Final written documentation in Foundations in Digital Media. Title: Conversation Through Patterns. Ilze Briede [Kavi], 2020.
Can patterns become a mediator and a field of communication between human and machine? Could pattern also mean a form of emergence when looking at the landscape of complex and unknown? Pattern recognition and creation have been on human existence agenda for millennia, in its core lies the idea of abstraction and re-creation. The pattern can also be seen "as an algorithmic movement in making of things" (McLean, 2020), especially when we look at the process of weaving. Pattern travels across various domains of materials and media, such as paper, textiles, clay, organic vegetation, pixel space and binary systems. Because of its inherent properties and characteristics, the pattern exists in both fields of human creative thinking and algorithmic computation. I propose to create a language of patterns that can serve as communication protocols merging our thinking and computation on a terrain of equals in response and exchange.
Keywords: Patterns, complexity, emergence, human-algorithm collaboration.
Figure 1
Imagine sitting by the table with one thousand puzzle pieces laid out in front of you. Where do you start? What strategy, better or worse, will you apply? Just pick a random piece, any piece. As you are twirling this puzzle element in your fingers in an attempt to find some point of reference, you also begin to feel a brewing neural storm up in your brain chambers. Your senses are narrowing down on this one piece of the puzzle, and you start to notice all kinds of things about it: shape, fuzzy but definite colour, some abstract ripped off paint stroke of a larger image yet to be discovered. This singular tiny piece is dense with information, fragmented and ready to be put in use, offering multitudes of obscure, and yet significant clues. Finally, another piece finds it's corresponding match, followed by a few more affirming their neighbouring positions. There is still nine hundred ninety-six more to go, but you are getting a hang of it now. But have you noticed something? The significance of the singular piece of the puzzle is starting to melt into multitudes. The starting reference point now grows into a field, and soon enough, you are staring at the sunset on some imaginary island. The final piece of the puzzle also rings the death of all puzzle pieces as they get stripped off significance, heightened attention and excessive handling. Hold that thought for a moment about you forgetting that first piece of a puzzle.
This short analogy is here to incite and bring to attention our very nature when dealing with information, images and ultimately the world around us, which is one continuous expanding image, sound, rolling wallpaper of sensual data, a tangible matter. Let's look at the world as a puzzle, and us exploring it, piece by piece. This particular puzzle is generative, not pre-determined nor cookie-cut on stiff cardboard. It is shifting and changing, a sort of a puzzle you should never attempt laying your fingers on, but you have. More precisely, we are part of it! When we face unknown, new, emergent and strange, this heightened sense of encounter within is an important moment in the process of discovery and learning. Learning to me means abandoning what you know, more like giving it slack so that new thing can come and ruffle things up a bit. I do think about the nature of evolution and the complexity of body cell formation. When embryo starts as a single stem cell that holds answers and solutions to myriads of possible questions and challenges, it is ready to fold into learned shapes and forms tampered and tested through times. It is like a piece of this mysterious puzzle in the world yet to be discovered and formed. A constant feedback loop between a newly built environment of self that will need to live and exist in a much bigger environment that of a world. "Evolutionary trajectories depend on development" (Fontana, 2003), and "the mechanisms of development are themselves subject to evolution, creating feedback between evolution and development." (ibid.). Fontana argues that capacity to evolve a.k.a. development a.k.a. potential for change is formed inside RNA with the help of phenotype and genotype, rather than responding directly to the outside environment. This internal structure and behaviour of cells or a "circle of cause and effect known as development" (ibid.) is what structures us and our world, and us within this world.
"Behaviour is not a thing, behaviour is the property of a thing." (Fontana, p.21)
When facing complexity and venturing into the unknown, we rely on our cellular navigation and senses buried deep in our guts. This inner space, the topology of possible, holds competent cells and biochemical liquids that respond and form networks of contextualising solutions, signals, pulses, and emergent forms that also manifest as sight, hearing, smell, taste and physical touch. These senses externalise the inner workings that also serve as a connecting agent allowing communication between us and the world at large. In the context of constructive systems, Fontana describes interactions between different autonomous organisations via "new functions that belong to neither organisation" (ibid.) These functions that have access to each of the systems, also form new connections directly linked with the "laws of change". To me, this middle space looks like a sound space for innovation, experimentation, trial and error, forming new bonds and remaking the old ones. This is also a room where ideas can be formed and tested, languages constructed and trialled, behaviours configured and shaped or discarded altogether, a shifting space, that darn puzzle I mentioned to you at the start.
Figure 2
You are staring at this image, and as the title suggests, your eyes are scanning for a shape of a dog. It suddenly magically lifts off the plot of black and white blobs. As a piece of a puzzle, this canine is emerging whilst detaching itself from the field of the noise.
Figure 3
What do you see? Here are some probabilistic answers:
- A satellite image of Mojave Desert
- A microscopic rendering of Purkinje cells
- A generative computational art piece
The answer is somehwere at the bottom of this page.
Figure 4
Look around, does the world look familiar to you today? Imagine this: the world around you is a finished puzzle. All the pieces are working together tirelessly to render a reality you wake up to every morning. Go and take a closer look, actually, why don't you pick a one piece of a puzzle in your own hands. As a side note, by doing that, you have irreversibly erased all the memory about everything, including the world itself. All that you got is this one piece of a puzzle against the gigantic unknown. How does this piece look to you? What can you tell about it? What strategy, a better or worst, will you apply to learn about this complex new world that you are about to discover?
Moving from one realm to the other requires some methodology, instrumentation, and perhaps an invention of new thinking approaches. As a case study, I will examine paper written by two programmers David Griffiths and Alex McLean called "Textility of code: a catalogue of errors". The reason, why the error was a case, is that both authors thought to translate the structure of old textile weaving into contemporary source codes by "treating weaving as a computational medium." (Griffiths, McLean, 2017). They succeeded, but they also discovered multiple ongoing levels of linked interactions between the thread, loom, weaver and textile that were hard to anticipate when programing the algorithms. The aspect of improvisation at the loom by a weaver, especially in the case of creating selvedge that are fabric's edges, "is analogues to live coding, where code is written 'on the fly'." (ibid.) There are also other aspects of textile behaviour whilst on the loom and when taken off. The choice of thread material, physical strength and experience of the weaver, and particularities of the pattern, all play an impactful role in the technological process of making. Even though the source code and set of rules and functions persist throughout the weave, there is the unwritten and undefined world of possibilities for error, malfunction and other challenges that needs to be solved creatively, skillfully and en route. Both co-authors see textile-making and its artistic philosophy informing and enriching computer science development. They are not far from it, Jacquard loom with information punchcards is considered a computer's predecessor. Charles Babbage, British inventor and mathematician, also known as a "father of the computer" based his Analytical Engine on Jacquard machines. To navigate in the creative field of pattern creation, McLean and Griffiths deployed L-Systems, a recursive programming syntax that simulates plant growth and fractals generation. "L-systems can be related to weaves, in that they consist of rules which may appear to be simple, but which often generate complex results." (ibid.)
The pattern is a piece of a mystery, or even a puzzle itself. It has many properties and characteristics. It is also an abstraction of something else, an idea, a concept, or a thing. Its crude visual body is information encoded. A pattern can become a symbol; it is a container, a library. The pattern is a letter in a word, a word in a sentence, and a sentence in a tome of other patterns. "All visual patterns and tessealations at their core are composed of algorithms. Even centuries-old patterns, such as Scottish tartans, follow strict compositional rules that are capable of being encoded into software. Writing code is an exciting way to approach visual patterns." (Reas, McWilliams, 2010)
First of all, let us examine the pattern. We look at flat representations of patterns in 2D; we only see two of many possible dimensions. Let's try and think about it as a slice of a state, a frozen moment captured in time passage. Or as a cross-section of a far more exciting and outlandish fruit or vegetable that you will ever encounter!
Figures 5, 6
I am opening this suggestion for a few reasons. Thinking about patterns as an ongoing morphing visualisation will allow me to contextualise the pattern as a live real-time interchange and continuously updated piece of information. Similarly, as in Roy Ascott's 'Change paintings', the spectator can deliberately alter the physical body of painting by sliding Plexiglas layers that reorder and change the composition anew. He calls these kinetic pieces "analogues of ideas" that have an inert property to change and be changed. Roy Ascott believed that ideas should not be fixed and "open to investigation and reconstruction" (Ascott, 1964). To witness a change, we can do it through a feedback loop system in computerised environment. This type of system allows for a constant update that takes the input and generates the output, and that gets fed back into the input again, becoming a perfect way to detect and observe changes. This change is also evaluated continuously against the previous generation of data and registers occurring and prior chain of events in an ongoing conversation. To me, this exchange looks like a suitable method to facilitate a cross-communication between human and machine (algorithm), using feedback loops as patterns. Here I would like to refer back to Walter Fontana's paper "The Topology of the Possible". He mentions the third kind of organisation, a "crosstalk" between two autonomous organisations that connects them without changing their functionality. All together, they create a high-order system. "Rather than perturbing an organisation with a single function, we can add a whole other organisation. In some cases, the merged organisations don't drive each other out of existence, but integrate stably. [...] successful integration is dependent on feedback loops." (Fontana, 2003). The feedback loop can be achieved by real-time access and modification of the source code from both parties: a coder and an algorithm.
This paper approaches the idea and is a proposal that still needs to be developed through practice. The methodology I would like to start with is as follows:
-
Create an open code environment that allows real-time updates from human and non-human parties. The code will generate a pattern, but also permit its modification and update in real-time from external sources, such as midi or OSC data, as well as internally by using a built-in interpreter in the code environment.
-
Construct meaningful visual registering displays that show input data and updated data simultaneously, perhaps using different colour codes or displayed in 3D as a time slice. See mock-up images below.
-
Allow to capture and record the ongoing pattern modifications that could be studied later away from the code and interaction.
Figures 7, 8
To allow two different systems to meet, in my case, it is a human creator/coder and a computer algorithm, a third independent system should be devised that will work as an interconnector. The connection lines running through all three would be supported by feedback loops, cross-communicating and coupling each other systems based on their internal rules and laws of functions. This third alternative glueing system I imagine to be generative space of pattern a.k.a. pieces of the puzzle.
The most challenging part would be to create an algorithm that can overwrite, change, transcode itself and set its own unique rules of its worldbuilding. The live coding aspect here is very crucial, as it will set all systems according to the same time zone of now.
We also need to imagine, that the way human/coder will communicate with the algorithm would be through this new pattern interface that would be an open coding environment. Perhaps, that could be an open-ended system that would allow multiple connections, as well as its own supporting functions, to facilitate this collaborative communication and vis-a-vis worldbuilding. Alex McLean calls "live coding 'codeo-morphology' as the changing shape of code over time." (McLean et al, 2010).
John H. Holland, an American scientist and professor in computer science and psychology, in his book on emergence talks about mechanisms or "building blocks" that allow to "construct models that exhibit emergent phenomena" (Holland, 1998). I believe there is a way to create a different kind of dialogue outside spoken word and rooted in the space of visualisation and experimentation. The main question persists: when does complexity become emergent? When does emergence appear, has it always been there and we somehow missed it? Is it a Dalmation? Or is it an ability to overwrite complexity with familiarity, which is when emergence has a chance to surface? I used the analogy about the world being a shifting puzzle tapestry, where we seem to fail in locating the building blocks. It is perhaps unnatural to see at such minute detail; therefore, we seem to be dulled down to see the change in static chunks, not as a continuous everlasting integral moment in passing. I think this phenomenon addresses the way we look and not see, forgetting about the complexity and emergent phenomena surrounding us everywhere. I hope that patterns would be more suited and complex enough to capture small wonders and situations that are out of ordinary; the ones we might call memorable and emergent.
Below is a simple puzzle game that invites you to interact with pieces of segments and arrange them into a pattern. The idea behind this simple game of puzzle is to ask yourself what the pattern is? Can and does it have a single finite variation or multiple ones? If you would be a generator, what would your pattern look like, what made you choose this particular combination? In this space of thinking about these questions, we can also invite other new forms coming from non-human creator perspective. In this new light of observing and dissecting, what would we see?
body {
text-align: center;
}
.puzzle {
display: inline-block;
margin-top: 10px;
}
//this codepen was forked from James Meyers
//https://codepen.io/FullR/pen/zKVKwE
const src = "https://ilzebriede.github.io/Conversation-through-patterns/images/Pattern1.jpg?quality=89&w=500";
class Puzzle {
constructor({src, rows, columns, width, height}) {
this.src = src;
this.rows = rows;
this.columns = columns;
this.width = width;
this.height = height;
this.tileWidth = width / columns;
this.tileHeight = height / rows;
this.tiles = Array.from({length: rows * columns}).map((_, i) => {
const x = i % columns;
const y = Math.floor(i / columns);
return {
x, y,
imageX: x,
imageY: y,
empty: false
};
});
this.emptyTile = last(this.tiles);
this.emptyTile.empty = true;
this.scramble();
this.createElements();
}
slideTile(tile) {
const {emptyTile} = this;
if(!this.areTilesNeighbors(tile, emptyTile)) return;
this.swapTiles(tile, emptyTile);
this.updateTileElPosition(tile);
this.updateTileElPosition(emptyTile);
}
swapTiles(a, b) {
const {x: ax, y: ay} = a;
const {x: bx, y: by} = b;
a.x = bx;
a.y = by;
b.x = ax;
b.y = ay;
}
scramble() {
const {emptyTile} = this;
let last = null;
const isValidTile = (tile) => tile !== last && tile !== emptyTile && this.areTilesNeighbors(tile, emptyTile);
for(let i = 0; i < 1000; i++) {
const nextTile = last = sample(this.tiles.filter(isValidTile));
this.swapTiles(emptyTile, nextTile);
}
}
updateTileElPosition(tile) {
const {tileWidth, tileHeight} = this;
const {el, x, y} = tile;
el.style.left = `${x * tileWidth}px`;
el.style.top = `${y * tileHeight}px`;
}
areTilesNeighbors(a, b) {
const {x: ax, y: ay} = a;
const {x: bx, y: by} = b;
return (
(a !== b) &&
(
(ax === bx && (ay === by + 1 || ay === by - 1)) ||
(ay === by && (ax === bx + 1 || ax === bx - 1))
)
);
}
createElements() {
const {src, tiles, width, height, tileWidth, tileHeight} = this;
const tileEls = tiles.map((tile) => {
const {x, y, imageX, imageY, empty} = tile;
const tileEl = createEl("div", "tile");
Object.assign(tileEl.style, {
"position": "absolute",
"width": `${tileWidth}px`,
"height": `${tileHeight}px`,
"background-image": `url(${src})`,
"background-size": `${width}px ${height}px`,
"background-position": `-${imageX * tileWidth}px -${imageY * tileHeight}px`,
"transition": "top 0.1s, left 0.1s",
"vertical-align": "top",
"cursor": "pointer"
});
if(empty) {
tileEl.style.opacity = "0";
tileEl.style.cursor = "default";
}
tileEl.addEventListener("click", this.slideTile.bind(this, tile));
tile.el = tileEl;
this.updateTileElPosition(tile);
return tileEl;
});
const puzzleEl = this.el = createEl("div", "puzzle");
Object.assign(puzzleEl.style, {
position: "relative",
width: `${width}px`,
height: `${height}px`
});
tileEls.forEach((el) => puzzleEl.appendChild(el));
}
}
function createEl(tag, ...classNames) {
const el = document.createElement(tag);
if(classNames.length) el.classList.add(...classNames);
return el;
}
function sample(arr) {
return arr[Math.floor(Math.random() * arr.length)];
}
function last(arr) {
return arr[arr.length - 1];
}
const puzzle = new Puzzle({
src,
width: 600,
height: 400,
rows: 4,
columns: 4
});
document.body.appendChild(puzzle.el);
Figure 9
- Figure 1. Fragment of a pattern, Ilze Briede 2020
- Figure 2. Hidden dalmation, Published by James Dean https://www.moillusions.com/hidden-dalmation-dog/
- Figure 3. "File:Cerebellum Cross Section Purkinje Cells (42040995732).jpg" by Berkshire Community College Bioscience Image Library https://commons.wikimedia.org/w/index.php?curid=70159812
- Figure 4. Fragment of a pattern, Ilze Briede 2020
- Figure 5. Exotic fruits, Jannes Pockele 2009. https://www.flickr.com/photos/44148352@N00/4200905730
- Figure 6. Fragment of a pattern, Ilze Briede 2020
- Figure 7, 8. Coded patterns created with p5.js, Ilze Briede 2020
- Figure 9. A codepen puzzle. Image: Ilze Briede 2020, code: James Meyers 2016 https://codepen.io/FullR/pen/zKVKwE
Ascott, Roy. Telematic embrace: Visionary theories of art, technology, and consciousness. Univ of California Press, 2007. Fontana, Walter. "The topology of the possible." Understanding Change. Palgrave Macmillan, London, 2006. 67-84. Griffiths, David, and Alex McLean. "Textility of Code: A Catalogue of Errors." TEXTILE 15.2 (2017): 198-214. McLean, Alex. "Algorithmic Pattern." NIME, 2020. McLean, Alex, et al. "Visualisation of live code." Electronic Visualisation and the Arts (EVA 2010) (2010): 26-30. Reas, Casey, and Chandler McWilliams. Form+ Code: in design, art, and architecture. Princeton Architecturel Press, 2011.
Ascott, Roy. Telematic embrace: Visionary theories of art, technology, and consciousness. Univ of California Press, 2007. Chapter: The Construction of Change (pp.97 - pp.108)
For Roy Ascott, artwork occupies a space between two sets of behaviours: the artists and the spectators. "It is essentially a matrix, the substance between. It exists neither for itself nor by itself." (p.99) His Change Paintings are analogues of ideas, open to different interpretations and able of various states. The process that is an act of creation itself happens amid the artwork and the perceiver. I think this is Roy Ascott's "fluid field" that encourages, catalyses and supports the change. The journey from idea to its manifestation is more critical than the outcome, as each time the result can be ultimately a different form. The idea behind his Groundcourse (a two-year art program) is to allow creative mind seek possible outcomes to impossible things, an invitation to work with something unthinkable and unique and translate it via real-world materials and tools, and techniques. Because "out of the flux, a many-sided organism may evolve" (pp.102). He sees cybernetics as a unique angle to explore the environment, its structure, behaviour and building blocks, a methodology that artists can apply and expand through the process of art-making.
Cariani, Peter Anthony. On the design of devices with emergent semantic functions. Diss. State University of New York, 1989. Chapter 12 Emergence and open-endedness (148-169).
Emergence is directly connected with the notion of novelty. Cariani states that "If we want our devices to be creative in any meaningful sense of the word, they must be capable of emergent behaviour if implementing functions we have not specified." (p.148) Cariani lists three types of emergences: physical (water molecule states as ice, water, steam = thermodynamic model, order from noise), biological (such as life = form from formlessness, order from chaos), and psychological (aha moment). There is also a computational emergence, such as a-life simulations and cellular automata. Another point Cariani is trying to get across is that the "higher-level patterns must be recognised by the human observer. [...] it is a mistake to believe this to be a property of the device." (p.152) I would argue here that we are not trying to attribute who or what owns the emergent pattern. In my opinion, the key is that there is a moment of acknowledgement that such pattern even exists. I am curious about how can we come to this moment of realisation, that the emergent behaviour or pattern has happened. I don't think it is about why and how, it is about a moment of encounter, realisation. Even though this moment of discovery does flash up within our human psyche, something external initiated it. We need to look at how to expand this space of the encounter into a field of enquiring, a space for work and experiments. Cariani says that "emergence relative to a model (biologically based emergence - I.B.), then is a result of the finite and hence incomplete character of all models of the world." (p.157) So be it! Why can't we operate on incomplete models? For Nietzsche, language and words are moving away from the truth. Nevertheless, we do use language as a means of communication, no matter how far we are from the true essence of the truthfulness this word abstracts from. It is our only way to communicate via spoken and written language. It is complete in its incompleteness. Emergent system 1)ability to measure and affect changes in outside world 2)capacity for adaptive self-alteration. Cariani calls them "syntactically adaptive" = genetic algorithms, "semantically adaptive" = this mapping interprets the input = forming a new sensory organ. But is this a "new" organ, or is it same organ but in a different configuration?
Fontana, Walter. "The topology of the possible." Understanding Change. Palgrave Macmillan, London, 2006. 67-84.
Keywords: System = sequence, configuration, genotype. Behaviour = shape a.k.a. folded sequence, phenotype. Change, evolution. In this draft paper, Fontana talks about how change happens in evolutionary systems such as RNA based on two main biological components: a phenotype and genotype. Suppose the phenotype is in charge of the system's behaviour. In that case, the genotype is a "heritable repository of information that participates in the production of molecules whose interactions, in conjunction with the environment, generate and maintain the phenotype." (ibid. p.2) The key phrase here is "environment", Fontana argues that environment alone is not what drives evolutionary change, but internal workings of the system itself. Fontana proposes looking at phenotype as a self-maintaining system that is a functional closure with intricate inner workings between its components. The feedback loop within the system ensures a state of homeostasis, or at least it is drifting towards that direction. It also allows any repairs of missing components, and it creates a certain level of robustness to the system. Fontana states that "robustness enables change". It is an exciting standpoint thinking about our evolutionary traits, proposing that stability and stasis are a catalyst for new formations, opposite to what history suggests in world events. Based on Fontana, change is bound to happen if the system, whether it is a human race, nature, or any other species, is fit and ready for it internally. When two different systems interact, the connection will foster a new type of components that neither belongs to the one or the other system. These new elements will serve as a "glue" allowing a cross-communication between these two autonomous systems. The change can't be propelled from outside. Once the inner structure and components reconfigure, it no longer is the same system. The change is a cause and effect in the worldbuilding. "The mechanisms of development are themselves subject to evolution, creating feedback between evolution and development." (ibid., p.5)
Griffiths, David, and Alex McLean. "Textility of Code: A Catalogue of Errors." TEXTILE 15.2 (2017): 198-214.
This research article describes attempts to understand and communicate how weavers think and create textiles. Two programmers and researchers David Griffiths and Alex McLean from England approached this question from programming an coding. They both worked on creating computing algorithms using Scheme and Haskell programming languages to "help communicate the complexity of its (weaving - I.B.) structure and perhaps look for ways in which textiles could inform the development of computer science." (p.2) What was interesting in this article was the approach in thinking from the perspective of a thread. When translating weaving functions within the computing realm, there can be many departures or centres of dwelling, such as the perspective of a weaver, loom, or thread. It made me think about the programming world's multidimensionality, such as the egocentric or the allocentric approach. Where code can be written in parallel exiting from the object's perspective and then being translated into coordinates of the field this object is also a part. This article is dealing with the same questions I had ever since thinking about weaving patterns and computation. It even goes beyond creating computer programs that simulate different types of weaving, such as plain weave, four-shaft loom, tablet weaving, warp-weighted loom, all of those being ancient technologies developed and practised before the advent of computers. The key points I want to take from this article are:
- Application of L-Systems in the generation of complex patterns.
- The properties of thread, weave, and textile is based on rules, binary nature and three-dimensional phenomena.
- Finally, the aspect of weavers response in real-time altering the weave corresponds to the idea of live coding.
Licklider, Joseph CR. "Man-computer symbiosis." Multimedia: From Wagner to virtual reality (2001): 55-63.
The idea about computer-man symbiotic work practice where a machine takes over technical tasks while the human mind can engage more freely with the generation of ideas. A need to create a methodology where man and machine meet in productive collaborative space, able to communicate back and forth each other findings and needs. Dissimilarity and potential supplementation between man and machinic thinking. Challenges: language to aid two-way translation between parties, "To bring computing machines effectively into processes of thinking that must go on in "real time," time that moves too fast to permit using computers in conventional ways." "If computer thinking could be introduced effectively into the thought process, the functions that can be performed by data-processing machines would improve or facilitate thinking and problem solving in an important way." My personal thoughts: This article was originally written in 1960, and it paints the future we already reached. The question about human-computer symbiosis is still relevant, and it hasn't been answered in the past 60 years. The computers have evolved as we have developed ways to interact with them. However, computers and computational programs are still solving problems. Symbiotic relationships can harness different interaction outcomes, and there are classified eight such interaction modules. What Licklider was suggesting by offering a fig tree and Blastonphaga grossorum insect example, is a mutualistic relationship where both agencies benefit from each other. It seems to me that only humans have profited from computers, and it is hard to talk about mutual inter-relationship as computers are not independent agents, but programmed and constructed by humans. Additionally, Lickider suggests that "computer [...] will accept a clearly secondary status" in decision making and recognising relevance. If this type of relationship is formed where human will take an upper-hand, doesn't it question and distrusts the computational process to be equally relevant and important? Machine learning is operating on given data that becomes it's learned memory. Even though neural networks of computerised systems are built inspired by brain neural networks, we are still learning to understand how decisions are formed in unsupervised computerised systems. We have created something that we do not understand ourselves, and that has become a subject of inquiry in itself. We feed computers data that represents humans in the hope that they will form a sort of essence or ways to reflect on our ways or show something that we didn't know. If we feed computer algorithms known and existing data, how can they create something novel? Aren't we making an echo-chamber of our world, transmitted, recycled and rebuilt by machine? How can this data exchange benefit us and computers in general? Symbiosis is described as "cooperative "living together" in intimate association, or even close union, of two dissimilar organisms" ("Welister's New International Dictionary," 2n(l e(i., G. and C.Mlerriam Co., Springfield, Mass., p. 2555; 1958.) The keyword here is intimate, suggesting a close, personal and mutually understanding connection and exchange. Is it possible to build an intimate and close inter-personal relation between human and machine?
McLean, Alex, et al. "Visualisation of live code." Electronic Visualisation and the Arts (EVA 2010) (2010): 26-30.
This article focuses on coding as live performance and lists several live coding languages and environments. many of them are created within Fluxus, a game engine meant for live performances and experiments. "Live coding has the unique opportunity to visualise the movement of an underlying process while it is being performed." (p.28) This article also talks about the body of these live coding environments, a collection of symbols interpreted by both, a coder and computer. These non-language visual environments offer a new communication method between coder and code interpreter, such as a computer. I also think these esoteric languages become so visually engaging because, in live coding performance, the coder screen is shared with the audience. This functional visualisation becomes a map of clues for the audience and map of instruments for the coder. The main underlying question in this paper is this: "Can a live coder elucidate the more abstract thinking gestures of their practice?" (p.26) To me, this topic is significant, as I have been live performing visuals since 2006. I have many VJing tools and appropriated other types of software for live performances, such as TouchDesigner, Photoshop with graphics tablet and pen, and Max/MSP. The choice of these visual instruments would be based on the visual style I could achieve. I would also experiment with data input and manipulation in real-time using midi controllers and sensor-based hardware. However, my working screen would be exclusively accessible to me, and the audience would see curated output minus the control panels. Live coding environments become input area and output screen simultaneously. It is a radically different approach to invite spectator inside the studio space to observe work being made.
Sommerer, Christa, and Laurent Mignonneau. "Modeling the emergence of complexity: Complex systems, the origin of life and interactive on-line art." Leonardo 35.2 (2002): 161-169.
Keywords: Complex systems theory, emergence, A- Life, edge-of-chaos (C.Langton, N.Packard) This academic research paper describes an Internet-based interactive artwork called VERBARIUM (1999) created in order to model and simulate creative emergence based on participator engagement and interactions. The principle discussed for catalising interconnectedness and collective co-creating are phase transitions (Complex systems theory); a balance act and the midpoint between order and disorder, stability and flexibility, intent and meaning. In VERBARIUM an input digital text gets transformed into 3D form, then added and stored with a collective image transforming and evolving overtime. The process is supported by specially designed text-to-form editor that morphs and growcs 8 vertices ring into complex growing structure.
Whitelaw, Mitchell. Metacreation: art and artificial life. Mit Press, 2006. Chapter: Emergence (pp.207-237)
Whitelaw distinguishes two types of levels in a-life art emergence: local and global. If local emergence is informed by a computational set of rules and functions, then global level emergence appears as behavioural "patterns in time or space" (ibid. 214). This type of emergence becomes a new phenomenon that wasn't programmed beforehand. The local level means "technological substrate", and it is software and hardware. The global level means "phenomenal and behavioural product of that technological substrate" (ibid., p.215). "In a-life systems there is no simple correspondence between substrate and phenomenon but a complex entangled causality giving rise to artifacts and events that seem to constitute something new, something extra" (ibid., p.215) Whitelaw talks about a-life that "becomes other", in which case it needs to "surrender its intentionality at some point in this process" (p.226). My thoughts are that we can't speak about the intentionality, that implies that we do already understand the system to has some sort of intentionality. The question is: is this intentionality read by us, meaning, what we consider intentional, or is it really intended by system. But how can we know that? "The evolved form can be considered an emergent phenomenon, one that has somehow exceeded or pulled from its mechanistic substrate." (ibid., p.215) "Any system capable of autonomous ongoing emergence could move outside the bounds of its host system, across domains." (p.228) "There is no reason why it (a-life art - I.B.) should stay in the gallery or in the computer. [...] It would be unbounded and unintentional, an adaptive pattern indistinguishable from the wider dynamics of its environment." (p.228) Personal Note: This analogy reminds me of Walter Fontana's description of genotype being a system and configuration, and the genotype being the form and behaviour. One can't survive without the other. Same in here: the emergent behaviour within the computational world can't happen without the hardware and syntax of the code, but the code and hardware also inform such behaviour that exists within this type of system. Once again, I do think of the importance of the feedback loop and genetic systems where output can inform and alter the input, therefore becoming a self-sustaining self-"aware" system. The level and speed of calculations and tasks have also informed technology itself by becoming more accomodating and suitable for computation needs. However, I would argue that this is a human-created necessity to build more sophisticated machines to do more complex computations. The neural networks that reconstruct themselves to become more efficient at tasks are closer to self-sustaining, self-improving systems, but that only exists as software and not hardware.