It was so interesting going through what we could call the history of computing. Through understanding the importance of semiotics and symbols one can see the true origin of computing. I think we often times forget the connection of the modern world with the past in terms of truly conceptualising the fact that all dots connect to the present and current “status” of how things are. In the initial weeks we further delved into the meaning and representation of symbols in human beings (“the symbolic species”) that allowed for certain behavioural, cultural and neurological characteristics to form and over time adapt to the specific moment of time and develop along with it. 

Through 

In this course, I learned a lot of new things. In the beginning, we learned semiotics, semiotic thinking, Peirce’s semiotic theory, signs, and symbols. In this part, it is exciting to know the relation between signs/symbols and meaning: signs/symbols are interpretable only in a socially understood context of use. It means that meaning is not a fixed entity; it is a relation, making me rethink the symbols and signs and realize they have significant power in our lives. To be honest, I never take symbols seriously before taking this course. My understanding of signs or symbols is the “stop” sign or the “apple” sign.

Then we talked about the language, that is my favorite part. Language to humans is an intricate talent: humans have an inborn ability and tendency to speak. For example, children are born with universal grammar. It contains the common characteristic of all human languages. When a kid is young, even with poor input, he or she can learn a language quickly. Because there is a syntax rule under the language, children can recombine the words to form unlimited sentences with this rule in their brains. This ability disappeared when they grow up. That theory is astonishing; when I learned this, I regretted that I studied English too late.

Next, we learned electricity and binary code. When I did the reading, I wrote down a quota which is very impressive to me: “We didn’t create electricity, we design it.” when we are using 0/1 to represent the state of the electricity, we map the abstract symbols to the physical thing (electricity). With 0 and 1, we can represent anything in the computer system, such as numbers, words, and images. The computer only can run the binary code to execute actions. For languages such as C++, Python, or Java, the target audiences are humans, not computers. Now I realize the importance of symbols and abstraction. I feel the previous materials we learned are like a foundation for now. We also do some practical practice this semester. I tried HTML and python that are brand new experiences for me.

Studying semantics can better analyze the rules of using human language, which is beneficial to the realization of artificial intelligence. Besides, when we delve into these language rules, we are more likely to design more advanced translation software. Microsoft has added a real-time translation function to Skype. Google also has a camera real-time translation function, but at the current level, especially the translation between Chinese and European languages has many problems.
And I think it is also beneficial in artificial intelligence conversation. There is an AI dating experiment recently. The developer allowed two virtual AI characters to communicate in the same space for four days. The two AIs come from different companies. Through the dialogue between the two AIs, it can be found that AI’s use of language and rules cannot reach the human level.

I really appreciate professor Irvin and this course. It brings basic but essential knowledge behind computation, so we can understand why and how a computer works in this way, filling the gap between theory and actual programming.

My main learning achievements of the semester so far have been:

1. General understanding/introduction to concepts that create the meaning of code and the history thereof
2. Deblackboxing of some coding languages (e.g. HTML, CSS, Python)
3. History of computing and how technology has advanced
4. How and why programming languages are designed the way they are
5. Basic understanding of methods and concepts from a variety of fields that feed off of computing (e.g. design thinking, systems thinking, semiotics, cognitive science, etc.)

The class has covered many topics within the field of computing and the meaning of code, but what I found most rewarding was relating the technical concepts to those of human representation concepts. It’s interesting to humanize computing in that way: as a reflection of human thought processes, which in fact it is. While diving into how computing has progressed as a field (seeing the image of the computer Professor Irvine wrote his thesis on) to the modern computers we use today (or at least what we consider modern in 2020), it’s clear that the core purpose of computing has remained the same. Computing is in a way an extension of the human brain; it stores information (cognitive off-loading), performs calculations, and retrieves and processes information – all in a more efficient and often times more reliable way than humans. Computing is responsible for much of why humans have become such advanced animals. What has differed since the conception of the first Turing machine was invented is the increased efficiency at which processes occur and the increased set of capabilities that a computer can complete.

In recent weeks we have moved on to discuss artificial intelligence (and even viewed a video of a robot communicate independently in an interview without direct instruction) and the ways in which this will further advance our notion of computing. We are teaching computers to think for themselves. It’s a strange and interesting new landscape for the information that humans will have access to.

At CCT I would like to continue to develop on our AI learnings and conduct research on the ethics and responsible implementation of AI in our society. There is an interesting field of research that covers the intersection of artificial intelligence and societal impact that continues quickly evolves as technology continues to advance. Some of the larger big tech firms and some smaller foundations are conducting extremely interesting research on this topic:

1. Google’s PAIR group: https://research.google/teams/brain/pair/
2. Facebook’s FAIR group: https://ai.facebook.com/
3. Microsoft’s FATE group: https://www.microsoft.com/en-us/research/theme/fate/
4. AI Foundation: https://aifoundation.com/
5. Center for Humane Technology: https://www.humanetech.com/
6. AI Now Institute: https://ainowinstitute.org/

The intersection between societal impact and emerging tech that is growing today is especially interesting because it almost represents a full circle effect of the history of technological development that we have discussed in class. Computing was once developed to enhance human capability and, while that still is the goal today, it has strayed away slightly to over-saturating its capabilities to few large corporations. Responsible AI brings the goals of computing (and emerging tech more broadly) back to the masses of people it aims to serve.

Professor Irvine’s course has taken us through how computer systems and digital information is based on basic human symbolic capabilities, taught us a basic level of programming, and helped us apply that knowledge to being the middle man between the technically-leaning and non-technically-leaning fields – a, too often, overlooked importance in any field.

So far, we have deblackboxed so many things around computation and computer. I now have the basic understandings about not just the hardware of computer construction, but also about how programs are executed  inside the computer memory system. I have tried basic programming using python and therefore deepen my knowledge of how program is wrote and the logic relations behind each line of code.

I also learned how to view computation and technology in a brand new perspective. By combining symbolic culture and human cognition knowledge, I now understand what is code, why are human-machine interface and peripherals designed like this, how do we connect natural language to program language…

All above and so many other definitions I have not mentioned are something new for me. Interestingly, this semester, I am also taking Prof. Turner’s Communication Theories class, which we learn about interpersonal communication theories and applications, and Prof. Zalman’s Foresight Method, which we examine signs and trends of our lives that can lead to future change and impact.  These two courses also focus a lot on technology — how technology impacts human relations, our behaviors and future. I feel like these three classes are all connected: symbols & technologies. 

I am very interested in how people implying symbols to machines and in turn, some of the original symbols are reconstructed in their meanings level. I wonder if I can apply what I have learned in this class to human behavior studies. 

Detailing the discoveries I made this semester, through a multitude of lenses has been enriching and ameliorated my understanding of Computing and the Meaning of Code.

To break down the frameworks of how code has affectively enhanced the progression of computing has been a fascinating journey as we worked through the complex, abstract blackboxes of code. As we gained a deeper understanding we were able to conceptualize how understanding semiotics and syntax at a novice level, helps understand computer science better.

Through the course work, we kept finding ourselves amused with how closely knit the subject areas of linguistics are involved in being able to communicate with our computers through code. We gained a deeper understanding of how natural language processing works on a human-to-human level and how this inadvertently overtime, was something that could be used with not only something not considered a being but a machine.

The continuum of human symbolic capacity is broken down with language being the heart of the symbolic capacity, abstraction, mathematics, computation, and software. Further, we delve into the theory of symbolic systems and technology in introducing Semitic theory. Throughout history, we are met with abstractions of art and symbols to be interpreted as a code signaling for humans to understand. Whether it was for aesthetic purposes and pleasure or for informing another, it holds significant value in what we are capable of creating through just symbols.

Humans are able to understand and interpret hundreds and thousands of symbols. For a computer to understand symbols immediately is a great deal to ask of it. Therefore, an advanced system of binary code is designed at the foundations of code to better communicate with computers. Through binary,  1’s and 0’s are used; as on and off switches. The computer interprets symbols through true and false negatives. Therefore, leaving computing at its most unostentatious form in two switches as the variables are used as instructions. The information is transmitted to the computer which is called a bit. Binary is necessary for any aspect of computing to function. Everything we see on our digital interfaces is a complex system of binary code that has been amalgamated together and used as information surrogates, transferring data into the system.

Professor Irvine hones on the essential tools embedded in modern computing and states it as “the crucial prerequisite for the use technology to computing…the development of notation, or language systems, sufficiently comprehensive to satisfy both the need for representation and the need to express and implement mechanisms for the transformation of expressions in the language”.

Progressing further into the abstract parallels of computing. The nativity of the internet and Web lies on the segments assessed above. Networked data and “multimedia” interfaces represent cognitive ability to build and comprehend. This is where natural language, to semiotics and symbols, binary code, tie together in how this is conducted. The most basic interface is HTML, CSS, and JavaScript. Through these computation forms of “programming”, this is used as the platform to cascade and convert binary code to something we can easily understand rather than shifting between multiple languages, and the conventional languages we speak but to understand the digital processes. With these basic steps, the design principles have been enabled, seamlessly transferring data through the servers. The metadata and data are supplied through these domains making the web interfaces so that we can comprehend the symbols and images with ease. These operations are mitigated through a multitude of commands within the system. 

The first half of this course was especially gripping, as it was my first exposure to any linguistics literature. To see what originally seemed very random and different subjects come together so closely knitted were key concepts of computing I would not have understood otherwise. While it felt like “jargon”, my coding experience has been enhanced as I understand more fully the nativity of how code works and not just plugging and chugging the system and taking for granted that these terminals are there by chance. 

 

Irvine, Martin. Important Steps in the History of Ideas about Symbols and Computing. 

Part One

Major Learning Achievements & New Knowledge

• Basic knowledge of semiotics
• Human symbolic cognition & symbolic representation
• The essence of nature languages and a brief history of symbol evolvement
• Basic history of computer science and how it related to human symbolic cognition
• How computer works and why it works in that way
• Operation principle of “programming”
• Basic knowledge of HTML, CSS, JavaScript and Python

 

 

Part Two

Discoveries

【How we turn into this?】

Before I learned this course, the development of computer seems like a mystery for me. As someone with a great interest in zoology, I have always been curious about how to define the boundaries between humans and other animals, and how homo sapiens evolved from the poor omnivorous mammals to what we are now. If a person uses a time machine to travel from Han Dynasty (206 BC – 220 AD) to Ming Dynasty (1368 – 1644), he might struck by the splendor of the Ming Dynasty and some of its novel designs and civic activities. But if he travels from late Qing Dynasty (1901 – 1912) to now, that will be MIND-BLOWING! He might be deranged~

How did we come out of our caves to build city-states, and how did we move from the age of monarchs to the age of information and globalization?

The answers of these questions are in the black-box before.

I feel the readings of semiotics and nature language in the course shed a light on these black-boxes. I can’t say they solve all my confusion, but they provide a terrific approach to think about our human development. Our progress towards the information age began when our ancestors began to paint on the rock walls and carve symbols on the stones. We add layer after layer of abstraction from generation to generation, and with the development of engineering, the computer comes out!

【Our ability of learning language is a superpower! 】

It’s hard to realize that language is actually a part of symbolic representation, and also, hard to realize that the complexity of nature languages is a superpower of human beings. That is because we live with language everyday since we born, we just take that for granted. It’s hard for us to see the inherent connection between language (or let’s say, symbolic system) to computer development.

I was shocked when I learn how human babies deal with language information and weave the information in their little brain to create new expressions. I still feel that part is a miracle.

【Programming】

Punch cards and punch tap, the important component of programming in early age. After I learned how programming evolve from physical things to codes, programmers didn’t look like magicians anymore. And thanks for all the efforts our predecessors made, we can just type in symbols belong to human cognition community to communicate with machine is all because of their hard work on UNICODE, complier and high level languages.

 

So basically: [BEFORE] Everything is cool and mysterious [NOW] Everything is cool but reasonable!

 

 

Part Three

How the methods, key concepts and approaches that we have used will apply to other topics, disciplines, or courses that you want to study in CCT

【Web Development】

This semester I also take a course called Creative Web Development (by Professor Undeen). In this course I have to learn HTML, CSS, JavaScript and also JS libraries like jQuery. But it confused me at the beginning that who am I writing these codes for? And the most essential one, why browser can understand the English I write? These questions are slowly being answered in the study process of Computation and Meaning of Code. This helped me to build confidence on code learning, and now I found coding is quite interesting, not a barrier impossible to overcome. So I might try to learn some Python next semester.

【Communication and UX Design】

Before came to CCT, I was a graphic designer in a Shanghai company. I really had issues with our web developers since I don’t know what is they can do and what is they can’t, or what is difficult what is easy. Now, with an overview of computer science and understanding of many terminologies, I believe I could communicate with them in better way. One of the CCT learning goal is to help students to be a bridge between technical and non-technical staff, I think that’s exactly what is course is for.

【Art】

Without any knowledge of art, I have to say most of the time I could not understand what all those art works are for, especially modern arts. I love David Hockney’s swimming pool, love Dali’s dream-like painting, Edward Hopper’s city life, Georgia O’Keeffe’s flower, but I don’t really get the beauty or meaning of Andy Warhol, Mondrian, Henri Matisse and etc.Their works look so simple. Are they just fish for fame? And more importantly, why some people are willing to pay so much money for art? What can art do?

But semiotics really, really change my view of art. Painting on the rock wall is the start of art, the start of symbol using, the start of language and everything related to human symbolic cognition. The letters in English, or the characters in Chinese are fixed form of art work (not that fixed maybe, we still have calligraphy art). Now I feel that art is like an extension of our primitive ability. We use our creativity to create different symbols, express emotions with colors, and express rhythm with lines. I want to quote Mr. Keating from the film Dead Poet Society:

We don’t read and write poetry because it’s cute. We read and write poetry because we are members of the human race. And the human race is filled with passion. And medicine, law, business, engineering, these are noble pursuits and necessary to sustain life. But poetry, beauty, romance, love, these are what we stay alive for. To quote from Whitman, “O me! O life!… of the questions of these recurring; of the endless trains of the faithless… of cities filled with the foolish; what good amid these, O me, O life?” Answer. That you are here – that life exists, and identity; that the powerful play goes on and you may contribute a verse. That the powerful play *goes on* and you may contribute a verse. What will your verse be? 

He is talking about the poetry, also a form of art, and I believe his words apply to any kind of art. These are what distinguished us from other animals.

Many art works always look abstract is because symbols are on many layers of abstraction. They look simple might just because audiences usually take everything for granted.

Combined with digital technology, art now has more forms of expression. Among them, I am particularly attracted by Net Art, and I hope to research further in this field.