologies.

Recent research has shown that the overall distribution of links on the Web follows a power-law structure, meaning that a small number of large Web sites gain most new links, making them larger still. "This means that an extremely small number of Web pages have the vast majority of inlinks

OK, so basically how the power law applies to the WWW is because it’s using the form of rich get richer network. We all know from years of research that the majority of internet traffic is directed to the top 5% of websites, whereas the rest of the traffic is directed to the other 95% of websites. Using the power law, and understanding the algorithms of modern search engines, we can see why this is true.

In a rich-get-richer network, nodes that already have many inbound links tend to receive more over time. "Mathematically, the probability that a node receives another inlink is proportional to the number of inlinks it already has,--the rich nodes keep getting richer and the poor nodes can never catch up,"

The websites with more links continue to acquire more links, whereas the others also stay constant in relation to that as well, therefore giving view on the distribution of powers. What’s important to note is that even if the size of the web grows immensely, the power law will stay constant over time; therefore, making it vital for the understanding of the power law and the WWW to better increase our search engine techniques and algorithms.

Here is the image of the small network that is competitive CS gaming..

The reason why I choose this community is two fold, firstly, because I am very much apart of it (part of caleague, sogamed, etc) and that it shows the huge number of connections of the internet and underlying communities. Virtually every link on all those sites relate to counter-strike and competitive gaming in some way or fashion. Relating to concepts already learned, it’s almost like the example Johnson illustrates in emergence, about the affiliates stations pooling content from CNN. In this case, the content is being pooled from caleague.com and each of these sites can choose what they want. As he pointed out, sometimes CNN feels it would not be beneficial for them to post a particular news piece (just like it won’t be beneficial for caleague to post something about cheaters, etc) so in a sense, this feedback loop, or network is following the same style; since the sites can choose whatever they want to report. This both motivates the individual affiliates and helps the league to have a professional reputation. It was definitely beneficial for me to post this small network graph in order to better understand the community I am a part of.

As Taylor posted, I took the same community over the game Counter-Strike, but I refined it to be more specifically concentrated on the competitive aspect of the game. Like any traditional sport, Counter-Strike has a high competitive factor in which tournaments are based on. Basically constructed of 5 player teams, competition becomes a very feasible idea, and has become an absolutely huge part of gaming. The last counter-strike based tournament was based in Dallas, Texas where the winning team (clan from Sweden) won $200,000 from THE CPL or www.thecpl.com. This is a LAN tournament, and its online counter part serves as practice with thousands of clans participating, www.caleague.com . This is what the graph was based around, and each website or collections of sites are somehow related to caleague. The majority of content is based around the happenings of the leagues, such as demos of recent matches (as many as 1200 live spectators watching), rule changes, etc. Each of these sites are not particularly based around competitive gaming but link and interact with them somehow. As the graph shows, the ‘demo player’ made by sogamed.com, relates to caleague because that is where the demos of the matches come from. The fact that these sites literally share the same content, which is often generated by the same source, is what makes the community as a whole connected. Sogamed.com has 121,000 registered members, each with their own personal profile, each with their own personal demos, clans, friends, etc. As with the other sites like www.domainofgames.com, they all relate to counter-strike.net because that is the game that generates the most media attention(since it’s the most popular with a combined total of over 2.8 billion hours a month being played based on the latest statistic).

Another concept learned this week is the work of Paul Erdos, a famous mathematician, and his random graph idea. From my understanding of this graph, it is made up of random points and each of these is connected within a fixed probability. They then become independent to any other points on the graph. The basic idea that comes out of this is that the length or number of connections of links differs from both smaller and longer connections. What this states is that the mean length between any 2 connected nodes [if they are] is the logarithm of the number of nodes. This is based on years of mathematical research by an extremely smart mathematician. This is why I would be more willing to believe this random graph theory rather then believing the 6 degrees of separation concept…

The idea of the internet being a huge network can be used as a great example in further explaining this principle of small world networks. Many of the terms are universal, and can help explain social and nature networks quite well. A hub acts as a sort of connector towards the small network; connecting or linking itself towards something bigger. As tim points out in his web log post, small worlds can be related to hubs because hubs are in themselves small networks or connected nodes. Networks then, are obviously made up of many different hubs, these hubs are made up of nodes, each with separate links. So, from that, you can see how ‘someone’ or ‘something’ in another hub can be related to someone else in another hub, both connected by the larger network. This is a simple way of defining an extremely complex set of connections… which is why I still can’t agree with the idea of 6 degrees of separation concept. HRMM….

Well, after reading the weeks readings and trying to understand the concepts, I have sort of a pessimistic view on this idea of ‘6 degrees of separation’.
The small-world phenomenon formalizes the anecdotal notion that "you are only ever six ‘degrees of separation' away from anybody else on the planet."
As the Kevin bacon site reiterates, this idea was first introduced in 1967 by Stanley Milgram. The experiment basically worked by the following:
“sending a series of traceable letters from originating points in Kansas and Nebraska to one of two destinations in Boston. The letters could be sent only to someone whom the current holder knew by first name and who was presumably more likely than the holder to know the person to whom the letter was ultimately addressed. By requiring each intermediary to report their receipt of the letter, Milgram kept track of the letters and the demographic characteristics of their handlers. His results indicated a median chain length of about six, thus supporting the notion of "six degrees of separation"
The underlying idea behind the experiment is that everyone on the planet is linked within 6 links. Meaning, a starving child in Africa is somehow 6 related links (6 people) away from the person reading this post. Granted, his research does show this concept in action, and it can possibly be used to explain all the links on the internet but I personally don’t believe in it. I highly doubt that everything is related within 6 degrees of separation, primarily because these networks are inherently random to begin with and explaining them is difficult and complex. A significant amount of research still has to be made to explain these networks, and making a bold claim like that, based on a coincidental experimentation is not helping the cause. From my understanding of networks, chaos theory and on the evidence of his claims I don’t agree that everybody in the world is linked within 6 nodes.

Negative and positive systems have been transferred to digital systems quite nicely, as my above example points out. In general terms, negative feedback is a way of reaching an equilibrium point despite unpredictable and changing conditions (Johnson, 2002). It’s a way in which we can transform a complex system into a complex adaptive system(like the CNN example). Positive feedback then, propels the system onward as with the thermostat example. The emerging understanding of these systems will come to play once new software and ideas have been transferred to the WWW. As a designer, studying them is important in order to architect bottom-up adaptive systems in which they basically moderate themselves without leaders…. More to come….

Definitely the most interesting parts of the chapter are how; these feedback loops are so relevant to the internet and communities on the World Wide Web. By utilizing feedback loops, we are able to design and have better, more meaningful communication within our communities. The example used, was that of Slashdot.org, an extremely popular techie site that utilizes a rating system. This underlying system is a negative feedback loop, in which, users would moderate themselves based on user ratings and karma. By using this rating system, Slashdot
“not only encouraged quality in the submissions to the site; it also set up and environment where community leaders could naturally rise the surface. – Slashdot was not just a metaphor for winning the implicit trust of the Slashdot community; it was a quantifiable number. Karma had found a home in the database.”Truly impressive, slashdot has managed to incorporate feedback principles that have been used in our bodies for so long, and transfer these ideas into the World Wide Web. This is what makes studying these complex emerging systems so relevant.

The chapter on feedback loops in the emergence book was particularly interesting to me, an avid web designer. It accommodates insights on how to transfer offline community properties into an internet community. Some principles are universal, whereas some principles need to be changed in order to cope with the inherent differences of online communication. Things like lurkers on forums affect the type of communication, and these types of components must be realized in order to successfully design a web community. The chapter went into detail explaining how the media, front lined by CNN has gone through several significant changes, and now being based solely on feedback. Citing examples from Bill Clinton and various other political scandals, the media, especially TV, runs in a more bottom-up process—the system today has changed considerably from that time. Local affiliates now choose from a pool of content, that CNN itself can either air or not air depending on their views, HOWEVER, the local affiliates can now run ANYTHING from that content pool. From the affiliates side, it is beneficial because because they now have exciting, professional content to attract viewers. Conversely, it’s beneficial to CNN because they can become a content-provider for thousands of affiliates worldwide, signifying them as market leaders. This is very relevant to digital systems like the internet, since these properties and patterns help shape the World Wide Web.

As I was reading the course content, and specifically the cms, like a lot of students I was getting contradictory thoughts. Finally, though, I figured it out and after reading this http://davenet.userland.com/2000/11/30/bootstrapping it became clearer. As the generic definition states from both the CMS and the readings, bootstrapping is,
When engineers build a suspension bridge, first they draw a thin cable across a body of water. Then they use that cable to hoist a larger one. Then they use both cables to pull a third, and eventually create a thick cable of intertwined wires that you can drive a truck across
The first time I read that, I thought to myself, how the hell does that relate to computers and more importantly digital systems? Well, as I figured out soon enough, bootstrapping is the way in which software has worked from the very beginning. Bootstrapping is so relevant, that not studying it would be counter-productive in what we are doing. Basically, bootstrapping is the process in which the computer inherently works, or in which the software calls up the relevant resources. A good quote to sum these ideas up comes from Davenet,
Bootstrap is an ancient computer science term. When you turn on a computer it bootstraps, or "boots." First it loads the most ancient bit of code, probably written in the 1970s. It runs a program written in the 80s, which in turn launches a program written in the 90s. Each of the levels loads only for the purpose of loading the next bit of history.
It’s the method in which software calls upon its relevant predecessors, the method in which more complicated systems are formed from utilizing simple steps. By slowly working your way towards a more complex/difficult goal using simple, doable steps, the method of bootstrapping becomes useful – in both computers and other activities.

As it pertains to digital systems, booting up is how(the process in which) the computer begins to load all the appropriate resources. Not only has this been used in software, but in the world wide web as well, to develop better software and communities. The Internet itself can be used as an example of this bootstrapping methodology. As Tanya explained, it was originally designed for the military. This ties into the point made by Winer, “And unlike the designer of a suspension bridge, we must be more flexible, because the pace of innovation in our art is so rapid”. The internet was designed not for the uses of today but for the military, so in a sense, it had that idea of being flexible—since the original target market differed. Over the years, it has developed from simple bulletin boards, usenets and websites to an advanced system of communication that sufficient for online banking and purchasing. An Interesting question arose from that quote about being flexible while using bootstrapping, how do you stay flexible and design ‘bigger’ in a sense, while still designing for a specific audience or market? In several of my classes, it is repeated that designers should design towards a specific audience, and when there needs are met the system is a success. Is that the difference between designers and programmers? Albeit, there is a difference between the conceptual framework of digital systems and the actual application, but I believe the question is still valid.
Maybe I’m a bit off topic here, but if bootstrapping really does relate to the web and current digital systems then how does one both design flexible and towards an audience?

Regardless, bootstrapping is used in digital systems and it has been used to evolve the World Wide Web considerably. Before XML, there was HTML, each system is then loaded up and used as another resource for the most recent language. XML Could not form before the invention of HTML, and it literally uses its core as its engine in order to function. This is an example of bootstrapping, “Each of the levels loads only for the purpose of loading the next bit of history”. The analogy/methodology is obviously relevant but there are still some important questions that need to be answered IMHO.(read above!)

I was surfing some cool blogs today and stumbled upon nicks. The first thing that interested me was his little rant…

“Rant: why do companies continue to operate outside of complexity? With recent research and scientific observation explaining the ideas and concepts of complexity, you would think that organizations would finally realize that the existing top-down approach to management is highly ineffective and is preventing progress in our society. Why are we held back back large organizations who control our lives? Let's let complexity shine through and gather (individually on our own will power of course) to notify these people that complexity is the way of the future.”

I honestly do agree with him here, considering analyzing contemporary systems like organizational behavior is not where third culture intellectuals are focusing on, it is still relevant. I was just thinking, maybe these scientific systems, such as emergence can really be linked to things like marketing and organization hierarchy. Would better marketing methods come up with a harsher study on consumers being adaptive and seemingly random? Can complex systems accurately define how these corporations should work, and how/why they are succesfull? Is the success of Microsoft a complete managerial success or is because they realize and can predict how the world adapts to different environments… Do they know how complex systems affect the actual market and the users trends towards purchases? If complexity really is the wave of the future, just how much will it affect the world? Can all systems be defined within this boundary? …. I just noticed I asked about 50 questions there, maybe this whole module opened up more important questions that it answered? One thing’s for sure… more research in the way in which these complex systems emerge and adapt are necessary to give us a better understanding of life in general
.

Principle 3: Encourage random encounters

Johnston explains that the encounters within ants are sometimes random and can eventually alter the macrostate of the system itself. This is a component of the overall architecture that makes these systems so chaotic. Random interactions and encounters can eventually lead to a change in the overall system; either by forming sub systems or otherwise.

This principle can be applied to web logs, because the interactions that occur randomly are sometimes the most difficult to connect. Random interactions within our class can find some interesting similarities between both the way we think and our personalities. One student could go off an on their own separate tangent while posting, and they could link to another blog, even though they didn’t realize a connection at first. These chaotic connections can help define the system better, making the connections between the nodes stronger and more relevant.


Principle 4: Look for patterns in the signs

As Johnson notes, the ants rely and detect patterns in order to survive. The ability for them to identify patterns is important for them to survive.

By identifying patterns, it can help increase the overall intelligence of the system or blog, emerging the blog in a sense. If a pattern pops up, its important to follow that in order to foster more patterns that can emerge within that sign.

Principle 5: Pay attention to your neighbors

This is the most obvious of the principles, in order for a system to emerge, individual components must interact. Things that happen in individual nodes can definitely affect the larger system as a whole. In that sense, it is important that these miniature systems are being contributed.

As with web logs, its important for students to actually pay attention and understand others logs. Within our class, if we don’t have interconnections within our individual nodes then the system as a whole will not become better. Individual ideas are important, “Local Information ca lead to global wisdom”.

Principle 1: More is different

This concept can be applied quite nicely to the idea of statistics and generating a good user base. Johnson argues that “only by observing the entire system at work that the global behavior becomes apparent.”. This is an extremely important point to understand. By analyzing or utilizing a larger number of users or parts a better understanding of the system can be known. Moreover, trends or interactions between more nodes can be made accordingly.

This relates to web logging on a direct level. The more students, the more meaningful interactions can be made, within both a node-to-node level and within the overall system. Additionally, a greater sense of the flow or loop within the system will be known because more users are used to identify a trend. Having more students use web logs, you can see what trends are occurring and what the overall feel or flow of the system is.

Principle 2: Ignorance is useful

“Emergent systems can grow unwieldy when their component parts become excessively complicated.”

This was an important point that interested me, outlining the whole idea behind the ignorance is useful principle. Basically saying, don’t get off-topic, and create simple but efficient components is useful.

In the case of web logs, if all the students created simple but knowledgeable posts, then the system as a whole would be more concentrated and efficient/effective. The interconnectivity of these components is important, and by not being simple it can make the system less effective.

Principle 1: More is different

This concept can be applied quite nicely to the idea of statistics and generating a good user base. Johnson argues that “only by observing the entire system at work that the global behavior becomes apparent.”. This is an extremely important point to understand. By analyzing or utilizing a larger number of users or parts a better understanding of the system can be known. Moreover, trends or interactions between more nodes can be made accordingly.

This relates to web logging on a direct level. The more students, the more meaningful interactions can be made, within both a node-to-node level and within the overall system. Additionally, a greater sense of the flow or loop within the system will be known because more users are used to identify a trend. Having more students use web logs, you can see what trends are occurring and what the overall feel or flow of the system is.

Principle 2: Ignorance is useful

“Emergent systems can grow unwieldy when their component parts become excessively complicated.”

This was an important point that interested me, outlining the whole idea behind the ignorance is useful principle. Basically saying, don’t get off-topic, and create simple but efficient components is useful.

In the case of web logs, if all the students created simple but knowledgeable posts, then the system as a whole would be more concentrated and efficient/effective. The interconnectivity of these components is important, and by not being simple it can make the system less effective.

Principle 3: Encourage random encounters

Johnston explains that the encounters within ants are sometimes random and can eventually alter the macrostate of the system itself. This is a component of the overall architecture that makes these systems so chaotic. Random interactions and encounters can eventually lead to a change in the overall system; either by forming sub systems or otherwise.

This principle can be applied to web logs, because the interactions that occur randomly are sometimes the most difficult to connect. Random interactions within our class can find some interesting similarities between both the way we think and our personalities. One student could go off an on their own separate tangent while posting, and they could link to another blog, even though they didn’t realize a connection at first. These chaotic connections can help define the system better, making the connections between the nodes stronger and more relevant.


Principle 4: Look for patterns in the signs

As Johnson notes, the ants rely and detect patterns in order to survive. The ability for them to identify patterns is important for them to survive.

By identifying patterns, it can help increase the overall intelligence of the system or blog, emerging the blog in a sense. If a pattern pops up, its important to follow that in order to foster more patterns that can emerge within that sign.

Principle 5: Pay attention to your neighbors

This is the most obvious of the principles, in order for a system to emerge, individual components must interact. Things that happen in individual nodes can definitely affect the larger system as a whole. In that sense, it is important that these miniature systems are being contributed.

As with web logs, its important for students to actually pay attention and understand others logs. Within our class, if we don’t have interconnections within our individual nodes then the system as a whole will not become better. Individual ideas are important, “Local Information ca lead to global wisdom”.

I can’t think of a better way to relate the whole idea about the emerging third culture then using our school and our journey as an example. Third culture defined by the intellectuals who are striving to bridge the gap between science and art. This seems like a pretty decent description of all of us in IA that went through TECHBC. Not only are our courses a combination of both hardcore scientific theories that are made alongside art theories but we are actually learning how to learn creatively—utilizing both scientific and artistic methodologies. Moreover, we are able to communicate in a way where we can blend both sets of ideologies and strategies effectively in order to design or problem-solve. I’m not saying we are part of the third culture, but if the third culture is emerging, then we are certainly helping the cause by utilizing such interdisciplinary courses and technologies. The fact that we are using computer science techniques to maintain dynamic WebPages while theorizing and communicating artistic theories is relevant. We are practicing third culture because that is the most efficient way to learn for the future. The education in which we would receive is based on the fact that collaboration between fields is important. For example, as brad posted in his blog, flash could be used an example of third culture emerging. It’s both stems from art and the science, providing designers with absolutely powerful technology. This convergence is not only happening in theory(third culture theorists) but in the world as well. It will continue to emerge, until more suitable ideas about our societies are generated; humans are adapting in order to understand more.

Third culture… sounds like some mainstream horror movie about bacteria, doesn’t it? Third culture by definition is “those scientists and other thinkers in the empirical world who, through their work and expository writing, are taking the place of the traditional intellectual in rendering visible the deeper meanings of our lives, redefining who and what we are”. Basically, a sub division of the seemingly opposite fields of science and the arts; the third culture is the bridge between these gaps. Two fields that for centuries that have had different ideas about life and the systems that govern it. The third culture intellectuals that are credited to finding a new way of paving our societies and understanding complex systems come from a variety of different fields. From philosophers to biologists the “The emergence of the third culture introduces new modes of intellectual discourse”. Generally speaking, the third culture combines both sides of thinking to create intellectual discourse and to solve problems that have been plaguing society for centuries. Important questions like, where did the universe come from? Where did life come from? Where did the mind come from? By literally teaming up, the third culture theorists help to explain these meaningful questions. What is interesting to note here is the emergence of these individuals to adapt to the new century. What I mean is, scientists and ‘artists’ so to speak are now agreeing to agree, in order for the benefit of society—to answer important questions. The individual nodes of the system(people) that comprise the world as a system or whole are going through change and emerging (creating intelligence) in order to adapt. The Third culture can be described as an adaptation of humans in order to solve more complex problems using that logic.

yeah.......
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Obviously, there are always inherent design problems when designing a new system that’s never been tested before. Within all these systems, prototyping is essential, and research is important in order to make the design relevant to the users. Our class web log is new, it’s a new concept that has never been really done before in TECHBC/SFU, so in that sense, it would be difficult to design for. Continually, the concepts discussed above can be related to the design problems as well. The class meta blog, or all the blogs put together is part of a system. This system is comprised of individual nodes(individual blogs) and these nodes are linked together to create an adaptive system. As the definition of complex systems states, “ it has many components that interact in an interesting way”. The problem lies within that sentence, the components interact in an interesting, yet they are sometimes hard to estimate or predict. So theoretically if one doesn’t know how these components, IE. Students will interact that how can they design the frame/scope or the rules of the system? How can you design for an emergence without knowing exactly how the components will interact and adapt? The problem becomes the inevitable reality that the system will be randomly generated. Conversely, when designers are making a graphic interface, they KNOW their user, their habits and how they interact( how the body interacts and analyzes the screen, etc) which is why they can design so efficiently. On the other hand, emergence is somewhat chaotic, so it would be difficult to design a system in which it caters towards a positive loop.

At first glance, these concepts relate nothing to what we are studying, but when further analyzed its evident that they are extremely important. These concepts are relevant because they help define the system in which we are designing and how it flows and adapts. As future designers, we have to understand how networks and inviduals work, and how the overall system is made up. Moreover, its important to note the future and the trend of digital systems and this can be done by analyzing them in scientific ways. Science is relevant, and so is the underlying theories that have helped so many different industries for so many years. Studying them is essential if students want to create meaningful and RELEVANT projects or works.

It is often important while dealing with complex subjects to define the term completely, utilizing the definition that works within the context being argued. Webster’s defines adaptation as the following:
1 : the act or process of adapting : the state of being adapted
2 : adjustment to environmental conditions: as a : adjustment of a sense organ to the intensity or quality of stimulation b : modification of an organism or its parts that makes it more fit for existence under the conditions of its environment
3 : something that is adapted; specifically : a composition rewritten into a new form

From these definitions, we can see that generally, adaptation refers to objects or organisms adapting in a way to fit better within another environment. Additionally, the state of adaptation is that of being adapt, or even being more useful/productive. So, whether this adaptation is occurring at the macro or micro level, something is always adapting. This brings up a number of interesting concepts that can be related to both digital and natural systems quite easily. However, it is important to see how other important topics relate to emergence as well before quickly defining its core relationships within digital systems. Phase transitions are defined as, A change in a feature that characterizes a system. Within the context we are dealing with, this feature could be one of the components of complex systems. So from this, we could conclude that constant changes are being made on the micro level towards a better state of adaptation in order for the system to emerge. This is primarily what emergence is, the architecture behind emergence is a variety of different agents adapting and changing. Emergence in a multi-agent system is the collective behavior of the individual agents in such a system. Emergence is conspired through agent interactions and adaptations, emergence produces intelligence. Looking at everyday systems these principles and concepts can define them quite nicely. For example, looking at the economy, you can see how overall it is emerging, but behind the scenes each individual agent(Customers) are constantly adapting and going through changes. This is noticeable because of the constant changes both within individuals and within the industry, going through recession and different trends in order to become intelligent. The industry as a whole tries to become more efficient, intelligent by adapting to changing environments. These concepts and the general flow of the system can be applied to other systems as well, such as nature and social systems.

As I was doing research about emergence, its history and its theory by nature, I stumbled across an excellent site that put its definition in the simplest terms; at the most fundamental level, emergence is more then the sum of its parts. This was the following example “Human thought is reliant on nearly all the cells that make up the brain. If you cut out sections the results are completely different. A single cell is incapable of thought it is and emergent property of all the cells of a brain*. This is true for all cells.” Emergence is thought of as a dynamic-equilibrium which signifies seemingly-random change. Let’s face it, the whole theory behind emergence isn’t easy to simply grasp, to properly conceptualize concepts of this magnitude we often try to make an analogy of the situation. After reading the story about the slim mold and how they reacted and functioned without the pacemaker I realized just how this button-up design works. Moreover, the example above about the brain and the individual cells reminded me about a cartoon I used to watch frequently as a child, transformers. While not directly linked to emergence, the fundamental aspect about these machines is how they would form an extremely large machine using their bodies as the structure. Only by forming in that pattern, without a ‘pacemaker’ could they unlock the power of this larger, more /complex machine. On a simplistic level this machine is going through emergence – the ability for individual organisms or parts to create a more complex structure or system without the use of a leading-role. The modern day theory of emergence can be used to theorize today’s complex systems such as the Internet or our complex phone systems. As stweart dean explains “the American phone system is now so complex its started doing things a) it was not designed to do and b) people do not want to happen. After much research someone pointed out that they were the results of emergence.” It has become obvious that more extensive research into this topic is crucial at this point in time in order for the world to reach the third ‘phase’ of the emergence theory.

Without exercising mathematics, the theory of emergence can be identified by its core properties and fundamental principles. The university of California Philosophy department identifies the 3 major propositions from the theory of emergence, they are the following;
-that there are levels of existence defined in terms of degrees of integration;
-that there are marks which distinguish these levels from one another over and above the degrees of integration;
-that it is impossible to deduce the marks of a higher level from those of a lower level, and perhaps also (though this is not clear) impossible to deduce marks of a lower level from those of a higher.
The theories in itself and the continual research behind it cannot be defined or associated without the use of mathematics, so for my purpose that is a decent definition.

The theory of emergence, the study of complex systems and their dynamic equilibrium can be linked to web logging and the internet in general quite easily. At first glance one might think they are totally irrelevant topics that don’t pertain to each other, but when links looked more closely can be associated. Firstly, the Internet in itself is a structure comprised of little nodes, or organisms, and as a whole they form the ‘internet’ which acts as a super-node. By straight definition this can mean that the Internet has emergent properties. Another link I noticed, this one being a bit more far fetched pertains to web logging and its ultimate ‘goal’ for the author. The practice of web logging is considered a self expression, and at the same time is part of the authors goal to be part of a community. As the log progresses and more expression is jotted down, the author feels as if they are a part of something bigger, more complex – a society in which each person tries to become ‘better’ as a person. This may seem a bit off, but you have to think why people use web logs to begin with, to express themselves, to communicate what they think is relevant information, to be important. The practice of web logging is emerging and more people are becoming interested in expressing themselves to become apart of something that wasn’t possible unless they all formed this new system. More to come as I dig up some more links…….

References:
http://www.webslave.dircon.co.uk/alife/emergence.html
http://search.barnesandnoble.com/booksearch/isbnInquiry.asp?isbn=068486875X&pwb=1#ForewordsIntroductions
http://www.ditext.com/pepper/emerge.html