Semiotic dynamics

I’m in an informal reading group with some of the gang from complex systems, cog sci, and linguistics. One of the papers we’re reading for today really illuminated - in an HCI/d way - the talk Jeff was giving yesterday about the shared collective space of intention, meaning, and understanding. Since I know Dewey and Turner, et al, can seem a bit flimsy to some students with a more technical background, I thought the opening page of this paper made a great concrete example of how the complex emergence of meaning impacts our future technical designs.

Here is a link to google scholar (you still have to click the top link “Semiotic dynamics for embodied agents” by L. Steele to get the PDF): http://tinyurl.com/yqv2ov

To make this relate directly to our discussion yesterday, you might just consider semiotics as “words”, dynamics as “interactions”, and embodied agents as “people.” If you’re intrigued, move on to the later pages where you’ll see how the modern research in artificial intelligence (2006), very much mirrors the modern perspective on HCI/d that Indiana U teaches. This technical research in this paper clearly suggests that artificial intelligence specialists need to look at language acquisition and understanding as an emergent property of social context and shared interactions.

Just like Dewey.
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Semantic change of design.. Just a lot of questions

While I read the Dewey’s book, I was wondering if I am an artist, designer, or even scientist. My identity, just as a humble live creature is seriously getting to be ambiguous. When I was addicted to draw I thought I was an immature artist, when I had studied and worked in design I used to be a fake designer, and now, in this HCI area, I feel I am an irrational researcher in science field even though the field is somewhat different from natural science.         

Of course, I have read that someone have said in terms of the definitions of each area and the evidences they collect in order to support their argument in terms of the boundary between Art and Design, between Design and Science, and even, in the design discourse, the design from the realization of everyday life to technology-centered design to Human-centered design, and as Klaus Krippendorff said, if we need to consider of Science of Design, Design science, or Science for design or not.

For me, it is getting to be difficult to realize that what identity of design is where the boundary is and what its discourse stands up.        

In some moment, it seems to be clear for me, but in the other moment, I have no idea what it is.     

In addition, as if HCI people seem to enjoy jumping in its ambiguity when they design, they have thrown many questions and unsettled resolutions to me even though Jeff has been not to stop explaining what design is, what factors of human beings we need to consider, what theoretical methodology we need to study users. I think his explanation is just for him and his evidences that he collects, but not mine. He provides me with huge thinking space to make me ponder in the questions. And I have to think about the questions in my own way: How do I ultimately answer this question? How do I participate in the design discourse?  

The name of design, it changes its semantic body. It is like another aesthetical experience for me.     

Among the Thugs

I just remembered that I wanted to post the link to that book Among the Thugs I mentioned in the lecture about complex systems.  It’s an interesting read of first-hand experience with crowds and violence and mob mentality kind of stuff.  Plus, it’s all about hooligans, and who doesn’t love that cuddly bunch?

Attention Economy of Memes

We discussed meme’s in class earlier this week in relation to complex systems and HCI. As we mentioned, meme’s are a unit of cultural propagation similar to gene’s for the propagation of DNA. The Internet is responsible for dramatically increased rates of memetic cultural proliferation. However, the rate of memetic proliferation on the Internet has led to the discussion of a (sort of) new phenomena, the attention economy.First coined by the one and only Herbert Simon in 1971.

“…in an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it” 

Recently the notion of an attention economy has entered popular interaction design discourse. Specifically, the attention economy has gained a foothold in terms of customer retention on e-commerce sites. Keeping customers involved on a site with relevant information that enables purchasing decisions is a taxing enterprise. The most common solution is to use some sort of recommendation system, but we’re starting to see the limits of those systems as the complexity of e-commerce systems increase. Another concern of the attention economy, especially as it pertains to e-commerce, is the use of potentially private browsing behaviors for corporate gain. Essentially, what right does Amazon have to use my browsing behavior to improve the effectiveness of their recommendation system to increase their future profits? Sure, I might get a better recommendation too, but you can see the gray area.Now to go back to memes. Are meme’s subject to the attention economy? Will meme’s hit a “wall” like recommendation systems? Will the proliferation of meme’s expand so fast and so far that they we lose our ability to focus on any of them or are meme’s impervious to the effects of the attention economy? Or will those meme’s simply be replaced with others that do grab our attention?One last thought for the road.Recommendation systems are an attempt to control attention by providing helpful and relevant information. What systems do we have (or might we have) to control memetic propagation online? We’ve seen plenty of examples in previous posts about how designers embed values into designers (intentional and not) so how are we embedding memes in our designs?

Post-structuralism and Destiny

We’re talking about that every human being is a survival machine of genes, memes and maybe other units. From this perspective, is there a destiny for every person?

Like Shakespear, his genes, memes and the environment he was born into might be the crucial elements to his success. Are there other elements which lead to his achievement? Are all his personal efforts afterwards pre-destined by the gene, meme and the birth environment? The education and impact he received from the world around him can also be important, but are they also pre-destined before his birth?

There might also be some dynamic things going on which can be taken as coincidences. So are people’s lives just combinations of pre-destined elements and conincidences?

complex system

In my opinion, every design, as a process or design situation, is a complex system. I say so not only because that there is no single correct/wrong answer,  but also, again, function follows forms. Function is not the result, but the function!–What you could or might get from what you do during the design process was decided how you do it, although it is not guaranteed that you would get it. To say this maybe is too confused. For example, I realized that what kind of questions I asked during the interview process is super-important. What the questions is, and at what time in the sequence I ask a specific question, what kind of manner or tone I use  when I ask questions, all of these matters for an interview, and maybe directly related with what kind of data I could get in both quality and quantity, and nobody cares how much hours I prepare the questions. Nobody knows how could we get a useful and meaningful data for a design project by doing interview, no theory could teach me. At this point, I could only remember one thing: practice makes perfect. Because as a human being, I am a self-reflect machine and could learn from the practice, even unconsciously!However, “genetic mutation” always happens, and I am sure it exists in the design process as well as HCI. It could be a totally refresh air for specific situation, or an evil design. Inter-disciplines is very popular and people believe that by introducing people from different background into the design team would benefit to our work. Anyway, how could we control these kind of situations?

Natural Selection in Design

Affinova.com is a company which has explicitly adopted an evolutionary approach to product design.  Essentially, products are broken down into genetic components which are then evolved by a group of participants.

Interaction Culture: the Study of Non-Linear Systems

So i’m reading a paper today by Chris Langton on the subject of Artificial Life (available online at http://www.aec.at/en/archiv_files/19931/E1993_025.pdf), in which he points out the fundamental differences between approaches to studying linear and non-linear systems.  I would say that in researching Interaction Culture, we must more fully understand ourselves to be dealing with non-linear systems, and adjust our epistemology accordingly.  I’ll leave it up to Chris to elaborate (from the paper, pgs 12-13):

“..the distinction between linear and nonlinear systems is fundamental, and provides excellent insight into why the principles underlying the dynamics of life should be so hard to discover. The simplest way to state the distinction is to say that linear systems are those for which the behavior of the whole is just the sum of the behavior of its parts, while for nonlinear systems, the behavior of the whole is more than the sum of its parts. Linear systems are those which obey the principle of superposition. We can break up complicated linear systems into simpler constituent parts, and analyze these parts independently. Once we have reached an understanding of the parts in isolation, we can achieve a full understanding of the whole system by composing our understandings of the isolated parts. This is the key feature of linear systems: by studying the parts in isolation, we can learn everything we need to know about the complete system.

This is not possible for nonlinear systems, which do not obey the principle of superposition . Even if we can break such systems up into simpler constituent parts, and even if we can reach a complete understanding of the parts in isolation, we would not be able to compose our understandings of the individual parts into an understanding of the whole system. The key feature of nonlinear systems is that their primary behaviors of interest are properties of the interactions between parts, rather than being properties of the parts themselves, and these interaction-based properties necessarily disappear when the parts are studied independently.

The process that we call “life” is a fundamentally nonlinear process, emerging out of interactions between non-living parts. Life is a property of form, not matter, a result of the organization of matter rather than something that inheres in the matter itself. Neither nucleotides nor amino acids nor any other carbon-chain molecule is alive — yet put them together in the right way, and the dynamic behavior that emerges out of their interactions is what we call life. It is effects, not things, upon which life is based — life is a kind of behavior, not a kind of stuff — and as such, it is constituted of simpler behaviors, not simpler stuff.

Thus, analysis is most fruitfully applied to linear systems. Such systems can be taken apart in meaningful ways, the resulting pieces solved, and the solutions obtained from solving the pieces can be put back together in such a way that one has a solution for the whole system.

Analysis has not proved anywhere near as effective when applied to nonlinear systems: the nonlinear system must be treated as a whole.

A different approach to the study of nonlinear systems involves the inverse of analysis: synthesis. Rather than start with the behavior of interest and attempting to analyze it into its constituent parts, we start with constituent parts and put them together in the attempt to synthesize the behavior of interest. Analysis is most appropriate for the understanding of linear systems, synthesis is the most appropriate for the understanding of nonlinear systems.” (pages 12-13)

I will illustrate this idea here with an example.  Seeking to understand MySpace is similar to understanding the genesis of life in an important sense.  Studying one user or one page on MySpace (the approach appropriate if it were a linear system) could not have predicted that the site would gain 100 million users any more than studying one amino acid could have predicted that i would exist as a quasi-intelligent life form who writes posts for a professor with strongly idealistic hockey affinities.  But once i realize that MySpace or quasi-intelligent life has a non-linear relationship with the behaviors of their requisite parts (millions of users and millions of profiles are what create the macro-level behavior of MySpace), i have made the first step toward being able to understand  MySpace and, if i’m very clever in my “synthetic” approach, i might be able to guess at how i might create a competing social network for sub-intelligent life.

Another point made elsewhere in the paper is that the only way to understand non-linear systems (since their underlying mechanics can’t be predicted by looking at the final system)  is to create models of the systems and see how they behave.  I believe that this concept also supports a design methodology that puts at least prototypes, if not artifacts, out into the real world iteratively and often, since the effects, the meanings and the uses of artifacts in an Interaction Culture are probably too complex to predict ahead of time.

Social Informatics

This is NOT a plug for SLIS…
I mentioned it in class last week during our list discussion and so I’m posting the link.

http://rkcsi.indiana.edu/index.php/about-social-informatics

I’ve been reading some of Kling’s work and it definitely relates to some of the issues we’ve discussed in class, especially the role of society while designing technology. The definition of social informatics in this sense (as taken from site):

Social Informatics (SI) refers to the body of research and study that examines social aspects of computerization — including the roles of information technology in social and organizational change and the ways that the social organization of information technologies are influenced by social forces and social practices. SI includes studies and other analyses that are labeled as social impacts of computing, social analysis of computing, studies of computer-mediate communication (CMC), information policy, “computers and society,” organizational informatics, interpretive informatics, and so on.

SI studies and SI courses are organized within diverse fields, including information systems, anthropology, computer science, communications, sociology, library and information science, political science and science and technology studies (STS). SI provides a common meeting ground for isolated and scattered scholars to locate each other as well as relevant academic programs and courses.

Social Informatics is a relatively new term that can serve as a banner for those who are interested in contributing to these studies. The name “Social Informatics” can also serve as a pointer, by which we can help lead others to appropriate theories, key ideas, studies, findings, books, articles, courses of study, etc.

Complex Babbling

Jeff’s last lecture has got me thinking that much of Massive Amateur Culture is about emergence.

Platforms emerge, the things that people create on them emerge and cultural phenomena emerge as people interact with (and even change) those products. The whole thing is one big complex system, whose most beautiful and exciting output is often entirely unintended and unanticipated. Pretty cool.

It reminds me of a story I read about when the engineers at Atari designed the Stella (a.k.a. Atari 2600) game system back in the mid-1970s. Apparently, they thought that at most maybe a dozen or so games could ultimately be created for it. What they didn’t anticipate was that the Atari 2600 would go on to become the first video game platform, for which hundreds of games would ultimately be developed. That was some pretty cool emergence, if you ask me.

And today, platforms pop up all over the digital landscape, all of the time. Some intended, but some unintended (or emergent) as well. And when platforms happen, the things that people create for them are often unintended (or emergent) as well. And as the emergent products of these emergent platforms become part of our collective consciousness in various ways, they begin to inform how we perceive our lives and the world. And that’s just wild to me, that we create HCI stuff for whatever reason and to whatever ends we might imagine, but then we give it to the complex, churning world of culture and ideas and it starts creating all of these new and unimagined emergent things.

Wow.