Author Archives: Lauren Neville

Perice’s Semiotics and Environmental Education



This paper argues for an enhanced education design in Peirce’s theoretical work on semiotics for those working in environmental conservation initiatives. In light of the recent environmental and climate crisis, our communities are faced with a myriad of complex innovation challenges. The environmental crisis is weaved into faulted economic, technological, and social systems, which lack an understanding and foresight of our impacts on the surrounding ecosystem. A true paradigm shift is needed in environmental science and management, which is both collaborative and complex. Peirce’s work in semiotics values the complex and collaborative understandings of mapping and sharing knowledge on our universe. This paper takes the specific field of cartography as a case study for the argument. Particularly, the principles of semiotics should be applied to the use of new interactive maps such as Google Earth Maps.


“A sign is something by knowing which we know something more. The whole universe is perfused with signs,” said C.S. Peirce. Being that the whole universe is perfused with signs, it is not unusual that humans have been dedicating themselves to depicting the surrounding universe into a symbol form for thousands upon thousands of years through mapping. The complex academic work of C.S. Peirce has led to advanced work in languages, syntax, and computational work as it has enlightened the field of semiotics and provided a base for symbolic theory. As a polymath, Peirce drew connections between logic, math, and linguistics. Notably, he was also a cartographer and is known for creating the quincuncial map. His work hightlights the complex nature of our cultural connections and notes that the study of signs is in many ways the study of relationships between individuals, culture, sign vehicles, time, and the surrounding the environment. It is this focus on the complex networks of understanding that leads one to see parallels in his work with the future of environmental science, map-making, and ecological knowledge.

Throughout history, maps have been used as a symbolic meaning-making system to understand and communicate a shared environment. Maps are persuasive, political, scientific, and explanatory. Humans have culturally evolved throughout time because of our abilities to interact with representations of reality rather than true reality. Maps have allowed people to symbolically render their surrounding environments to make documentations, future plans, and share information to others in the community.

“Peirce discovered that the human social-cognitive use of signs and symbols in everything from language and mathematics to scientific instruments, images, and cultural expression provides a unifying base for understanding meaning, knowledge, learning, and what we call “progress” in developments in both sciences and arts,” (Irvine). I would propose that these principles are being largely ignored in today’s environmental movement as ecological scientists have been unable to have the resources to properly communicate environmental knowledge.

Peirce’s semiotic principals should be more widely distributed as a means for the environmental paradigm shift to begin. The affordances of Google Earth’s Web 2.0 software allows for the potential greatest cartographic collaboration in history. Google Earth attempts to subvert traditional power structures through the use of interface and an demonstrated understanding of the semiotics of maps. Peirce’s theories on semiotics can and should be applied to our analysis of interactive design in Google Earth.

Peirce Introduction

C.S. Peirce’s lifeworks revolved around the process of meaning-making and knowledge as a generative process. With every symbolic experience, one experiences a process of combinatorial information processing. “A sign that by knowing something by which you know more said Peirce. He developed an understanding of the meaning-making process as a triadic experience. This process in explained through Martin Irvine’s evaluation, “A Sign, or Representamen, is a First which stands in such a genuine triadic relation to a Second, called its Object [an Object of thought], as to be capable of determining a Third, called its Interpretant, to assume the same triadic relation to its Object in which it stands itself to the same Object,” (Irvine).

Peirce expanded this notion by defining multiple different types of signs and categorizing them under icon, indexes, and symbols. Icons were defined by Peirce as, “a mere community in some quality.” Put simply, the sign would share a quality with what it was signifying and also called likenesses. Indexes were “whose relation to their objects consists in a correspondence in fact” and this indexical aspect would point in a way to the true thing it was representing. Finally, symbols were those “whose relation to their objects is an imputed character” which had general or conventional connections to the object, (Stanford).

Peirce Cartography

C.S. Peirce begins his essay A Quincuncial Projection of the Sphere, “For meteorological, magnetological and other purposes, it is convenient to
have a projection of the sphere which shall show the connection of all parts
of the surface.” In this essay, Peirce further explains his projection “is formed by transforming the stereographic projection, with a pole at infinity, by means of an elliptic function.” This map places the north and south poles as single points that are then radiated out from with mathematical precision. The map uses squares of varying sized scales from his formula to create the highly accurate spatial rendering of the sphere on the map, (Peirce).

His theoretical work was based around the logic problem of representation, which linked his interests in mapping, imaging, language, and mathematics. With his fascination in geographical mapping, he pondered the regressive element in continuity of the map image itself. He wrote,

“If a map of the entire globe was made on a sufficiently large scale, and out of doors, the map itself would be shown upon the map, and upon that image would be seen the map of the map, and so on indefinitely. If the map were to cover the entire globe, it would be an image of nothing but itself, where each point would be imaged by some other point, itself imaged by a third, etc. But a map of the heavens does not show itself at all,” (Carolyn, 300).

He often noted his own quincuncial projection map as being superior to the standard map of the time as he stated, “a Mercator’s projection shows the entire globe (except the poles) over and over again in endlessly recurring strips.” He continued, “many maps, if they were completed, would show two or more different places on the earth at each point of the map (or at any rate on a part of it), like one map drawn upon another.” His quincuncial projection map is analyzed by Pierpont as “representing one-to-one correspondence of the interior of a square by the interior of a circle of unit radius about the origin on the plane of the stereographic projection,” (Carolyn).

Peirce’s quincuncial projection map was successful as the U. S. Coast and Geodetic Survey recently published its principals while working on a major international plane air routes. Due to the accuracy of his map, the air routes are shown with the least distortion of any other map and in most situations are depicted as straight lines. This aids in understanding the true angles of intersection for air traffic as opposed to Mercator or the stereographic projections (Carolyn,307). This work is further built upon in digital mapping such as Google Earth Maps. While interacting with Google maps, users experience satellite rendered images that are overlaid into appropriately sized squares. These image overlays continue into smaller and smaller squares in conjunction with earth’s longitude and latitude coordinates.


Cartography and Semiotics

            Beyond his work on the quincuncial projection, all of Peirce’s semiotic work has stood as a platform for others studying the sign systems within cartography in both politics and sciences. Geographic Information Systems (GIS) have created a new phenomenon in cartography as the digitization and high information based renderings of the environment has dramatically changed the work of many fields of science. Due to the increase of use and influence of such systems, it is imperative that the new users understand the fundamentals and traditional representative capabilities of cartography.

As users begin to gain an understanding of the ways in which maps have traditionally represented space, time, and other natural phenomena through expressive communicative powers, they are then aware of their own role in the semiotic process. Their meaning-making literacy goes through a meta-experience of not simply knowing what a sign stands for, but also being cogitatively aware of that process through interpretation. I would argue that this education could vastly increase political engagement and empowerment.

Ferdinand De Saussure discusses the recognition of two dimensions of meaning – the context-free and the socio-cultural value. This distinction is crucial for understanding any system of symbols that we come across. In the context of the complex meaning systems of maps, I found that socio-cultural value is key. Mapping is valued as a specific social sharing device, but in the case of GIS technology within environmental science, most citizens have no socio-cultural understanding of these maps because they lack relevant symbolic meaning. This socio-cultural component is, in many ways, a missing link in the sphere of environmental messaging. This missing link can be traced back to understanding symbols in a messaging language form. While each map acts the same in what Peirce would call its material-perceptible form, we as a collective then have the initial learned associations. However, in the triadic form, the response formed by such a map was only held within my own personal experience.

Our cumulative experiences with maps have changed throughout time simply based on our ability to change between the three basic classes of signs from icons, indexes, and symbols because of our abilities to capture the surrounding universe in different symbolic forms. While hand drawn historical maps are known for their geographical inaccuracies, we now use satellite and photo imagery to gain precise details of the planet and surrounding universe. However, it is important to remember these new and highly accurate depictions of the universe are still symbols of instances in time.

“These models are mash-ups of the iconic, indexical, and symbolic—none of which the interface makes clear, until one considers another element of the Peircian model of semiotics: that all signs must have an interprétant: an agentive, cognitive frame for reference,” writes Helmreich, (1226). In the case of Google Earth, we have a conglomerate of images and data collected by Google camera missions, satellites. publicly shared initiatives like data from environmental or oceanographic research studies, or the everyday citizen. It is here that we can see that see that systems of meaning can pre-shape what will count as a sign.

These interpretants are tools of use that have cultural influence. Helmrich futhers analyzes the role of semiotics in the Google Ocean application within the Google Earth application. He writes, “Artifacts in the data reveal some of the assumptions built into the human and machine intepretant ecology. The image of the real, filtered through the model, indexes its social and institutional conditions of possibility, underscoring the way that systems of meaning can pre-shape what will count as a sign,” (1226).


A simple example for Google Earth is the blurring of images over the government security areas or the on going security debate between countries like China and Saudi Arabia and Google. While icons, indexes and symbols are perfused across the Google Earth platform, there are interpretant experiences that already craft what type of icons, indexes, and signs the individual interpretant has access to view, (Helmreich, 1226).

This interpretant holds an immense amount of power. To further expand upon the role of the interpretant in maps and in particular Google Earth Maps, we can look at the political acknowledgements of sovereign nation-states written and highlighted on the map. These maps are not simply satellite images taken of the planet, but highly edited and stylized renderings of the world we politically associate with.

“What we have learned from Saussure is that, taken singly, signs do not signify anything, and that each one of them does not so much express a meaning as mark a divergence of meaning between itself and other signs,” (Wood and Fels, 95). In this sense, signs allow for systems of relationships to exist through the creation of distinct working parts. In this sense we are faced with understanding the nature of systems of complexity in meaning-making systems. Wood and Fels explain this as, “what the map does (and this is its most important internal sign function) is permit systems to open and maintain a dialogue with one another,” (96). Maps form a complex systems through the distinction of these varying signs in a spatial representation of the relationships they have to one another. These distinct working parts operate interdependently acting as individual components, but also creating a hierarchal and combinatorial sign that is the map itself.

They continue that “There is nothing in the map that fails to signify,” (96). Each symbol for a river, political border, mountain is acted upon by the others. Even if there was to be a blank space left on a map, that blank space is relationally interacting with the other pieces and therefore symbolizes something. In my Fijian map example, we see just lines mostly distinguishing land from ocean. In the absence of line exist one or the other as we create the spatial representations of our universe.

Overview of Google Earth Interfaces

Google Earth provides an abundance of information for users in a variety of interfaces. It was originally only accessible via desktop but as of 2008 began to be used as a mobile app for iOS and Android. The mobile ability created a new future for Google Earth as its geolocation technologies were now used in a Web 2.0 format with mobile users producing an incredibly new amount of data. On the mobile version as well as the iPad and i-touch, Google Earth uses the multi-touch interface to explore the globe and other Google Earth spaces. The multi-touch allows for zooming and moving throughout the mapping system. It also allows for the use of the iPhone Assisted GPS to aid in crowdsourcing data.

The dependencies that must be in place for such a technology evolved from the evolution of remote sensing technology with the ability of satellites to collect data on the dimensions of earth objects below. This data is rendered into image format. This technology can be traced back to earlier remote sensing technologies combining from airplane companies such as Boeing. Google Earth users actively participate in the creation of Google Earth through taking pictures on mobile devices and also using the SketchUp software for 3D modeling. The whole program uses software to superimpose images onto the same mapping system that is interactive. The imagery is updated to higher pixels as satellite and remote sensing technologies are updated and more participants engage with the 3D rendering software, (Google Earth).

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Through the use of these interfaces, users come into contact with a varied collection of icons, indexes, and symbols. The likeness or icons are directly implemented through a number of interactive features including adding photography to street view. As users begin to create and formulate important locations on the map, they are able to make place-makers with descriptions and names in an indexical fashion. Finally, users are interacting with the varying sized squares of image information to better understand space and relational distance as the map acts as an entire symbol meaning-making system constantly creating generative cycles as each piece of symbolic representation interacts relationally with each other adding more and more meaning to each piece as other pieces are added and relationally observed.

Google Earth and Environmentalism

Every year, Google hosts the “Geo for Good” conference in which they discuss their goals as a company partnering with city planners and conservation organizations as a way to have their technologies such as Google Earth used for aiding projects for health and the environment. This partnership gives both Google and these NGO’s positive public support. Google Maps and Earth ended up beating out the competition of Map-quest and other’s such as Microsoft and Yahoo by making a bold move. Google avoided advertisements on the site and instead slowly integrated local businesses into their mapping, provided information about the business, gave indoor imaging to some, and fulfilled these partnerships through Google Business, (Geo for Good).

Distributed agency is given by those that use this technology as substantial amounts of scientists have begun employing Google Earth technology. However, the use of the mapping system is mainly for communication and cause marketing rather than scientific analysis. Because of this, conservation organizations have begun employing the technology in their campaigns. These organizations include the Jane Goodall Institute which provide digital mapping and ecosystem management visuals for potential donors and communities in areas of conservation. Beyond these NGO’s, we see that Google Earth has components such as offering traffic data thanks to crowdsourcing (The Jane Goodall Institute).

Affordances of Web 2.0

Manovich’s example of Google Earth as a Web 2.0 software opened my thoughts about our perceptions of globalization, computer technology, and the physical nature of our planet, (37). Never before has the physical space of our planet been so heavily monitored and documented nor have we had the capacity to use software as a precomputation with Google Earth users as distributed cognition. If societal advancement comes from our exceptional symbolic ability to offload cognitive memory, emotion, and logic into forms for reuse and distribution, the potential of computer technology in the form of Web 2.0 as a source of data monitoring in geography and planetary change seems infinite. As I continue to learn about technology for conservation, I am curious how to best design software for “precomputation” of environmental data and how to best use the internet for “distributed cognition.”

The use of Google Earth and other conservation technology tools are beginning to be broadly distributed by technology companies through non-profits. Using design principles to simplify products such as Android tablets, Google has been able to cross language, cultural, and educational borders to provide services and employment options to communities deeply affected by deforestation or other environmental hazards. These products have been specifically given to local communities in the Democratic Republic of the Congo working on primate monitoring. If the design of these products allowed such technologies to remain “blackboxed” and mystical, such institutions as the Jane Goodall Institute would be unable to access these technologies for research purposes. Through proper training of the user, these technologies are de-blackboxed into simple experiences that allow for efficiency. This user-interface design model is the key to de-blackboxing and distributing these cognitive artifacts globally (The Jane Goodall Institute).

On a more scientific note, field data scientists are able to track the range of species and create ecological niche maps based on population densities and sprawl of the species. This saves scientists an incredible amount of time in the field and allows for data collection and visualization to be collected directly on the computer for further study. Often, this visual data is used for forest monitoring and even carbon credit analysis.

Furthermore, this visualization allows for conservation organizations such as Earthwatch Expeditions to explore citizen science projects and educational sessions within classrooms. This organization uses Google Earth to reach a wide range of individuals by placing markers on participants’ local Google Earth maps that explain an ecological issue facing their environment. It then gives information about how the citizen can collect simple data or pictures of the area for scientists looking to build their research, (The Jane Goodall Institute).

One of the grand affordances of Google Earth Maps is the Web 2.0 functionality and “Google Earth Community.” The program allows citizen participants to engage in the social network of the Google Maps by making placemakers and contributing to central community knowledge of certain locations. Of course, this function does need to be monitored as any one can contribute individual knowledge that may be false or inaccurate to the local cultural standards. One such example is individuals have be observed placing false business locations in an attempt to boost advertising. However, this function is mostly used appropriately. Community members can even create overlays which can provide augmentations of their local street view or even storm paths.

Increased Semiotic Education in Environmental Projects

“We are able to store and forward symbolic thought from one generation to many others. Enabling a cumulative cultural ‘ratchet effect’ also known as ‘progress,’” (Irvine). This storage through time allows for the cumulative process in which all symbol systems evolve including maps that are known to hold the knowledge of geographical landmarks, political boundaries, and pathways to resources. The knowledge within these maps are also made from societal needs and created from the knowledge of many members of communities. They are created to be referenced over and shared throughout time while still holding the knowledge of a time in which they were created.

If we are to hope for any sort of amelioration for the environmental crises, we must employ this type of thinking into our environmental management and mapping projects. As there has been a movement towards creating distributed cognition in environmentally threatened sites through citizen-engaged projects. As the realm of environmental science is reaching out and engaging with those not trained in some of the symbolism, icons, and indexes known to the niche group of environmental scientists in the area, it has become more important than ever to not simply teach meaning to contributing citizens, but also teach the project team and citizens the meaning-making frameworks. The semiotic work of C.S. Peirce is largely overlooked in active fields of environmental science, but as stated, Peirce is potentially one of the greatest minds in foundational scientific thought.

Overall, it is imperative that citizens contributing to the Google Earth Maps have had an education in Perice’s theories of semiotics. Through the dissemination of these concepts, citizens participating in citizen science initiatives through interacting and adding to Google Earth Maps can better involve themselves in the collective symbolic creation and interpretation of the signs and symbols of interactive digital mapping. With these principles, citizens and scientists can both be reflexive about their own patterns of understanding the cartographic information in front of them and progressive in their work to collect, interpret, and disseminate their own work.



Irvine, Martin. The grammar of meaning systems,: Sign systems, symbolic cognition, and semiotics.

Saussure, F. Course in General Linguistics. 1911-1916. English translation by Wade Baskin, 1959. Excerpts.

Manovich, Lev. Software Takes Command. New York: Bloomsbury Academic. 2013.

Stanford Encyclopedia of Philosophy. Peirce’s Theory of Signs. Stanford University. 2006.

Peirce, C.S., A Quincuncial Projection of the Sphere. American Journal of Mathematics. 1879.

Eisele, Carolyn. Charles S. Peirce and the Problem of Map-Projection. Proceedings of the American Philosophical Society. 1963.

Helmreich Stefan. From Spaceship Earth to Google Ocean: Planetary Icons, Indexes, and Infrastructures. Social Research. 2011.

Fels, John. Wood, Denis. Designs on signs. Myth and meaning in maps. North Carolina State Univeristy.

Google Earth. 2016.

Geo For Good. 2016

Pintea, Lillian. The Jane Goodall Institute. 2015.

Google Arts and Culture – Weaving A Fabric of Complexity and Moving Towards a Newly Curated Future – Lauren and Carson

The Meaning-making of Curation

To begin our understanding of the meaning-making process of curation we drew from Professor Irvine’s words on reproduction and creating “moments” of art. He writes, “It is the same with figures that in reproduction lose both their original significance as objects and their function (religious or other); we see them only as works of art and they bring home to us only their makers’ talent. We might almost call them not “works” but “moments” of art.” With this in mind, we found that we could illustrate a case study where individuals may study a single piece of art 200 times and compare that to those who take a collection of works of the era and study them in the cultural context of the era’s customs, politics, science and medicine. In this sense we gain an understanding of the complex cultural and artistic fabric that has been weaved over that timeline. As we view the Google Arts & Culture Project’s pieces, we see the zeitgeist of that time rather than one single piece. This is the art of curation. While we may lose some details in a single piece by focusing on these “moments” of art, we that we gain a much greater understanding of the moment by viewing its past influencers and future influences. With the creation of the Google Arts Project, however, we have the affordances of digital remediation to gain the details in individual pieces back. In a digital space, we are granted the ability to both see the larger cultural context and the individual details at the same time. Taking Pierce into consideration, we must remember that a piece of art is a sign vehicle and acts only as one part of the meaning-making process. The other components of the meaning-making process are the relationships between individuals, the vehicle, and past culture.



Understanding Complexity of the Remediation of Art

“Thanks to the rather specious unity imposed by photographic reproduction on a multiplicity of objects, ranging from the statue to the bas-relief, from bas-reliefs to seal-impressions, and from these to the plaques of the nomads, a “Babylonian style” seems to emerge as a real entity, not a mere classification— as something resembling, rather, the life-story of a great creator,” continues Professor Irvine. Grusin and Bolter describe remediation as creating a mosaic of the individual parts in a new platform. We see that the remediation process of photography and then subsequent digital layout and curation very much resembles the mosaic that Grusin and Bolter were referring to. In this space, the seemingly invisible relationships become far more tangible through the Google Arts & Culture Project. Museums have historically attempted to master the art of visually rendering these connections through curation. However, digitality offers far greater affordances in the art of linking and displaying complexity through the remediation process.  As Professor Irvine notes, through photography reproduction, a theme such as the “Babylonian style” or “Cubism” seems to emerge as a real entity rather than just a classification. This emergence is created not by simply one artistic piece, but by the interaction of many unsimple working parts creating a larger system. This system then demonstrates emergent properties not seen in the individual smaller entities. This is the definition of a complex system – a system that a cultural fabric is constantly working within but one we try to pull apart into simple parts and relationships in our search for meaning-making of the entire zeitgeist.



Museums as Meta Space

Museums themselves are meta. Places like the Louvre and the British Museum are cultural symbols filled with cultural symbols. Integrating the Google Art Project and these cultural symbols creates new levels of symbolism.

Multiple levels of symbolism:


Level One: A Piece of Work

The Rosetta Stone









Level Two: The Gallery or Museum the painting is housed in

The British Museum







Level Three: Google Arts & Culture







Level Four: Exploring the Icons with 360 Video

306 view of British Museum

Google Arts & Culture Interface

As a digital interface, the Google Arts & Culture Project is changing the nature of museum environments. Herbert Simon writes, “An artifact can be thought of as a meeting point—an “interface” in today’s terms—between an “inner” environment, the substance and organization of the artifact itself, and an “outer” environment, the surroundings in which it operates. If the inner environment is appropriate to the outer environment, or vice versa, the artifact will serve its purpose.” With this in mind, we analyzed the interface of the Google Arts & Culture Project and see that the project has immense potential. The freedom for personal exploration through photographic representations allows the viewer to study their topics of interest. The site also creates unique curations through movements like Dada and Pop to other themes such as Time or even Color Pallet. The “Art Adventures” create digitally rendered curated explorations into …..


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The Interactive Interface and Agency 

Reminds me of Conery when they talk about this:

“Clearly there must be some structure to the computation, otherwise one could claim any connection of random symbols a constituted state” (p.815).

There needs to be a reason for the output, in turn making it symbolic.

Wegner says, “The radical notion that interactive systems are more powerful problem-solving engines than algorithms is the basis for a new paradigm for computing technology built around the unifying concept of interaction”

This supports the agency embedded within the interface.


Morse only wanted what he thought would be important in his painting of the gallery. Is the Google Art Project the same? What exactly decides what shows up on the main interface? Is there agency within the interface or are there predetermined patterns that could skew the meaning making process?

The Future of Google Arts Project Interface Design

“Perhaps the most important role of the Google Art Project is to be a ‘‘platform,’’ as Michael Edson puts it, giving rise to new and surprising ways of interacting with collections,” writes Nancy Porter. She notes that Google’s Create a Collection is a very popular feature and in our exploration of the Google Arts & Culture Project, we found a link to “create your own curation.” However, this link was not active and the interface for this feature has not been created. Like Nancy Porter, we envisioned the great potential this project could have if the feature existed. We believe that the full affordances of digitality are not being utilized in this project. With the digital revolution, we have seen an emergent property of “making” as a digital research tool. The Google Art project attempts to allow you to take greater agency over your museum-like exploration through finding your own way through the site, but the exploration phase fails to allow you to curate your own experience. We have imagined a Google Art Project that allowed you to have an individual account attached to the site. Here, your artistic journey would begin and you would be allowed to make your own collections similar to interfaces like Spotify, Zotero, and Tumblr. These personal collections would then be shared publicly with others and could be compared and analyzed and there would be digital art curation gate keepers who would receive massive amounts of followers.


These personal curated collections would help us better understand our cultural meaning-making processes and the complexities of how we view symbolic and artistic movements while exploring ours and others’ collections. These collections act as hyper-distributed cognition in somewhat real-time and constantly changeable digital visual renderings of the seemingly invisible relationships between artifacts, individuals, and culture. Participants can also create “Art Adventures” using the simple motion effects used in the already highlighted “Art Adventures” like Vemeer’s Little Street. Acting as the ultimate gatekeeper, Google Arts & Culture could then pick certain curators or “Art Adventures” to be featured similar to the interface of Vimeo or Instagram.


These collections would allow the agency to be given back to the user that the interface had previously disrupted. The user would be able to curate and create their own patterns using the works provided that were particular to their own liking. Creating their own virtual gallery.



Martin Irvine, “From Samuel Morse to the Google Art Project: Metamedia, and Art Interfaces.”

National Gallery of Art, background on Samuel Morse’s painting, The Gallery of the Louvre.

Nancy Proctor, “The Google Art Project.” Curator: The Museum Journal, March 2, 2011.

Herbert A. Simon, The Sciences of the Artificial. Cambridge, MA: MIT Press, 1996. Excerpt (11 pp.).

Peter Wegner, “Why Interaction Is More Powerful Than Algorithms.” Communications of the ACM 40, no. 5 (May 1, 1997): 80–91.

Jay David Bolter and Richard Grusin, Remediation: Understanding New Media. Cambridge, MA: The MIT Press, 2000. Excerpts in 2 files: Introduction | Chapter 1.

A convergence with an open-ended future – Lauren Neville

Unexpectedly, I find myself facing existentialism at this time of reflection. As this is my second course with Professor Irvine and second year in CCT, I have noticed a sense of dramatic and unanticipated growth in my understanding of my own meaning systems. Last year, in Leading by Design I began further conceptualizing boolean logic, cognitive distribution, layers of abstraction, and architectures of complexity. However, our work in semiotics has changed even my perception of self and of the reality I had built.

Signs are not simply images or words, they are context filled relationships that we have with each other. We render a symbol as a culture and interpret the symbol as a culture and because of that we are ever-presently engaging in a network of complex relationships with each other. Our speech, art, written word are all predetermined and therefore, we share a constant distributed cognition. What I once perceived as my personal judgements of music have now been explained to me as the collection of past interactions and relationships I have had with other music from our culture.

Because signs and symbols act as networking nodes, it now makes sense to me that semiotics is the obvious path to computation. It seems that throughout time, we have been getting closer to this convergence and valued the shared cognition that could link many people and concepts into hub-like spaces. The early book wheels of the Renaissance, Babbage’s difference engine and Sutherland’s Sketch Pad are not simply tools, but act as symbolic meaning making hubs. It seems obvious now the most important part of this evolution was the Internet in which cognitive distribution through relational symbol systems could be shared at the speed of light. 

Of course, this convergence and finally the development of the Internet does not imply an end-all be-all to our progress in meaning making systems. On the contrary, we have just opened up many new doors for making and creating as the affordances of graphical user interface and interaction designs begin to allow our culture to discover and explore our fantastical symbolic renderings of the world far beyond what we could have anticipated. I believe that advanced mathematics, social networks and planetary systems can only now be explored because of our abilities to utilize billions of cultural relationships to make symbolic representations of our universe. As I noted in my first post in this course, we should contemplate C.S. Peirce’s statement, “A sign is something by knowing which we know something more. The whole universe is perfused with signs.”

Interfaces, Relationships, Symbols – Lauren Neville

This week I have grasped a much better understanding of the meaning behind interfaces and their evolution alongside digital computers. My understanding of the definition best came from Herbert Simon’s writings, “An artifact can be thought of as a meeting point—an “interface” in today’s terms—between an “inner” environment, the substance and organization of the artifact itself, and an “outer” environment, the surroundings in which it operates. If the inner environment is appropriate to the outer environment, or vice versa, the artifact will serve its purpose.” In this respect, I am able to understand an interface on a computer as more than simply graphics and instead as a substrate for conceptual organization. Interfaces also act as platforms allowing the mind to build these concepts through the interface design.

Engelbart wrote about the notion of interfaces in the form of filing systems. This is not a new system, but has acted effectively for thousands of years. Computation then allowed to tasks to happen faster and for information to take up less space. Because of this, the interface platform is both modeled after traditional filing systems as well as altered to utilize the affordances of computation. Written information on a computer is often stored on a document which resembles a piece of paper. Then that document is stored in file folders and are often organized alphabetically or by data. All of these interface systems are for humans to feel conceptually organized. Computers on the other hand, do not actually store written information in a folder, it stores it wherever it has space in the form of binary numbers.

Near the end of Augmenting Human Intellect, he writes, “The conceptual metaphors of interface and medium have deep roots. The philosopher-scientist and founder of semiotics, C. S. Peirce, defined a sign (and sign clusters) as a medium because sign structures enable cognitive agents to go beyond the physical and perceptible properties of representations to their interpretations (values, meanings), which are not physical properties of representations themselves. Perceptible (and remembered) representations only become signs when an agent supplies.”

This nod to Peirce has helped me make some of the conceptual leaps between semiotics, computation, and design. I am beginning to understand that each symbol we interact with is in fact a series of complex relationships to our knowledge of the past, our cultural standards, and our cognitive organization. The standard graphical user interface that is so often what comes to mind when one thinks of interfaces is actually a complex network of relationships to each other as well. Each of the sign vehicles on a computer screen make up a symbol system similar to our alphabet. The meanings behind them have deep roots in our analog system.

If we take the filing system example again, when we see a folder on our computer screen, it acts as an icon referencing a physical folder. What I am curious about is how many new symbol systems that are made on computers are not referencing analog experiences and culture. Because computational user interface is a fairly new field of symbol system making (30-40 years) as compared to the roots of the alphabet or filing library systems. I wonder if as time moves on interfaces and computational graphical user interface design will move more towards the creation of symbol standards.

Engelbart, “Augmenting Human Intellect: A Conceptual Framework.” First published, 1962. As reprinted in The New Media Reader, edited by Noah Wardrip-Fruin and Nick Montfort, 93–108. Cambridge, MA: The MIT Press, 2003.

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.

Programming, Language, Conditionals, and … Animals? Lauren

In Great Principles of Computing, Denning writes, “A programming language is a set of syntax rules describing a precise notation for each of the above structures.” It was important for me to realize that we communicate to computer in both a similar and different way than we communicate with others. While coding in Python and my previous experience with Python and Javascript, I came to realize the strict importance of syntax. Computers fail to understand a variety of contextual information if not already programmed with a library of understanding about that information. Therefore, you need to provide very strict gramatical patterns for the computer to make sense of your program.

This then means that computational thinking needs to happen as we are not speaking for another human. In Jeannette Wing’s Computational Thinking video and essay she notes, “The process of building a computational solution to a problem is fraught with errors, which can occur at any of the four keypoints: expressing intentions and desires accurately, programming accurately, compiling accurately, and executing accurately. Here: “accurate” means preserving the original intention of the designer.” This explanation helped me understand that beyond linguistic dimensions, Wing’s video statement that Computational Thinking and programming is clearly pulling from engineering and mathematical theory. Programming is building in strict fashion to execute something that needs to be interpreted in one way and one way only. In linguistics, the patterns can be rearranged and interpreted in an infinite amount of ways. In engineering, if the instructions and numbers can be interpreted in more than one way, human error and miscommunication can cause rockets to explode.

Wing goes on to explain, “Computational thinking involves solving problems, designing systems, and understanding human behavior, by drawing on the concepts fundamental to computer science.” I began to understand that programming itself is not all of computational thinking. Programming is the interaction between the human and the computer in which the meaning making semiotic process occurs. However, computational thinking is the process one takes to solutions. The language is the instructions to the solution. In her video Wing said that space, time, and energy were the fundamental efficiency objectives in computational thinking. Similar to theoretical principles or Occam’s Razor, the simplest, least time and effort consuming answer is the one we must chose because we live in a universe with physical constraints.

Wing continues, “It is recognizing both the virtues and the dangers of aliasing, or giving someone or something more than one name. It is recognizing both the cost and power of indirect addressing and procedure call.” While programming in Python, I learned just how clear I had to be with my definitions. Because computer programs have very little vocabulary stored in their library as compared to human’s, creating new vocabulary for them must happen in the programming language. This is when we define and set our variables. Red = 5 and Monty = 23. Unlike humans, computers cannot function if Monty can equal 23 and 29 unless specifically told when it can equal 23 and when it can equal 29. This could be made in a conditional statement. If 1 + 1 == 2 is True, then Monty =23 , else if 1+ 1 == 4, then Monty = 29. This conditional function operates similarly to our understanding of words in sentence context. If you say, “I am all fired up,” or you say “I was fired today,” or if even you say the word “fire,” They have very different meanings even though the grammatical structures are not that different. As natural language processors, we can make sense of these conditionals through cultural absorption.

My own personal side note on the future of programming:

This week, I was curious about some of Vint Cerf’s (also wrote the forward to Great Principles of Computing) new ideas and projects and was excited to come across this TED Talk. As usual, I like to talk a multispecies view on new arising technology. In this TED Talk, computer scientists and animal behavior biologists come together to define elephants, great apes, and dolphins as sentient or self-aware beings (being able to identify themselves in a mirror). They then go on to imagine a world in which the complex communication patterns that these animals have would expand to our understanding through computing. Vint Cerf describes this project as a precursor to the large projects of the ISS and the Mars project are working on to increase computational language processing outside the scope of humans. Their intention would be to communicate with intelligent extraterrestrial life if they were to come across it.

While at first, this all seems very “wooshy washy” and reminiscent of pseudoscience, this TED Talk made me realize that there is actually a lot of science funding going into this type of computational programming because we exist within a universe of endless possibilities and any physicist and mathematician can tell you that there is a statistical change of coming across intelligent communicative life. Moreover, even getting a glimpse of animal communication networks can help us better understand our own cognition and biological evolution on our own planet.

I wonder how our understanding of abstraction and computational thinking may change as further research into multispecies computing continues…


Jeannette Wing, “Computational Thinking.” Communications of the ACM 49, no. 3 (March 2006): 33–35.

Peter J. Denning, “The Great Principles of Computing.” American Scientist, October, 2010.

Music Records as Distributed Cognition – Carson and Lauren

Music Records as Distributed Cognition


Our case study looking into music on records has many layers of distributed cognition and is a great example of the extended mind. Early on in the making process, we have the artist and their relationship to the instrument. Already we have an extended mind in which the human organism is linked with the external entity. As we know, there is no such thing as thought which is then suddenly put into a communication form. Rather, there is an artist who has listened and heard many other musical experiences before.

They are a member of a cultural system in which music has been created and interpreted by others before them. Because they have experienced this distributed cognition before, they begin with the ideas of other artists first. Then they begin to play the instrument. The sound the instrument makes in the external environment is then interpreted by the artist in relation to their ideas about past music. After judging the music, they alter their relationship to the instrument until they perceive a sound that they like.

Creating Record:

This whole experience is done through an externalized relationship of the artist with the sensory environment of the past (other music they have heard) and present (the music the instrument is making at the moment). From this point, the artist can then use more cognitive technology to offload the music as they create the music. This is recorded in analogue form onto a record giving even more mobility to the already distributed cognition.


The artist has little to no control over how the consumer will think about their music. The thoughts and emotions the artist put into creating the music are not provided to the consumer.

Actually playing a record:

The first step of this process is record selection. What do you want to listen to? The record selection is usually influenced by someone’s mood. (cognitive process) After the selection, the consumer would start the record player, letting the music play. This is where extended cognition comes in, the consumer’s thoughts and emotions at that time are being influenced directly by their environment. Sometimes, it is what they were expecting, but sometimes the music can trigger thoughts the consumer was not expecting.

What makes this special is that the vinyl spinning around creating music was created by someone else. The artist that created this piece of work is sharing their cognitive thoughts with consumers of that record. – Distributed Cognition.

Coding and Decoding at the ZOOHackathon – Lauren Neville

This week’s readings paralleled my experiences this weekend and helped me better understand the layers of abstraction and message coding involved in the making process. I spent the whole weekend at the National Zoo and the first annual ZooHackathon intended to bring designers and coders together to build solutions to illegal wildlife trafficking. The first night of the hackathon, we were given statements of how leaders in the wildlife field would like to combat illegal wildlife trade.

We were then sent off to form teams of engineers and designers to begin finding solutions to this problem. After discussing the problems, my team chose to create a phone app connected to email and Whatsapp for the law enforcement agents working in Uganda to use. They had expressed that the work they do is often very dangerous and that they would want a way to communicate that they were in danger to each other in a swift way. We ended up designing an app that at the touch of a button would send a prescripted panic message and your geolocation to everyone else connected to your team.

This app simplified the tedious process of writing a string of letters and sending individual messages to different members of your team with your location when you are in immediate danger. It revolutionized the law enforcement messaging system just by having a preprogramed system ready and updating it’s own information constantly from mapping technology.

This is the great affordance of the bit and digital technology. As stated, “Information theory [and digital encoding] works because we can reliably represent and reconstitute the material components of shared symbols.” I spent the weekend not writing their message, of course, but actually writing the message of that system into the computer to then display to them.

Using Javascript and Boolean Logic, I was able to write text write in components that asked the user to type in the phone numbers they eventually wanted the numbers to go to. Then I defined that component by stating “multiline: true” and “editable: true.” Javascript is a layer of language between the human and the computer. I was writing boolean logic statements into the software program, but of course these readings helped me remember that all of the components under the layers of Javascript were also written at a different time as a bit boolean logic statement.

The complex layering of messaging that went into just building another communication messaging system during this hackathon was truly amazing. Of course, I understand that none of the meaning within this project was an actual property of this data that I was using to relay instructions. “Meaning is not ‘in’ the system; it is the system,” was a very relevant point that I took from Introducing Information Theory. I was understanding that the meaning was our relationship to the instructions, our intentions, the designs we conceptualized.


Stuart Hall, “Encoding, Decoding.” In The Cultural Studies Reader, edited by Simon During, 507-17. London; New York: Routledge, 1993.

Martin Irvine, “Introduction to the Technical Theory of Information

James Gleick, The Information: A History, a Theory, a Flood. (New York, NY: Pantheon, 2011).

Our signs systems as interpretations: Lions

imageimageWhile doing these readings this week, I was also reading the book, Animal Internet which discussed the future of networked technology and our relationship to animals and the wild. It came to my attention how cultural relationships between humans and the environment happen through sign systems. Rarely do most citizens interact with the reality of a living animal. More often humans are interacting with the sound of the name of an animal, a written name of an animal, or very commonly a graphical interpretation of the animal.

Our relationships with animals revolve around our relationships to the symbol that is made to embody their essence. I began to analyze how Peirce would descibe our relationship and the psychological process that we go through when interacting with symbols of animals instead of the reality of them. An example of this may be the varying depictions of Big Cats throughout history, including lions and tigers.

Imagine a painting of a lion fighting a gladiator in Ancient Rome. We then begin Peirce’s triadic model. The object itself is a lion. The lion is depicted using paint into a piece of clay pottery. This is the representamen or sign vehicle. An ancient Roman is then looking at this pottery and with their own cultural and personal lens they interpret that lion as being vicious, aggressive, and often in fights with humans.

All of that meaning is not contained in that piece of pottery nor is an actual lion. The only way that the meaning is derived is from the relationship between the representamen and the interpreter. In this final process, meaning is made.

Does a simple example like this also help explain the notion of “double articulation” in linguistic patterns? From our Chandler reading we learned about the infinite amount of meanings we can make from a low-level of units. Chandler discussed that visual representations could fall into this duality of patterns in that elements of artistic design like lines are the sub- units that make up visual media. Could I go as far as to say that varying those lines across visual media in such a particular way has also allowed us to depict potentially the same thing (a lion) in visual representations in infinite different ways? For example lions have been looked at as brave, regal, terrifying, cute, cuddly, and helpless across pictorial depictions for millennia.

While I am focusing on animals in this piece because of personal interests, I think they also make for a good example of how we interact with other life forms and the universe through our relationships to signs interpreted to be the actual material things. I feel that this makes signs the most powerful tool in experiencing emotions towards causes like wildlife conservation.

Computer Coding & Language – Lauren Neville

My particular understanding of the human language actually first came from my experience coding in Javascript and HTML and realizing the extent in which syntax and structures must convey meaning from the human to the computer. Every word has to be placed appropriately and then was allowed to form command sentence structures. These were then nested and looped within each other to create complex architectures.

Of course, I have learned that coding is not language because language is not written language, but is actually words, rules, and interfaces. In computer coding there are very strict series’ of rules and grammars that must be followed. Within my Javascript platform, every word used came from a library which  was previously created and those words meant very specific meanings.

Comparing this experience to the readings about language, I was able to understand the unlimited ways that language itself can work. Words, contexts, and syntax are remixed constantly to form knew understandings from vernaculars to creating new words using morphology like “Googleable.” The lexicon of a single language is infinitely growing and allows for generative and combinatorial phrasing.

So while computer coding is not language by Steven Pinker’s definition, it is clearly modeled after our understanding of language and uses the affordances of recursion and combinatoriality through looping logic statements. Additionally, while many programs offer limited libraries of commands, such as “Circle” or “Canvas” we can also define new objects within coding. By defining variables and then referencing them as the newly defined word. This in many ways is how we bring a diverse lexicon and new meanings to the very rule oriented and structured system built into coding programs.

My question, however, is does coding limit language. As Pinker noted, computers cannot understand context very well and the same word in language can have many meanings with varying contexts. While coding it can only be defined as one thing. I suppose the future of AI is building computer programs that are modeled more closely to language in which words can be rearranged infinite ways and with many contextual components.


Jackendoff, Ray. 2002. Foundations of Language: Brain, Meaning, Grammar, Evolution. OUP Oxford.

Steven Pinker, Linguistics as a Window to Understanding the Brain. 2012.

Are humans just a network of relationships rather than single minds?

What are some of the main hypotheses and research conclusions (so far) in the research literature above for the question of how we have evolved as a “symbolic species”?

I was particularly interested in the notion that cultural networks are the vital link in the human cognitive process as stated in “Social Brain Matters.” This paper reminded me of the about Steven Johnson’s book, “Where Good Ideas Come From” in which he explains that innovation erupts often from highly dense, networked systems where there is an “adjacent possible” to every situation. This concept is built upon the notion that within complex systems, there is oppertunity to have something an alternate route to a solution. He writes, “The trick to having good ideas is not to sit around in glorious isolation and try to think big thoughts. The trick is to get more parts on the table,” (42).

Within several of the readings this week, I felt that the idea that the brain itself is not the reason for cognitive expression through symbolism, but rather that culture was. Through the archeological records it showed that there may have been a few isolated instances of symbolic expression on tools since the dawn of the Homo Sapein 195,000 years ago, but that only as populations went up and began to cluster into social networks 40,000 years ago did humans make “the Great Leap.” The Tasmanian example of limited tool and symbolic expression on the island thousands of years after the separation from the main continent struck me as another example of cognitive expression existing due to dense networked systems. When populations dwindled on the island, it was clear that the advanced practices subsided. 

This can be seen today in our innovative spaces. In the last 200 years, our extensive technological boom has been occurring in highly competitive and population spaces. Our cities are our cultural and therefore technological capitols.

Could it be said that the the statement “signs are not things, they are relationships” has a larger meaning in which human minds are not things, but solely the relationships we have. Do we only have the capacity to think as our beings as relational to everything else and that is the meaning of human consciousness?

The readings explain that our brains, built in a modular structure, at some point formed a “language of thought” which allowed for cross domain reasoning. In what way does this biological ability also cause the extended mind? Is the assumption that other beings exist in modular thought with a “non-extended mind”? Can they not see themselves relationally?

“Homo sapiens have been able to colonize the world by engaging with representations of reality rather than with reality itself,” (Barrett). On this mind blowing note, here is a video about chimpanzees using tools. While reading Social Brain Matters, I understood the vast differences between the ape mind and the human mind, but I can’t help but wonder about how they view reality and relationships as a “non-symbolic species.”



John C. Barrett, “The Archaeology of Mind: It’s Not What You Think.” Cambridge Archaeological Journal 23, no. 01 (2013): 1-17.

Merlin Donald, “Evolutionary Origins of the Social Brain,” from Social Brain Matters: Stances on the Neurobiology of Social Cognition, ed. Oscar Vilarroya, et al. Amsterdam: Rodophi, 2007.

Kate Wong, “The Morning of the Modern Mind: Symbolic Culture.” Scientific American 292, no. 6 (June 2005): 86-95.

Colin Renfrew, “Mind and Matter: Cognitive Archaeology and External Symbolic Storage.” In Cognition and Material Culture: The Archaeology of Symbolic Storage, edited by Colin Renfrew, 1-6. Cambridge, UK: McDonald Institute for Archaeological Research, 1999.