We are living an increasingly mediated life. As we intensively interact with computers in our daily life, two sets of symbols, human meaning system (usually referred to natural language) and “computational” meaning system (mediated meaning system simulating and representing human meaning system), are being used simultaneously and interactively. In fact, even without physically manipulating a computer, habitually, we are using computational thinking to solve problems, in which we are mediated by the technologies.

This mediation has been institutionalized; it has been collectively and culturally accepted after intersubjective practice. The reason why we are happy with interacting with computers is that we can gain efficiency from this process to some extent. The relative efficiency is realized through the affordances provided by the technologies. By offloading or distributing some part of our cognition functions into physical technologies, we are externalizing cognitive process, which was believed to be “imperceptible”, into perceptible devices. This embodiment is a remediated process and realized by the invisible and intelligible affordances. As we mentioned in the post of week 9, Venmo provides the affordances of calculating, initiating transaction, commenting, etc. While using this application, we are getting used to the icons, index and symbols intuitively in a human thinking way. If the process of accommodating ourselves to the context of this application is natural and smooth, we consider this application as a good example of humanized technology, which narrowing the gap between human and technology. If we get lost in mapping ourselves into this new set of symbols, the application is failed in simulating and remediating human semiosis.

It is why we are limited by the affordances as well. I happened to read a paper called “Are digital media institutions shaping youth’s intimate stories? Strategies and tactics in the social networking site Netlog” (Sander De Ridder, 2015). In this paper, Ridder insisted that SNS has established some institutions to shape youth’s intimate storytelling online. She also argued that the digital media reproduce the mainstream culture and make it even more prevailing. The “strategies” refer to the software design of the SNS, which provides affordances or options for audiences to self-represent themselves online. The “tactics” refer to audiences’ responsive behavior to accept or resist this predefined software context. Online storytelling involves information representation and information process as many other mediated symbolic cognition processes do. Researching how digital media institutions shaping online storytelling inspires me a lot to think about how we are limited by the affordances. For example, on Facebook, formerly we are only allowed to choose between male and female – just like there are two sides of a paper. Now, we are glad to see that we can custom our gender, getting rid of the “limitation” on self-representing ourselves online to some extent.

I think it is a vivid example of how computational context or digital media shape our information representing via predefined affordances.

The influence brought by the technology can also be observed in the case excluding the interaction with computers. Human’s (only human) computational thinking process is an example of how human are jumping back and forth between our own meaning system and “computational” system. The redefinition of computation and the term “computational thinking” put the emphasis on information representation, which is more inclusive to engage the human agent in this process. Different from delegating agency to the technologies and using them to extend and distribute cognitive abilities, we “computationalize” ourselves as well. In other words, we are not going to “physically” turn into a machine; we can reinterpret our thinking process in terms of computational terminologies. When we are solving a problem, we take discrete steps to formulating a solution. From the former step to the current step, we map out a “correct” path, excluding all the “wrong” path. In essential, excluding uncertainties to find out the certain path is an information process. The only difference between how human process information and how computers process information is that we are using different meaning systems. Nevertheless, we can still term the process of finding the solution to the problem as “computation”; we can still term our way of working out the problem as “computational thinking”.

In general, it is a “conceptualized” post that allows me to connect the key concepts to explain what happened between different sets of symbols. The basic argument is that “humanization” and “computationalization” can happen simultaneously, and these phenomena represent the computation process, the transformation between one set of symbols to another set of symbols.

References:

1. Irvine, Martin. “Introduction: Toward a Synthesis of Our Studies on Semiotics, Artefacts, and Computing.“
2. Denning, Peter. “What Is Computation?” Originally published in Ubiquity (ACM), August 26, 2010, and republished as “Opening Statement: What Is Computation?” The Computer Journal 55, no. 7 (July 1, 2012): 805-10.

TEAM: BEAUTY♡ PRETTY☆ SOCIETY♀ (Ruizhong & Yasheng)

I (Yasheng) just started learning how to do basic coding on Arduino and, to my surprise, the learning process was actually painless.

Here is an example on why learning to code is easy:

Arduino’s software comes with a lot of examples and you can just open them up to practice, and when you feel like you are confident in what you are learning, you can just modify the codes to make a new project. The information in the red block in the right of the graphic shows that the programmers of Arduino explained what how to utilize different classes and their instances. It feels like learning a new language in just minutes and I did not even have to take exams. My experience is consistent with the essence of Kay’s vision: “to provide users with a programming environment, examples of programs, and already written general tools so the users will be able to make their own creative tools. (32)” The reason why I feel the basics of coding is easy to acquire is that coding is not a brand new language, rather it uses “already existing representational formats as their building blocks, while adding many new previously nonexistent properties. (23)” This makes us think, why didn’t we learning computing this way from the beginning? Instead of treating it like a blackbox, we should have studied how programing works from a fundamental level. The interface of Arduino helps me to interact with the hardware directly, and we can see evidence of such system in Kay, Nelson, and others’ theoretical framework. We take advantage of Kay, Nelson, and others’ system of interaction – meta-systems, to “support the processes of thinking, discovery, decision making, and creative expression. (53)”

I (Ruizhong) have been learning Javascript (p5js) for about one year. What impressed me is the “all-in-one” style of this programming language website. The programming environment is easy to manipulate. I started to learn the syntax of the language by playing with it. With bunch of examples, I could adjust some parameters in the code and simultaneously see what changes happened in the output. It is not necessary for me to start from drawing basic shapes to complicated-structured image. I could start from a macro-view of how all these codes function, and acquire the knowledge of syntax through practice. With the libraries imported into the code, I could also make use of to the “mature” “building blocks” which function as a whole with only a few lines of code to create my personalized meaning tool.

The experience of learning p5js contrasts with my learning experience with Python. With a tutor teaching us in a traditional way, I feel it is a little bit “overcautious” while we moving forward to the next stage. With a problem proposed at the beginning, we practice the routine of solving a problem using Python code from drawing flowchart to writing code. We cannot directly see the relation between the code and output. I have no idea of how the code should look like. It seems to me that the codes stay as a conceptual level, and can never be brought into reality. Therefore, for me advantage of GUI and software is enhanced with this contrast in my learning experiences.

It is not surprising to us anymore that how much we can do using computers yet it is surprising to find out how the idea we take granted is formulated by people like Alan Kay. We are especially fascinated by Kay’s concept of Smalltalk. Smalltalk, as an early stage of all object-oriented programming software, is remarkable in the sense that it simplifies the thought process into small building blocks and creating meaning using these building blocks feel just like using our brain – only externally. Thanks to technological advancement, we can now do almost everything on a small laptop, from drawing to making music, or in Alan Kay’s term a “personal dynamic media” system (metamedium) that grants us endless possibilities.

No wonder people call Alan Kay a visionary – he was correct in thinking of a computer as new media generation engine during a time when a computer metamedium was only coming into existence.

According to Alan Kay, “symmetric authoring and consuming is quite lacking in today’s computing for general public.” In Kay’s vision, people are allowed to create, manipulate, sequence and share media across the world with the software. To realize his vision, modern technologies like notebook, tablet, and smartphone have fulfilled his expectation in terms of physical forms. However, the problem lays within the lack of open source. Open source is not a new concept, yet it still receives little attention comparing to massive success of Smartphone, PCs, and other products. Kay’s vision is closer to the Linux system, manifested as Raspberry Pie, Arduino, and other small appliances. These small appliances all have an open source library and easy to understand interface, yet they require a certain level of literacy for users to fully take advantage of it usability. Smartphones and tablets, on the other hand, are made into more and more like black boxes, allowing people to communicate and to create only at a surface level. If there is a way to combine the flexibility of Raspberry Pie with the affordance of smartphone, a Kay-styled Dynabook can be possible.

Speaking of flexibility, Kay’s vison is still not made possible. We still have the overarching notion that technology evolves does not evolve with us, but it continues follows a standard practice. Kay maintains that, “There is also the QWERTY phenomenon, where a good or bad idea becomes really bad and sticks because it is ingrained in usage.” So in terms of usability design, a truly “dynamic” interface should grant users freedom to truly personalize their experience with the machines. Furthermore, literacy of technology should be reduced to teaching people “building blocks” instead of teaching them to “Press to unlock” (formally known as “swipe to unlock”).

• Lev Manovich, Software Takes Command, pp. 55-239; and Conclusion.Follow Manovich's central arguments about "metamedium", "hybrid media", and "interfaces" and the importance of Allan Kay's "Dynabook" Metamedium concept.

• Jay David Bolter and Richard Grusin, Remediation: Understanding New Media. Cambridge, MA: The MIT Press, 2000Martin Campbell-Kelly and William Aspray. Computer: A History Of The Information Machine. 3rd ed. Boulder, CO: Westview Press, 2014.

• Kay, Alan C. “Microelectronics and the Personal Computer.” Scientific American 237, no. 3 (September 1977): 230-44.

• Alan Kay and Adele Goldberg, “Personal Dynamic Media” (1977), excerpt from The New Media Reader, ed. Noah Wardrip-Fruin and Nick Montfort. Originally published in Computer 10(3):31–41, March 1977. (Cambridge, MA: The MIT Press, 2003), 393–404.
  

• Kay, Alan C. “Microelectronics and the Personal Computer.” Scientific American 237, no. 3 (September 1977): 230-44.
  

• Interview with Kay in Time Magazine (April, 2013). Interesting background on the conceptual history of the GUI, computer interfaces for "interaction," and today's computing devices.
  

• Butler Lampson's original 1972 memo on the Xerox Alto computer, the first "personal" computer implementing a GUI Windows and mouse system and networked via Ethernet.

Interacting with computers, we human are on a continuum between ourselves and computers. According to Licklider’s depiction of “Man-Computer Symbiosis”, in order to enable the effective man-computer interaction, human and computers should work on the same display surface. In that case, before we get to that point when human and computers literally can work collaboratively, where is human’s position on the contimuum in this process?

It is interesting to know that Licklider’s effort to clarify “man-computer symbiosis” is considered as a way to humanize computing. We are getting computer adapted to human thinking. However, in the process of getting computer stayed tune with human, human is adapted to computer in this process as well. Extrapolating from it, it is true that human function as an agent in the development of technology, but technologies are self-evolved according to their innate mechanism. The role human play in the process is to take advantage of the technology and, according to human’s need, to decide what’s the main technology human would probably make heavy use of in the next decade. In this process, human can benefit from what affordances provided by the technologies, but also cannot get rid of the constraints of the technology.

As we look back into the history, it’s not hard to find that many of the computing technologies were developed during the post-War period. We cannot neglect the social context when we recount the history of computing. In the post-War period, there were growing demands of accuracy and efficiency in computing. It seems that the atomic blast that ended the World War II have an unforgettable impact on post-War scientific research. The eager for nuclear technology created the need for developing the basic computing technology. The most important feature of Sketchpad when it was invented in 1960s, was to perform rapid and accurate calculation, and model the architecture design: both of the two features are related to the preparation of arm race.

But look at the Sketchpad technology today, it is widely employed in our daily life, like handwriting system in our mobile phone, and children’s eco-friendly sketchpad.

It seems that using Sketchpad technology to do these daily things are like employing a steam engine to crack a nut. Is it? I think it is the necessary “backwards” of the technology. They are sharing the similar mechanisms, but they are differentiated by their usage. Using a mature technology to find radical new ways of using such technology. It reminds me of Gunpei Yokoi’s philosophy: lateral thinking with withered technology.

“Withered technology” in this context refers to a mature technology which is cheap and well understood. “Lateral thinking” refers to finding radical new ways of using such technology. Yokoi held that toys and games do not necessarily require cutting edge technology; sometimes, expensive cutting edge technology can get in the way of developing a new product.

It is exactly what is going on between human and technology. If we could slow down and have a look at the way we were coming through, human are driven by the social needs all the time. That’s why we are in a passive position in the development of technology. We do not have enough time to understand the computers, and we lock the secret of how computer working in a little box. We are going too fast to understand what’s going on in the world. Using Sketchpad for daily use is a sign that we could change our way of thinking and be ready to embrace another breakthrough.

Reference:

Martin Irvine, “Introduction to Affordances and Interfaces: Semiotic Foundations”

Mahoney, Michael S. “The Histories of Computing(s).” Interdisciplinary Science Reviews 30, no. 2 (June 2005): 119–35.

Bush, Vannevar. 1945. “As We May Think.” The Atlantic.

Conery, John. 2010.  “Computation Is Symbol Manipulation.” The Computer Journal, 55, no. 7.

Licklider, J.C.R. 1960. “Man-Computer Symbiosis”. New Media Reader. Wardrip-Fruin, Noah, Nick Montfort, ed.. 74–82. Cambridge, MA: The MIT Press, 2003.

Among the computing principles, the COMPUTATION category is the most impressive one. The computation category addresses the problem of converting complex problems into a number of computational steps to achieve a solution.

When I was learning Python on campus, in order to solve a problem, the tutor always started with a flowchart. For example, if she wanted to print out “Hello World” for 5 times, here is her workflow:

First, she would draw a flowchart:

Computational thinking is a way humans solve problems. In the process of drawing the flowchart, we are thinking in human’s way. Print out “Hello World” for 5 times, intuitively we have to define how many times and what to print, and then print it out. These steps in our mind are exactly depicted by the flowchart, as well as the code.

| while loop |

i = 0

nbrTimesToPrint = 5

while (i < nbrTimesToPrint) :

print(‘Hello World’)

i = i+1

In the code, we use the variable i as a counter to count from 0 to 4, which is 5 times. Using the while loop, the little program repeats the “print” action for 5 times in only 5 lines. The number of the lines will be the same even if we want to print it out for hundreds of times, thousands of times.

Therefore, the advantage of the abstraction is manifest. If you cannot abstract “printing ‘Hello World’ for 5 times” as a repeating process, it is impossible for you to think about having a loop in your code. The flowchart will be like this:

and the code will be:

print(‘Hello World’)

print(‘Hello World’)

print(‘Hello World’)

print(‘Hello World’)

print(‘Hello World’)

The number of lines is the same as the loop one; this version of code is even more explicit. It is coder’s call. For now, the requirements are easy to meet with: even with the second one without loop, the problem can still be solved in a few lines, but for further consideration, the loop one is more advantageous for sure.

It should be noted that human thinking come first and then computational thinking. The decision of whether to loop or directly to command for 5 times, has been made in human’s mind. The idea of loop is not taught by the computation or software; it is our developed logical thinking that enables us to simplify the steps by making use of loop.

We can observe the existence of RECURSION from this tiny program as well. Making use of the value of the counter variable i, with the comparing between the counter and the variable nbrTimesToPrint, the program knows when to stop. As we can see, the counter i needs an initial value i=0, and then with i = i+1 at the end of the program, the counter adds 1 when the program run through the whole process for one time. The counter is the descriptive feature of the program accounting for how many times the program has run, and it is this value that determines the end of the program.

Computing is the automation of abstractions. Computational thinking focuses on the process of abstraction. The computation and software rely on human minds, and by writing out the codes, human have a chance to recount what’s going on in their minds in an observable way.

Reference:

Information Is a Physical Order

This week’s readings about information theory remind me of the book I read last semester: Why Information Grows: The Evolution of Order, from Atoms to Economies. The author, Cesar Hidalgo, maintains that information is not a thing, rather, it is the arrangement of physical things. It is a physical order. The contrary side to the order is randomness, therefore, the information grows by overcoming the randomness. This point of view aligns with Claude Shannon’s opinion. Borrowing the idea from thermodynamics, Shannon calls the random, uncertainty principle “entropy”. What is the most important, Shannon proves that the entropy can be measured and controlled, which provides possibility to reduce the uncertainty to generate and communicate information. Since entropy can be measured, the same logic, the information can be measured as well. The basic measurement is used to quantify how much information will potentially be used to encode, transmit, and decode electronic signals. The measurement introduces the concept, bit (binary digit), which comes from Boolean logic.

Why can’t we extrapolate from the “information theory” model to explain transmission of meanings?

Because the information theory model excludes the meaning.

The signal transmission model is based on binary math, combined with the logic of probability theory. It is the method for signal transmission, not meaning transmission. People always blur the boundary between signal transmission and meaning transmission because we have the ability to interpret messages and infuse them with meaning. But what is going through the physical wires is not the meaning, but the signal. The information itself doesn’t contain any meaning.

Where are the meanings in our understanding of messages, media, and artefacts?

Meaning is created during semiosis.

Meaning exists nowhere but the process when we perceive the signals. As socially symbolic beings always live in technically mediated symbol systems and use information to exchange meanings. Since human are social and collective animals, the meaning-making happens during a certain community, in which people share a common ground on interpreting specific signals. The way that people interpret signals mean is embedded in the social structure and context. It doesn’t mean that the meaning exists somewhere. The meaning-making is a dynamic process, although to some extent it is subject to the social context.

What is needed to complete the information-communication-meaning model to account for the contexts, uses, and human environments of presupposed meaning not explicitly stated in any specific string of symbols used to represent the “information” of a “transmitted message”? 

Information theory + semiotics = the whole story.

Shannon’s signal transmission model perfectly explain how information encoded and decoded in a physical aspect. What it leaves out is the meaning system. Semiotics bridges this gap between bit and meaning. Semiotics addresses the process from symbols to meanings, which help complete the process from bit, a kind of symbol, to meaning. Information theory only talks about the input and output on the both sides of the black box, but semiotics clarifies what is inside the box. For example, the triadic structure and the parallel architecture help understand the process of interpreting the symbol from object – representamen – interpretant, in phonological, syntactic, and semantic aspect simultaneously.

[1] Irvine, Martin. “Introduction to the Technical Theory of Information.”

[2] Cesar, Hidalgo. “Why Information Grows: The Evolution of Order, from Atoms to Economies.“

‘Pepe the Frog’ meme deemed a hate symbol by Anti-Defamation League

When I saw the title this morning, I am not sure whether I can understand what it means, even though I know every single word in this title. As I scrolled down the screen, a picture showed up:

The Deplorables

OK, well, I have to admit that the only thing I know about the picture is that the guy in the middle is Donald Trump. But, wait … what’s that frog? It looks so familiar to me. Oh! that’s the famous meme! The sad frog! As I looked back to the title, I realized that the frog is not named as “sad frog”; it’s called “Pepe the Frog”. And as I continued to read the news, I even found out that the frog was not designed as “a sad frog” at the very beginning. The design of the picture looks like adapting from the poster of The Expendables – nice mimicking, but, what does “The Deplorables” mean? These people (and the frog) are put into the same frame because they are “The Deplorables”. The literal meaning of “deplorable” is “deserving strong condemnation”, but as I continued the search, it turns out that “the deplorables,” means people who are racist, sexist, homophobic or xenophobic.

… STOP! I am overwhelmed now. The series of self-asking and self-answering process shows that several pairs of triadic (as Peirce would say) relationships are going on here. The frustrated feeling accompanies with my superficial understanding – I only know one vertex of the triangle. For example, if I was overhearing someone’s conversation, and they were talking about “Pepe the Frog”, I would probably ask a question: what is “Pepe the Frog”. And they would show me a picture, and as soon as I saw the picture, I would suddenly realize that, “Oh! It is THIS frog”. I only store the symbol (representamen) of the frog in my mind, and merely with the symbol I cannot communicate the referent (object) with people. It is the object that provide people with an interface to communicate the concept and thought (interpretant). There is no direct relation between the symbol and the referent, I think the relation between the symbol (representamen) and the referent(object) is mediated by the thought (interpertant). Since I have a wrong u nderstanding of the origin of the frog, which leads to misunderstanding the relation between the representamen and the interpretant (a relaxed frog was misinterpreted as a sad frog), let alone the relation between a wrong interpretant and the object. Therefore, establishing “correct” relation between three vertices relies upon individual’s experience. I have never seen the comic, where “Pepe the Frog” made his debut. I didn’t experience the process how “Pepe the Frog” became famous on the Internet starting from 4chan.com. At the first time I met “Pepe the Frog”, he was already deemed “sad”. I set up a wrong relationship between the symbol in my mind, and the interpretant, and the object. Fortunately, today’s experience helped me integrate the three vertices.

However, sometimes I get lost in setting up the relationship between the three vertices because of the culture or social context. That’s why I say that it’s a long way to go from a frog to a hate symbol (at least for me). Hardly can I relate this frog meme to “White Supremacy”. As Ogden & Richard suggested, “When we speak, the symbolism we employ is caused partly by the reference we are making and partly by social and psychological factors”. We cannot get rid of the social context when communicating. Those people growing up in similar circumstances share the common ground when they are talking and the common ground has been embedded in the society structure, or institutionalized. The cognition process is intersubjective, and is generated by adding on social factors. In this case, people who grew up in America, and had a strong interest in politics and discrimination issues would easily go through the chain of sign-situation intervening between the act (making a reference) and its referent (the outcome of the act). For me, it’s a long way to go, because I know little about the both ends of the relationship, and limited by my culture circumstances, being indifferent to politics has become a normal thing in my life. That’s the reason why I think it is incredible to make such a reference.

Reference:

What is language?

Defined by linguists, language is a cognitive system which is part of every single person’s mental structure. Linguists believe that cognitive capacities are the product of structures in human mind. Given the hypothesis, language research is inseparable from the study of human brain and psychological process. Going beyond the individuals, language is an intersubjective system of meaning making dependent on collective cognition. Language is the primary tool for human to communicate information and ideas, however, why language became the primary cognitive system that is collectively shared by the human species remains mysteries.

What is the human capacity for language in general?

Human capacity for language is termed as language faculty. When we say language distinguishes humans from other species, in fact, it is the language faculty that makes the difference. Language faculty is the native speakers’ competence in that certain language. The competence of knowing a certain language equals having a certain mentally represented grammar. Native English speakers share common characteristics in their mental structure and it is same logic for any other language. People speaking different languages maintain different mental states. Regardless of the difference, language faculty is not specific to any one human language. That is to say, despite each language is governed by its distinctive grammar, all these grammars share principles of Universal Grammar, which go beyond a certain language, and define the features necessary for any language to be a certain language.

What is “a language,” What are the essential features that enables a language to be a language? 

As mentioned, the essential features that enables a language to be a language are termed as Universal Grammar. A language works according a set of rules. The essence of a language is phrase structure rules. It is these rules that allow for unlimited creativity of phrases and sentences. To form the grammar that is universal to any kind of languages, four components are indispensable: lexicon, syntactic component, phonology form component, and logical form component. It is comprehensible including the lexicon and syntactic component as a part of grammar. Lexicon is the brick for building a house. The syntactic component is the knowledge of architecture. Something special about language is that speech is generated with a sequence of words, and the “neighbors” of a word may change its phonetic form. For instance, the pronunciations of “west” in “west side” and “to the west” are definitely different. Another special point of language is that language is a tool for meaning-making, sometimes ambiguity occurs without the logical constraints. Think about a sentence: The boy saw the man with the telescope. We are not sure whether “with the telescope” is a complement for “the boy” or “the man” without the logical inference.

What are the implications of using the features of language as the model for other symbolic systems (visual, audio, and multimedia combinations) and for most forms of communication and media?

Language is one certain kind of symbolic system among numerous symbolic systems on the earth. Among all the symbolic systems, language emerges as the primary cognitive system of human being. The collective cognition is the most distinctive characteristics of language compared to other symbolic systems. Is it reasonable to apply the features of language to other symbolic system? I think it is a tentative process. Derived from the hypothesis in linguistics research, we can also form a more generalized term “symbolic faculty”, which could be applied to some specific field and specific group of people. Going to concert and art exhibition, is another way for people to communicate via visual arts or music. The major difference between these symbolic systems and language is the efficiency of communication: the efficiency would be discounted a lot if the participant in the communication share little common sense about visual or audio representation.

It is still interesting to apply the language features to music genre. We can imagine a baby who was born in a “music family”, in a band. His four older brothers had already played band for years, and the baby was born in a music atmosphere, which seems like a natural setting just like English language. You are allowed to play bass with the experienced music language speakers. Are you going to become a native music language speaker as well? Probably the answer is YES according to Victor Wooten. In his TED speech, he narrated his story of learning English and music at the same time, in the same way. It seems that it is possible to make the analogy between language and music as long as the natural setting of English and music are almost the same. You are not going to learn bass by enrolling into entry level class; you just play with it. You are not going to be taught English; you just say it. The special experience of Victor suggests the possibility of applying the language features to music genre, but also indicates the importance of social collective cognition of one cognitive system.

Reference:

The discussion of meaning-making reminds me of a game called Pictionary. Pictionary is a guessing word game played with teams with players trying to identify specific words from their teammates’ drawings. The definition of Pictionary addresses several key texts discussed in the readings. First, the symbolic cognition process is accomplished or implemented via two different sign-systems: language and image. Second, there are several cognition processes happening simultaneously – expressing, representing, interpreting goes back and forth between “describer” (the drawing player) and “decoder” (the guessing player). To complete the communication circus between teammates, players usually experience the following steps:

1. Describers get to know the object that they are going to describe, which is represented by written format;
2. Describers draw pictures to describe or represent the object;
3. Decoders watch the drawing process;
4. Decoders tell what they think the object being described is;
5. Repeat Step2 through Step4, until decoders get the correct answer.

These steps are observable. For describers, the word card that represents the object is an input, and what describers draw is an output. The process converting the written word into drawing can be roughly considered as a symbolic cognition process. For decoders, the drawn image is an input, and the spoken word that decoders use to represent what they think the object is is an output. The process converting the image they perceive into human speech is also considered as symbolic cognition.

However, the “converting” process is still a black box. As indicated in the reading: “how meaning happens – how we make, communicate, or “intend” meaning – when we use symbols, signs, and representations is unobservable.” True, what we can tell is the stage we are at, which is static; but we cannot tell is what’s going on, which is dynamic.

To clarify “what is in the black box”, researchers attempt to “build out models to account for what we can observe”. These models are testable, and open to revision and redefinition. Two models are discussed in the readings.

One model was developed by De Saussure. He pointed out that the meaning relation between signifier and signified is dyadic and static. In Saussure’s opinion, the relation between signified (the concept) and the signifier (sound-image) is arbitrary. Yes, the arbitrary principle indicates that there is no natural connection between signifier and signified. No natural connection indicates nowadays established rules of language is the result of social norm or collective habit. This inference leads to another conclusion that the establishment of the connection is a dynamic process (because the socialization is a dynamic process). The relationship doesn’t “born to be like this”. Saussure didn’t realize the dynamic relation between signifier and signified, therefore failed to explain the institutionalization process within a specific community.

Another model was developed by Peirce, who maintained that the meaning relation must be triadic and dynamic. The primary difference between two models is the newly introduced concept: Interpretant. It is this concept that explains the dynamic meaning relationship between signified and signifier. I am wondering is it possible to present the relationship between these two model as follow:

Signifier = Representatum (?)

Signified = Object + Interpretant (?)

It is Interpretant that enables “unlimited semiosis”. According to Peirce, Representatum is the material-perceptible forms of sign, which “equals” the “signifier” in Saussure’s model; Object is what the signs are “used to be” about, and Interpretant is the instant response to the signs – Object and Interpretant consist of the “Signified”. The behavior of Interpretant assumes the existence of recipient. It is recipient that differentiate the meaning of the object from the object itself. Representatum is only an “imitation” of the object, without the Interpretant, the dynamic process cannot continue. At the same time, the Interpretant can be perceived as a new Representatum, which triggers the infinite generation of Interpretants.

Take Pictionary game as example. There is a word “chocolate chip cookie” on the word card. The written word is a perceptible form of the concept “chocolate chip cookie”. For describers, they are the recipient and they are going to interpret the concept – at this moment, what in their mind is a Interpretant, something that is different from but infinitely close to the original concept (which is represented by the written word). Now, the first round of sign process ends up. The second round begins when describers start drawing. They are not recipient but “representer”. At the same time, the Interpretant in their mind becomes an original concept now, and the images drawn by the describers is the Representamen in the second round. The recipient of the Representamen is the decoder, and decoder is responsible for “interpreting” – again what decoders interpret is different from what they originally perceived. When decoders start to guess what the images represent for, the third round starts. It is the first effort of decoders to establish direct connection between the concept indicated by the word card and what they interpret. In the third round, what decoders inference from the image becomes the Representatum of the most original concept. It is a reconfirmation between the meaning and the concept. If the connection fails (in this context), then describers and decoders will repeat the second round and third round to “correct” their perception of the Representatum for them respectively. The process will not stop until the success of “confirmation”.

The Pictionary game is an “embodiment” of what we are experiencing in our daily interaction and communication. It enhance the feeling of that “We Are Symbolic Species”. In the game, we are seeking for the match between symbols and meanings, and we are continuously question the statement that “Are we on the same page?” The only difference between the game and real life is that we are not going to spare much time confirming whether we are on the same page. This feeling are attenuated, but it doesn’t indicate the absence of the sign process and the trouble brought by the sign process. We are fortunate to cultivate something called “Culture”. Culture has enabled us to share common ground to some extent, but it is culture, again, that creates gap between people. You never know the Representatum (a circle with triangle shapes on it) of the phrase “chocolate chip cookie” can be interpreted as something about quantum.

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