https://christopherswift.work CONTROL Tue, 17 Aug 2021 01:48:08 +0000 https://christopherswift.work en https://christopherswift.work/Introduction Tue, 17 Aug 2021 01:47:45 +0000 CONTROL https://christopherswift.work/Introduction CONTROL Reconsidering the designer as one among many in a creative and collaborative network of active participants full of agency and potential. In these most depressing of times, these are some of the issues I want to press, not to depress the reader but to press ahead, to redirect our meager capacities as fast as possible.—Bruno Latour AbstractMy MFA work explores the creative networks between a graphic designer and their collaborators, both human and non-human (other designers, but also software, papers, inks, presses, cameras, the internet, design history, cultural knowledge, language, etc). My thesis project examines how the interplay of control and trust in a designer’s relationship with their network of tools (creative, cultural, technological) can be attended to, challenged, and reimagined. The black boxes which envelop our tools obscure the complexity and scale of the collaborative and relational space we work in. My work reconsiders the designer as one among many in a creative and collaborative network of active participants full of agency and potential. My thesis seeks ways to give the tools of my creative network fully agented status as collaborator by foregrounding instead of avoiding their active participation in what we create together. Through coding in various languages (javascript and Processing programs, InDesign scripts, and machine learning models) I created new digital tools in which the agency of the tool itself is highlighted. I use these new tools to undertake an intentionally nonhierarchical mode of making, decentering my role as designer to create a vast and potentially endless series of posters, zines, album covers, music, and poetry. Each of my projects pushes me further away from a mode of control towards one of care and trust in the creative design process, anchored in a belief that as long as there is collaborative care, respect, and trust (love?), the work we make together is worthwhile. INTRODUCTION TO CONTROLThis thesis is about control, trust, and care in the creative process of graphic design, and about how trusting and caring for the network of collaborators, human and non-human that we work with can make a space for new kinds of work, exciting, unique collaborations that interact with the world in new ways. Through this reexamination of the role of the designer in the networks of actors that our industry exists inside of, we might find ways to accept change, to see failure in new ways, to find new energy of purpose. We seek control when we are more afraid of possible outcomes than we are excited by them. This fear of the unknown, fear of possible failures, fear of not having all the answers, this fear comes when we do not trust our team, our collaborators, our networks involved in our creative endeavors. But if we can show care (love?) for the actors in our networks (human and non-human), if we can trust that we are doing something worthwhile together, we can accept them and trust them. When we can do that, we can let go of the need for control, and we can leap with creativity, we can be the lightning of possible storms, we can light fires and be generative. This thesis is structured around a series of essays that explore a set of design projects executed over the past two years for this MFA program. They chronologically trace the path of my personal relationship with graphic design (from feeling disillusioned and burnt out to finding a source of excitement and energy and care), my need for control, my fear of failure, my understanding of my role as a designer, and my gradual acceptance of a careful trust and trusting care of my collaborators (human and non-human). The first essay, Camera Obscura, is about an ongoing photography project I set up in a converted attic bathroom during lockdown. The project’s key learning outcome for me was around a realization that this process was happening without me. The time spent sitting in the dark while my eyes adjusted to the relations between bent and reflecting photons and the substrates of the bathroom was a revelation in creative relationships that don’t center around me. A slow reveal that took time to grasp, but happened because I had the time to spend within this creative network of things that aren’t me, my role limited to setting up and documenting what they were up to. This was a first step in decentering my role, a step that was about seeing a nonhierarchical network of making and signification; seeing my place in it in a new light. Chapter 2 — Hybrid Posters is about my early explorations with tool agency. In my previous work with letterpress printing, I had come to a belief that I could never truly master my working relationship with the press. I could learn its nuances and work with them, as long as I could give up on perfection and accept that I would need to collaborate but not really control the entire process or the outcomes. I could try to make exact copies, but variation was built into the work. It did not see it as a flaw but as a feature, worth attending to. I wanted to achieve something like that with my current, primarily digital tools. I wanted to give agency to my tools. I was looking to work with them, not to control them completely. I made headway into this by learning to code in a couple of languages that could help me tease open the software of the profession and bring in something like agented action. I found delight in some of the things I helped to create with these tools and these collaborative creative networks. I created new tools, modified old ones, and collaborated in a way with the network at play in these creations. Chapter 3 — A Careful Trust / Zine Collaborations is about the process of collecting all of the prose, code, and images that I had been creating and making something new with it. Something that could highlight the year of work, and hopefully begin to make sense of what I was doing. I looked to find ways to alter my role in the process of making, spaces that could be played with in new ways, rules that could be bent, rules that could be broken. The essay considers ways that I might be able to let go and trust that we (myself and my nonhuman collaborators) are doing something interesting, together. Chapter 4 — Dragons and Princesses is about my first encounters with machine learning and artificial intelligence. In previous projects, I had introduced a kind of agency through randomness that the programs I had written could act on. While they produced new and often delightful outputs, they were still only able to develop along lines that I had determined. They could only act as freely as I let them. Machine learning let me explore another avenue towards the collaboration I was seeking. This would be an exponential jump in scale and complexity in the network of collaborators. This would be truly new. And these projects all failed. I did not trust these tools. I did not understand them, and they made me nervous and uncomfortable. I withdrew my care. I pulled back from what I thought might be monsters. Chapter 5 — Floating on Oceans. This essay documents my early explorations of generative machine learning models. The previous AI and ML projects I had worked on were based on the “detection” side of the models. They had been trained on huge datasets of images and could determine the content of new images with remarkable accuracy. They are often brutally flawed. I had abandoned them and their fraught ethics. The models I wanted to explore now could make amazing things. The StyleGAN model from NVidia was producing remarkable outputs depicting people’s faces, but people that did not exist; newly generated faces that looked so real that it was hard to comprehend what you were looking at at first glimpse. I hoped to find similar success making new graphic design pieces with similar ML models. This essay explores three attempts at working with GANs, each a fantastic failure and success. These projects were the first glimpses I had at the scope and complexity of what these models were producing. These projects all produced incredible things, but I could not understand their aesthetic value at the time. What seemed like failures at the time were, in fact, only failures in my ability to see or understand what I was looking at, at what I was experiencing. Chapter 6 — Infinite Art Bot is about the creation of a nearly autonomous art making bot that posts to social media platforms. This project was about an exploration of the massive networks that these projects interact with and collaborate with and about a real attempt at letting go of control, trusting, and caring—trusting the collaborators, and caring for (carefully attending to) both the process and the result. The bot was a months-long programming project that was the most complex arrangement I had worked on to that point. It brought into play all of the things I had been working on and with for the past year. It just needed a little nudge from me to get started, and then the network of agents pushed and pulled on each other, added and multiplied what each had to offer. We did and made the most amazing things. Chapter 7 — CONTROL V1 a booklet about care. This is an essay about teams, networks, and finding the thing I was looking for in all of this work and making. The entire process from learning to code simple five and six-line programs in Javascript to working with the most advanced language models available (a university in China just published a paper about a new language model they made that is again a tenfold jump in scale and power from the one I have access to now) has given me new regard for the entire endeavor. I am excited about graphic design again, about what is possible and how we can communicate and grow through this visual and textual making. I have an entirely new outlook on the process of making that is grown out of a place of trust and care. I am not worried about machine learning’s impact on my work. I am excited to see where the team-ups take me/us.Chapter 8 — Speculative Anthropology. This is the concluding chapter and project for this thesis document. This essay is about strange explorations of the latent spaces of machine learning. What can we find when we explore this sort of hidden and near infinite space that these networks allow us access to? This essay imagines a sort of exploration of possibilities never realized, a look at the objects we might find, a speculative anthropology of alternative histories that we might explore and learn from. And while maybe there are more significant concerns and uses of this sort of speculative research, they are not my interests. When I met HAL, I did not want to talk about questions of phenomenology. I wanted to make cool posters and start a cover band. This thesis is not and was never about machine learning or artificial intelligence. I am not going to have a big reveal at the end where I explain that this was all written by a robot and you have been tricked in some manner. These are my human words, but I got to them in relationship with a decidedly nonhuman team of collaborators and makers. It has been important and valuable for me to examine my role in the creative process more deeply, to question what I have taken for granted in my two decades of work in graphic design, to think about these things we designers do and make in strange new ways. Not to confuse the issues with jargon and obtuse readings of ideas but to imagine what might be the results of thinking about our roles in strange ways through odd and unexpected new lenses. What if we are all part of a network and not at the center/top of it? What would that mean to how we work and what we value, to the stories we tell ourselves and each other about the work we do and why we do it? I think that these questions can help us prepare for the changes that machine learning will bring (is already bringing) to our world and our work. The impact of this technology is going to be massive, but it does not need to be devastating or displacing. We don’t have to be gatekeepers; we can be collaborators, with a say in what happens next. <img width="480" height="366" width_o="480" height_o="366" data-src="https://freight.cargo.site/t/original/i/27f7ed853daf8e157853c732fc4ace33b598d3052541cb4589bd1a1f6c57c382/Kent.gif" data-mid="116703208" border="0" alt="The Simpsons. 1994 &ldquo;Deep Space Homer.&rdquo; Fox. February 24." data-caption="&lt;b&gt;The Simpsons. 1994 “Deep Space Homer.” Fox. February 24.&lt;/b&gt;" src="https://freight.cargo.site/w/480/i/27f7ed853daf8e157853c732fc4ace33b598d3052541cb4589bd1a1f6c57c382/Kent.gif" /> Graphic designers might be in a better position than many others who will be and are being affected by this massive change, because we may have enough imagination to see what this new way of making meaning can bring. We can ask important questions about what parts of work and making, even of creativity, might, in fact, be better handled by machines; we can rethink our curriculums to focus on what we can learn to better collaborate with these networks of making instead of trying to compete with them or keep them out of our precious creative spaces. We can loosen our grip on control, accept new forms of making from new collaborators, understand ourselves as one among many, celebrate and multiply in that multitude, delight in what happens next, trust we can make something amazing together, and care for each other—with beauty and courage.“Perhaps all the dragons in our lives are princesses who are only waiting to see us act, just once, with beauty and courage. Perhaps everything that frightens us is, in its deepest essence, something helpless that wants our love.” —Rainer Maria Rilke, Letters to a Young Poet︎︎︎︎︎Next Chapter 1 — Camera Obscura. https://christopherswift.work/Chapter-1-Camera-Obscura Tue, 17 Aug 2021 01:47:46 +0000 CONTROL https://christopherswift.work/Chapter-1-Camera-Obscura <img width="3840" height="2160" width_o="3840" height_o="2160" data-src="https://freight.cargo.site/t/original/i/663d3c9d705fc58f459338f681fbebe48b2f4691f096e545d216fb1470cea6d3/PXL_20201120_202821997.NIGHT.jpg" data-mid="116620150" border="0" alt="PXL_20201120_202821997.NIGHT.jpg Camera Obscura, 2020Digital photograph20 Nov 2020, Friday 15:28 GMT-5:008.3 MP 3840 x 2160f/1.8 4s 4.44mm ISO599Williamstown MA, USA" data-caption="&lt;b&gt;PXL_20201120_202821997.NIGHT.jpg&lt;/b&gt;&lt;br&gt; Camera Obscura, 2020&lt;br&gt;Digital photograph&lt;br&gt;20 Nov 2020, Friday 15:28 GMT-5:00&lt;br&gt;8.3 MP 3840 x 2160&lt;br&gt;f/1.8 4s 4.44mm ISO599&lt;br&gt;Williamstown MA, USA" src="https://freight.cargo.site/w/1000/i/663d3c9d705fc58f459338f681fbebe48b2f4691f096e545d216fb1470cea6d3/PXL_20201120_202821997.NIGHT.jpg" /> Chapter 1 Camera Obscura. A second aspect of my experimental attitude involves speculation, and for me that means asking about the reality of the relations between things, relations that are not dominated by the human experience of those things. That is a hard task, for how do you imagine the relation between a snail and the leaf it is eating (which is perfectly real as a relation) without anthropocentrism, without scientific reductionism, even without language?— Muecke, Stephen. “Motorcycles, Snails, Latour: Criticism without Judgement.” Cultural Studies Review 18.1 (2012): 40-58. Print. A camera obscura creates a projection from light on the other side of an aperture. It shows the outside on the inside. The light that you might typically experience hitting your eyes is instead hitting a wall, a bathtub, a door, or whatever solid surface is there, and then reflects back into your eyes or camera. This adds an extra step, a step that helps create something new and unexpected.This year-plus of lockdowns, shelter-in-place orders, and the sudden forced insideness of pandemic life has in many ways, more and more as I continue to think it through, made the meaning of this camera obscura project that much more significant and intense for me. I live in a small town in a low population area and see very few people (outside of my family) in real life. The images projected on the walls really do, in many ways, match my world. The upside down ephemeral images now seem right; they are an accurate reflection. This year has often felt surreal and incomprehensible.This is how it works: light from outside a black box projects onto the wall opposite the aperture, creating an inverted image of that view. One of the interesting things I had not been considering was the nature of that “wall.” I set up this project in my mostly unused attic bathroom in our temporary on-campus housing, and I had very pragmatic reasons for it. It has only one window (so it is easy to set up the blacked out window; I covered it with cardboard pierced with one small aperture hole); no one in my family really uses this bathroom, so closing off the window doesn’t matter much (I had started this project in my home office but it was unbearable to be in that dark of a room for long); the room is pretty empty so the projected images are not obscured by the objects of our daily lives.Deeper than that, past the pragmatic reasoning, I have made other choices that I had not given much consideration to. I could hang a sheet on that wall to create a clean and simple surface for the projection to show; instead, I am projecting on a wall with a door, a clawfoot bathtub, and a built-in storage unit. My wife commented that the photographs resemble something that David Lynch might make, in that they are surreal, unheimlich, uncomfortable, and sometimes maybe beautiful. The mundane everyday (but also mostly abandoned) space becomes elevated; the space is reconceived and made special in some way. Where a photo of my bathroom’s view of winter trees or a photo of my bathroom wall would not be interesting or worthy of much comment at all, the combination is something new, a bit strange, and strangely interesting. The materials, the process, the documentation, these all work together to make something worthwhile and maybe wonderful. I’m beginning to realize that all of my pandemic-thesis projects are like this. <img width="3840" height="2160" src="https://freight.cargo.site/w/1250/i/6b09c9ba23d25b4947fe137dd724f529e130496b71b4bd6ed886818ae1857d1a/PXL_20201201_170113487.NIGHT.jpg" data-caption="bPXL_20201201_170113487.NIGHT.jpg/bbr Camera Obscura, 2020brDigital photographbr1 Dec 2020, Saturday 12:.1 GMT-5:00br8.3 MP 3840 x 2160brf/1.8 4s 4.44mm ISO599brWilliamstown MA, USA"> The actions, or really lack of actions, needed to make this work—the sitting and waiting for your eyes to adjust to the light/dark of the room and the for the projections to become clear—reminds of a James Turrell piece viewed in a nearly pitch-black room that you have to just sit and wait for your eyes to see. I have entered one of these Turrell Dark Spaces at MASS MoCA, and find viewing it slightly uncomfortable. I start to get bored sitting looking at nothing, but then as I begin to make out something, it becomes clearer and more apparent, and I wonder how I didn’t see it before. The experience is something simple and maybe profound. The creative network of things (light, wall, bench; and then sometimes also eye, brain, me) has been there working together the entire time; it has not needed any audience to activate it in any way.My camera obscura project is a collection and collaboration of objects acting as tools, acting with a sort of agency, and participating in a network of ideas and things and idea things and things that are ideas. Each time I go into the attic bathroom to take these pictures projected light bouncing off walls, or as I sit and wait as my eyes adjust to the dark, to the faint light of this process, I am merely observing something that is happening with or without me present. The light streams and the photons bend and bounce, creating these images whether I can perceive them or not. The light, the cardboard, the enamel of the tub, the paint on the walls, door and cupboards are all part of the network making these images in ways I can’t fully understand, sense, fully grab hold of or in any way define, but that I can be a part of and document some aspect of. Not all of it, but a bit of it. The tip of an iceberg of making. I only need to sit and wait and trust that something worthwhile is happening. <img width="3840" height="2160" src="https://freight.cargo.site/w/1250/i/c080e8452374fc763de3658a6d641eb7c184eb9a8f7a079ef49f4339a0eb5cfd/PXL_20201211_190836297.NIGHT.jpg" data-caption="bPXL_20201211_190836297.NIGHT.jpg /bbr Camera Obscura, 2020brDigital photographbr11 Dec 2020, Friday 10:42 GMT-5:00br8.3 MP 3840 x 2160brf/1.8 4s 4.44mm ISO599brWilliamstown MA, USA"> This is an ephemeral experience; it does not make a record, it does not leave any trace. I have to do that part. To document the experience, you have to use some kind of long exposure camera with something like film. My phone’s camera app has a machine learning enhanced Night Sight setting that functions similarly to a long exposure setting on a film camera.Taking a picture with a camera while sitting inside a camera is an odd experience, like being in your car while traveling on a ferry. While not profound, unusual. When you pay attention to it.The end.︎︎︎︎︎︎NextChapter 2 — Hybrid Posters. https://christopherswift.work/Chapter-2-Hybrid-Posters Tue, 17 Aug 2021 01:47:50 +0000 CONTROL https://christopherswift.work/Chapter-2-Hybrid-Posters <img width="1350" height="2025" width_o="1350" height_o="2025" data-src="https://freight.cargo.site/t/original/i/42b0928d3ac9e005ab55ad809db7d23b0c2f51fa5d29cdae50d3603300633669/Poster-base-for-Theis7.png" data-mid="116620210" border="0" alt="This Space of Time is Organized Hybrid Posters, 2020Digital posterP5JS and Adobe InDesign1350px x 2025px150 PPI" data-caption="&lt;b&gt;This Space of Time is Organized&lt;/b&gt;&lt;br&gt; Hybrid Posters, 2020&lt;br&gt;Digital poster&lt;br&gt;P5JS and Adobe InDesign&lt;br&gt;1350px x 2025px&lt;br&gt;150 PPI" src="https://freight.cargo.site/w/1000/i/42b0928d3ac9e005ab55ad809db7d23b0c2f51fa5d29cdae50d3603300633669/Poster-base-for-Theis7.png" /> Chapter 2 Hybrid Posters. An essay about my early code based projects and attempts to let go of control, and collaborate. In trying to make something new, in trying to define a new relationship with my tools, to unsettle and challenge what I was comfortable with as a maker/designer, I hoped to find something to be excited by. And maybe if I couldn’t find it, I could make it. I was bored of my tools, bored of the traditional outputs of graphic design, bored of how I worked, what I made, and how I saw the things others made. I knew the marks that our tools make—again and again and again—and found little interest, no pleasure, and an absence of surprise or wonder at almost anything I looked at (anything that was in the realm of graphic design anyway). <img width="1350" height="2025" width_o="1350" height_o="2025" data-src="https://freight.cargo.site/t/original/i/eda64c18d7ecdbf2a0efbebe201f7670b3efc7a70e377692f3011e288f5b3740/Poster-base-for-Theis9.png" data-mid="116620208" border="0" alt="This is Finished Now poster Hybrid Posters, 2020Digital posterP5JS and Adobe InDesignText from Silence: Lectures and Writings1350px x 2025px150 PPI" data-caption="&lt;b&gt;This is Finished Now poster&lt;/b&gt;&lt;br&gt; Hybrid Posters, 2020&lt;br&gt;Digital poster&lt;br&gt;P5JS and Adobe InDesign&lt;br&gt;Text from Silence: Lectures and Writings&lt;br&gt;1350px x 2025px&lt;br&gt;150 PPI" src="https://freight.cargo.site/w/1000/i/eda64c18d7ecdbf2a0efbebe201f7670b3efc7a70e377692f3011e288f5b3740/Poster-base-for-Theis9.png" /> When I used to work with letterpress (on my own and while teaching a letterpress class at RISD), I had found a real sense of delight in that tool-designer relationship. It was fun and exciting to act against the weight of the drum physically, to feel and hear the paper crush under the pressure of the roller. To work and make with this massive and imposing machine and be surprised by the results. The new limitations and unknown (to me) possibilities of this work were fantastic. <img width="3480" height="4640" width_o="3480" height_o="4640" data-src="https://freight.cargo.site/t/original/i/f8ea7d1e0bb412658b30ae9f8d8380c120f7ed2abda65be3457d0ed26e4d6883/IMG_20161123_155347.jpg" data-mid="116620180" border="0" alt="Rhode Island School of Design letterpress studio, 2015" data-caption="Rhode Island School of Design letterpress studio, 2015" src="https://freight.cargo.site/w/1000/i/f8ea7d1e0bb412658b30ae9f8d8380c120f7ed2abda65be3457d0ed26e4d6883/IMG_20161123_155347.jpg" /> But I also saw master printers create pages that bored me to my core. The ink “kissing” the page was considered “good” by those who knew what they were doing—counter to the vulgar deep impressions that wedding planning young people and millennial hipsters wanted to see. The limited-edition runs of great American novels or new translations of the Classics that sold on subscriptions to a small number of collecting libraries for thousands of dollars made me angry and annoyed with the people I met in the letterpress community and the types of work they found acceptable and unacceptable. <img width="2048" height="1520" width_o="2048" height_o="1520" data-src="https://freight.cargo.site/t/original/i/80a43b0ec2e3416a58717bd6efc92f480e3df4472be38caa0e7581c93562f7a9/IMG_20151030_143855.jpg" data-mid="116620176" border="0" alt="Rhode Island School of Design letterpress studio, 2015" data-caption="Rhode Island School of Design letterpress studio, 2015" src="https://freight.cargo.site/w/1000/i/80a43b0ec2e3416a58717bd6efc92f480e3df4472be38caa0e7581c93562f7a9/IMG_20151030_143855.jpg" /> The excitement I felt for the possibilities of working with this capital-T design tool, matched and encouraged by the frustration I felt for the snooty and judgement filled rules and traditional outputs it was supposed to be used for, pushed me further into a space of experimentation. I decided to break as many rules as possible, stopping just short of breaking the letterpress itself. I came to seek this same expression, freedom, and novelty in my work with other tools. I started trying to learn code so that I would bend the rules of programs like InDesign. I used sound editing software to edit photographs. I used projectors and lasers to find new ways to interact with new substrates. And when it came time to choose a method and mode of work for my thesis project I decided that the most promising path forward, one that was well-tread and would be the easiest to navigate, was designing with code. I spent hundreds of hours learning to code in JavaScript and Java (for P5JS and Processing specifically). I wanted to find a way to feel that sense of collaboration I had felt with the letterpress again. I wanted to work with my tools in some way, to try and listen to what they wanted, to let them make choices. I had broken the rules with the letterpress and ignored traditional practices in order to get to a new creative space. With code, I could repurpose a program and make it work differently to try to make something new. I could misuse it, break it, and learn from the breaking. I was interested in flouting and breaking rules again, in making things work counter to their intended or “correct” uses. And the space of coding did that; it opened up my creative making, my tool use, in new ways, and allowed me to create new things. But I was still very much in control of the outputs and choices. <img width="4032" height="3024" width_o="4032" height_o="3024" data-src="https://freight.cargo.site/t/original/i/7fff761f57b5967a78b3b15f3853510c20261c542acca09c8ed63c7a8922949e/IMG_20190707_163540.jpg" data-mid="116620188" border="0" alt="Spread from untitled collageChristopher Swift2019" data-caption="&lt;b&gt;Spread from untitled collage&lt;/b&gt;&lt;br&gt;Christopher Swift&lt;br&gt;2019" src="https://freight.cargo.site/w/1000/i/7fff761f57b5967a78b3b15f3853510c20261c542acca09c8ed63c7a8922949e/IMG_20190707_163540.jpg" /> A solution came in exploration of Surrealist collage techniques. The exciting juxtapositions that often stemmed from these chance-based techniques were something I thought could be expressed with code in a new and exciting way. And randomness is a way of giving up control over outputs. The math.random() function (or something very similar in each programing language) was the method I would use to loosen my grip, and try to introduce a sense of agency into my hopeful collaborations with code (code as tool; tool as collaborator). The first steps involved adding a random display element to a coding tool that I could interface with and effect in some manner. I created a set of what I called “strange tools.” Most tended to act in this manner (example); a line was created between two points, where one point’s location on the screen is determined by me (usually through mapping mouse locations) and the other by an x and y coordinate using a random number generated by the program’s random function. I created dozens of these strange tools, each offering variations on this basic functionality. <img width="1025" height="1109" width_o="1025" height_o="1109" data-src="https://freight.cargo.site/t/original/i/0a835197696cb67608e02a6ce165906ffeb78d24361900ad399e9c36aab2009a/Noise-drawing-tests.png" data-mid="117570913" border="0" alt="strange drawing tool with noise seed Hybrid Posters, 2020Digital posterP5JS" data-caption="&lt;b&gt;strange drawing tool with noise seed&lt;/b&gt;&lt;br&gt; Hybrid Posters, 2020&lt;br&gt;Digital poster&lt;br&gt;P5JS" src="https://freight.cargo.site/w/1000/i/0a835197696cb67608e02a6ce165906ffeb78d24361900ad399e9c36aab2009a/Noise-drawing-tests.png" /> This randomness could be applied to almost any aspect of creating an image with code. The dimensions of the canvas or output space, the size and scale of added objects, the number of those objects, the locations of them—these all could be modified in something that looked like tool-agency by way of randomness. The randomness did work to challenge my control over the outputs, but it was constrained. The strange tools typically only reacted to my prompts and did not act without a push of some sort. I was allowing for a kind of messy interaction, but one that I plan and that I, in the end, control. So I pushed a little more, looking for a more authentic and non-hierarchical, even field of collaborative making. I hoped that the exciting juxtapositions of Surrealist collage techniques would create a less controlled output. Randomness was still my way of introducing something that could act outside of my control, but I would attempt to create distance from my inputs in these programs. The various collage techniques (cubomania, étrécissements, photomontage, and triptophraphy) could run as an algorithm of sorts. Each method had variables (i.e., the number of cubes) that could be given an upper and lower limit but be randomly picked by the program as needed. To push these programs further, I made the image selection itself a random process, adding randomness to the URLs used for the image archive sites. Many of these programs only needed me to hit the start button and would otherwise run themselves. With the Surrealist collage programs and the strange tools, I created hundreds of images. They were exciting and unexpected. I developed many other tools and techniques that worked in similar ways towards similar goals. The outputs were excellent, and that really should have been enough. I had created a set of tools that acted with a version of agency that I found compelling and valuable. The collaboration was productive, and I was finding myself often delighted with the outputs—and this is what I wanted; to be surprised and delighted by what I had a hand in making. But I suppose they did not feel like “graphic design” in some way. I didn’t have to try very hard; the designs didn’t communicate anything obvious; they were simple and easy, and graphic design graduate school felt like it demanded more. I needed to show my mastery over the materials; I still felt that I needed to control the output and do the real making, if I was going to call the work mine. <img width="1350" height="2025" width_o="1350" height_o="2025" data-src="https://freight.cargo.site/t/original/i/da5488dc5de39062920004a2e00008d9725768a76cbfa3311389e3a96c848965/Poster-base-for-Theis4.png" data-mid="116620213" border="0" alt="Goal Poster Hybrid Posters, 2020Digital posterP5JS and Adobe InDesign1350px x 2025px150 PPI" data-caption="&lt;b&gt;Goal Poster&lt;/b&gt;&lt;br&gt; Hybrid Posters, 2020&lt;br&gt;Digital poster&lt;br&gt;P5JS and Adobe InDesign&lt;br&gt;1350px x 2025px&lt;br&gt;150 PPI" src="https://freight.cargo.site/w/1000/i/da5488dc5de39062920004a2e00008d9725768a76cbfa3311389e3a96c848965/Poster-base-for-Theis4.png" /> <img width="1350" height="2025" width_o="1350" height_o="2025" data-src="https://freight.cargo.site/t/original/i/1d6a66e1646a9a1e5d077951a64b0f81b5cec484c36951a3c93c0f08239b94e3/Poster-base-for-Theis2.png" data-mid="116620215" border="0" alt="There is no such thing as silence. Hybrid Posters, 2020Digital posterP5JS and Adobe InDesign1350px x 2025px150 PPI" data-caption="&lt;b&gt;There is no such thing as silence.&lt;/b&gt;&lt;br&gt; Hybrid Posters, 2020&lt;br&gt;Digital poster&lt;br&gt;P5JS and Adobe InDesign&lt;br&gt;1350px x 2025px&lt;br&gt;150 PPI" src="https://freight.cargo.site/w/1000/i/1d6a66e1646a9a1e5d077951a64b0f81b5cec484c36951a3c93c0f08239b94e3/Poster-base-for-Theis2.png" /> <img width="1350" height="2025" width_o="1350" height_o="2025" data-src="https://freight.cargo.site/t/original/i/e2f02581ef730a4371eb146adda54e616b8fc4472f956b4e40476af6cee8f322/Poster-base-for-Theis.png" data-mid="116620189" border="0" alt="Lecture on Nothing Hybrid Posters, 2020Digital posterP5JS and Adobe InDesign1350px x 2025px150 PPI" data-caption="&lt;b&gt;Lecture on Nothing&lt;/b&gt;&lt;br&gt; Hybrid Posters, 2020&lt;br&gt;Digital poster&lt;br&gt;P5JS and Adobe InDesign&lt;br&gt;1350px x 2025px&lt;br&gt;150 PPI" src="https://freight.cargo.site/w/1000/i/e2f02581ef730a4371eb146adda54e616b8fc4472f956b4e40476af6cee8f322/Poster-base-for-Theis.png" /> In the final outputs of these projects, I treated the individual images as elements of a larger and more complex system. I created a set of hybrid posters featuring the collaboratively generated objects working together in various ways. Again, I exerted my control, this time as editor and curator. I determined the value and success of each of the elements and chose if I would include it in the final design. They are beautiful, a successful and prolific creative output, and maybe they are collaborative (with code/tool as collaborator). But they are still very much made by me, under my control as desinger-god working behind the screen to make a hopefully beautiful thing. And so, onto the next. The end. ︎︎︎︎︎︎P︎Next Chapter 3 — A Careful Trust / Zine Collaborations https://christopherswift.work/Chapter-3-Zines-and-care Tue, 17 Aug 2021 01:47:54 +0000 CONTROL https://christopherswift.work/Chapter-3-Zines-and-care <img width="3333" height="5417" width_o="3333" height_o="5417" data-src="https://freight.cargo.site/t/original/i/27fe7e4dc6731ffb0fddea431d70db1f2d303649d716d75970918b634f3f4c8b/Levy-Walker-Zine--2-1-copy.png" data-mid="116620238" border="0" alt="The Case for Deeper Readings of the Arts and Crafts Writings and Theories (Sept 3, 2020 at 10:57 PM)Levy Walker Generative Zine, 2020PDF ZineProcessing11 pages" data-caption="&lt;b&gt;The Case for Deeper Readings of the Arts and Crafts Writings and Theories (Sept 3, 2020 at 10:57 PM)&lt;/b&gt;&lt;br&gt;Levy Walker Generative Zine, 2020&lt;br&gt;PDF Zine&lt;br&gt;Processing&lt;br&gt;11 pages" src="https://freight.cargo.site/w/1000/i/27fe7e4dc6731ffb0fddea431d70db1f2d303649d716d75970918b634f3f4c8b/Levy-Walker-Zine--2-1-copy.png" /> Chapter 3 A Careful Trust / Zine Collaborations. An essay about the creation of a program that generates zines, and the first explorations of what moving from control to care might mean.The final project I created during my second semester of work is a zine generating collaboration program that pulled together all of the technical code-based learning of the previous six months, and the writing of the six months before that (my first semester was spent writing with Natalia). This generative zine project is an attempt to work toward sharing creative credit for the projects I work on; pushing forward my initial interest in collaborating with humans, and more and more with non-humans—with my design tools. To make these generative zines I assembled the various parts—tools, ideas, data sets—set some parameters, and gave it a nudge forward. I produced three versions of the program, all coded in Processing.The first uses a technique called ray-casting to display a simplified example of how light beams are cast around a space interacting with objects. Each zine page has a unique space and arrangement of various sized rectangles and a randomly placed circle representing the light source. The zine’s text comes from essays I wrote during my first semester, on a range of graphic design topics. Each page has one paragraph of an essay. The placement and dimensions of each text block in this ray-caster version are based on a randomly generated number with a minimum width. Each time the program runs and the network of things collaborates (text, image, page shape, code) it creates a unique zine. The range of possibilities is vast. The outcomes are PDF files: they are final, they can’t be edited, they are a collected output and a completed design object. The second version of the zine collaboration contains a selected (by me) essay I had written, alongside randomly selected, scaled, and placed photographs. Each page again holds one paragraph; the dimensions of the text block are determined by a version of randomness called Perlin Noise. This kind of number generation picks a random number based on inputs from the previous number, generating something that looks a bit like a wave moving back and forth through space. In theory, these text blocks might seem more related in shape and area than with the previous total randomness of the first zine generator. The locations of the text blocks and the folios rely on a version of a random walker. A random walker is a math-based example of random motion where each step can either be up, down, left or right. At each step, the choice is made again, creating something that has an uncanny naturalness to it, something planned but in a way or scale that is unknowable to me; something like the path of vines that have grown up a wall, or the spread of moss. The version of a random walker that I set up in this arrangement is called a Levy walker. This kind of walker uses a model based on a foraging animal in nature. The walker stays in one area moving around in small steps and then makes large jumps to a new location to spend some time there looking around, foraging, sniffing, whatever it might be imagined to be doing, and then doing it again in the new space. The photographs are linked from unsplash.com (a free website with an extensive archive of contemporary photos), because this website’s specific URL structure (ex https://source.unsplash.com/random/300x500) allows a random number to be added in the x and y values. Again in this version of collected inputs, the final piece is unreviewed, unedited, unchanged. Nothing is approved; the collaboration with the code is trusted to make something worthwhile. The third version of the zine project combines aspects of the previous two. Each page’s text block dimensions and location are generated in some variation of randomness. Some rectangles and one circle are added to each page with almost every measurable aspect randomly generated. A similar photo selection is used, but all of the photos are converted to grayscale (converted by the program, because I told it to do that). Each of these collections of ideas, methods, and actions produce a unique output: each and every zine is different from the last. Each is unique; changed; they are new. They repeat ideas or themes or aesthetics, and each time the program runs they are made anew, each run creating novelty. The space for this novelty is opened up and made possible as my expectations for what the outcome should be, what the page should look like, are erased, overridden (I’m sorry Dave, I’m afraid I can’t do that)—or at least dimmed a little, as my control over the other actors in this production becomes looser, and my trust that we are making something of worth in this weird collaboration is slowly but importantly strengthened. One of the aspects of this project that I find intriguing is the idea of potential possibilities: the many, many possible outcomes. I imagine the network like an atom—a collection of probability clouds, each element existing within its specific orbiting space. Like an atom, maybe, our observation of it changes it; we document it in a candid and unplanned manner—a series of snapshots of a river flowing, each one of the same river, but each different from the last and the next shot—potential, or real. A complete inventory of the network of actors involved in the creation of my zine generation programs would, likely, in the end, stretch out to touch an awesome number of inputs spread out across disciplines, technologies, spaces, and people. The center of this project (as observed by me) is the program Processing (used to organize all of the elements of the program), the programing language Java (the language that Processing runs on), the website unsplash.com (for image selection), my essays (the written content of each of the programs), and the reader/viewer. Each of those elements is deeply complex, with rich histories and complex networks of relationships connecting to more and more similarly complex networks. Things reveal themselves to be more and more out of my control.When considering this kind of collaborative making from a vantage point that decenters the graphic designer out of their (my) role as primary and sole author/maker, we (I) might be able to see ourselves as one among many. Sometimes small in context, occasionally massive, floating in an ocean affecting and affected by currents and forces we do not always see. But in this floating understanding, this unmoored space of ideas and things, maybe we can see that this is not a new or restructured hierarchy that has diminished us in any way, but simply a new view, cleared of our sentimental human-centric expectations, that values trust in collaboration and makes in relationships with our rediscovered collaborators. The end.︎︎︎︎︎NextChapter 4 — Dragons and Princesses. https://christopherswift.work/Chapter-4-Dragons-and-Princesses Tue, 17 Aug 2021 01:47:56 +0000 CONTROL https://christopherswift.work/Chapter-4-Dragons-and-Princesses <img width="1532" height="862" width_o="1532" height_o="862" data-src="https://freight.cargo.site/t/original/i/989527f13139760519bda389ea6903f25a36b56ebf10078d67a43c396decb8e1/Miyazaki1.jpeg" data-mid="116933652" border="0" src="https://freight.cargo.site/w/1000/i/989527f13139760519bda389ea6903f25a36b56ebf10078d67a43c396decb8e1/Miyazaki1.jpeg" /> <img width="1525" height="858" width_o="1525" height_o="858" data-src="https://freight.cargo.site/t/original/i/9fa5d70f968edf6b3c7cd8a8063ddc767a8d90d989aea48844e1a3a2f93a616b/Miyazaki2.jpeg" data-mid="116933653" border="0" src="https://freight.cargo.site/w/1000/i/9fa5d70f968edf6b3c7cd8a8063ddc767a8d90d989aea48844e1a3a2f93a616b/Miyazaki2.jpeg" /> <img width="1524" height="857" width_o="1524" height_o="857" data-src="https://freight.cargo.site/t/original/i/509a09e738c8f67d3811a6d37bb70c587b6d005ff57633929e3f2047c59587e2/Miyazaki3.jpeg" data-mid="116933654" border="0" src="https://freight.cargo.site/w/1000/i/509a09e738c8f67d3811a6d37bb70c587b6d005ff57633929e3f2047c59587e2/Miyazaki3.jpeg" /> <img width="1501" height="844" width_o="1501" height_o="844" data-src="https://freight.cargo.site/t/original/i/1b41e1702213350772344e69305bcbafd086569c5a91870ec4da95448643e535/Miyazaki4.jpeg" data-mid="116933655" border="0" src="https://freight.cargo.site/w/1000/i/1b41e1702213350772344e69305bcbafd086569c5a91870ec4da95448643e535/Miyazaki4.jpeg" /> Chapter 4 Dragons and Princesses. “Perhaps all the dragons in our lives are princesses who are only waiting to see us act, just once, with beauty and courage. Perhaps everything that frightens us is, in its deepest essence, something helpless that wants our love.”― Rainer Maria Rilke, Letters to a Young Poet This essay covers a series of failed collaborations, confusing princesses for dragons. In my attempts at unsettling my role as the natural and assumed center of the creative process, I added chance and forms of randomness to my network of tools. I included randomly selected lines of some texts, and loosened my grip on the specific numbers that needed to be included in the programs that affected the outcomes. I let go, but only a little, only within boundaries that I very deliberately set. Images were randomly selected (but from an archive I selected), the text block was randomly placed (but with parameters to stay fully on the page), the dimensions of the text block were randomly selected (but within a range that would prevent negative numbers and therefore backward text), the colors, the shape of the page, the overall aesthetic; all of it was at my direction. I had let go to some degree, I had loosened my grip, but it was still my show; the letting go was still well within my control. The programs that I had been writing were self-contained and narrow in what was required of them. They incorporated code from various communities, employing solutions other coders had developed to problems I was facing. They occasionally reached out into the internet to download a photograph, but they generally existed entirely on my computer. What was achievable with chance and randomness was fantastic, and I had only really begun working in that space, but what I hoped for was something past chance. I saw the possibility to move past randomness towards real collaboration in a new set of tools: machine learning and artificial intelligence. I saw various ways to link up my projects—to extended the creative network of agented actors, to redefine what a collaborator was—to the machine learning tools that Google and others had been developing was being developed by groups like ML5. Using and collaborating with these tools I saw an opportunity to create work with inputs that had much more say than math.random() had been able to express. &lt;HI PERSON&gt; <img width="967" height="1183" width_o="967" height_o="1183" data-src="https://freight.cargo.site/t/original/i/8536b09f0f38f5d1898cef31fce2a0a250da4c1b85e4498caddcda281c1b1aa3/BAG-Project10.png" data-mid="116620249" border="0" alt="buckleBad Ad Generator, 2020DigitalP5JS, ML5, and ImageNet" data-caption="&lt;b&gt;buckle&lt;/b&gt;&lt;br&gt;Bad Ad Generator, 2020&lt;br&gt;Digital&lt;br&gt;P5JS, ML5, and ImageNet" src="https://freight.cargo.site/w/967/i/8536b09f0f38f5d1898cef31fce2a0a250da4c1b85e4498caddcda281c1b1aa3/BAG-Project10.png" /> The first project was a failure, but I had set it up to fail. It was a failure in the sense that the output was clearly nonsensical, and I had set it up to fail mostly to make fun of it. The Bad Art Generator project uses a machine learning dataset called ImageNet (ImageNet is a massive collection of images tagged by hand that was used to train an image identifying algorithm) and a randomly selected photograph to create the output. The program downloads a random picture from unsplash.com and then the algorithm uses the ImageNet dataset to attempt to identify the subject(s) of the photo. What the algorithm can do is actually fantastic; its ability to even remotely identify the content and subject of an image it has never encountered before is a huge accomplishment. But it’s also often stupid and wrong, ridiculously so. It reminds me of a scene from The Simpsons episode “Last Exit to Springfield” (Season 4 episode 17): I am in the role of Mr. Burns chastising his monkeys for grammar errors. The program’s image identification is often wrong; it is hamfisted in its reductions and assumptions, lacks any nuance or cultural understanding, and seems hopelessly foolish. It can be all of those things. It can also make something like a profound statement, making a connection I had never made, seeing something new and different in an image I did not care about, or think twice of. <img width="967" height="1048" width_o="967" height_o="1048" data-src="https://freight.cargo.site/t/original/i/ce2ae8aa9193b1c93d28938a75ecc0871538154872d53a8fe515e00ff89dc5d0/BAG-Project9.png" data-mid="116620250" border="0" alt="coil, spiral, volute, whorl, helixBad Ad Generator, 2020DigitalP5JS, ML5, amd ImageNet" data-caption="&lt;b&gt;coil, spiral, volute, whorl, helix&lt;/b&gt;&lt;br&gt;Bad Ad Generator, 2020&lt;br&gt;Digital&lt;br&gt;P5JS, ML5, amd ImageNet" src="https://freight.cargo.site/w/967/i/ce2ae8aa9193b1c93d28938a75ecc0871538154872d53a8fe515e00ff89dc5d0/BAG-Project9.png" /> This was my first exploration of a real letting go, of something like a collaboration as I have come to understand it. The implications of this scared me more than I had thought it would. The collaboration was there; I could have chosen to trust the process, trust the network, trust that we were going to make something exciting and new. Instead, I withdrew that trust and turned to easy laughs at the expense of the nonhuman I claimed to be collaborating with. I mocked it for not being perfect and sheltered myself from caring about the outcome by making its failure the point. The text at the top that reads “hi person, buy this” was decided on and added in by me (not generated by the code) in a mocking fashion, using the bland and non-specific language that can make ImageNet sound silly. “Buy this” was also used to make the output seem clunky, crude, and unrefined (the opposite of what I want people to think of my clever and insightful work.) I then dressed it all up in a sort of youthful pose of something that looks like graphic design. The acid green, the stroked text, the system default Helvetica; a bunch of graphic design looking stuff to distract a viewer from what I had actually done and my intent. <img width="967" height="1183" width_o="967" height_o="1183" data-src="https://freight.cargo.site/t/original/i/0e6b8802ab046c3d2cff50ca9a7ef982d7e9c185d235558410e96ec0e3cc30cd/BAG-Project13.png" data-mid="116620246" border="0" alt="poleBad Ad Generator, 2020DigitalP5JS, ML5, and ImageNet" data-caption="&lt;b&gt;pole&lt;/b&gt;&lt;br&gt;Bad Ad Generator, 2020&lt;br&gt;Digital&lt;br&gt;P5JS, ML5, and ImageNet" src="https://freight.cargo.site/w/967/i/0e6b8802ab046c3d2cff50ca9a7ef982d7e9c185d235558410e96ec0e3cc30cd/BAG-Project13.png" /> The technical aspects of the project are a very teamwork oriented back and forth communication (the team being me, the code I wrote, the image archive unsplash, and the machine learning dataset ImageNet). The code adds a random number to the URL that is passed to the image archive site, and then downloads the photo. ImageNet then makes a guess about the content of the image and returns a text array of likely terms and percentages related to that guess. The program then takes that text information and determines the maximum size of the text in the font I selected to fit on the final output size (the percentages are ignored). The result is an intentionally terrible advertisement. If this project succeeds at something it’s making fun of AI, and also capitalism. OBJECT DETECTOR LOOKING AT ARTS <img width="900" height="900" width_o="900" height_o="900" data-src="https://freight.cargo.site/t/original/i/976e063f149d2faa8e0c7dca0ff90a22576855bd8cabb8d943ca6067cfec1b88/download-10.png" data-mid="116620271" border="0" alt="A Goldsmith in his Shop + ImageNetObject Detector Looking at Arts, 2020DigitalP5JS, ML5, and ImageNet" data-caption="&lt;b&gt;A Goldsmith in his Shop + ImageNet&lt;/b&gt;&lt;br&gt;Object Detector Looking at Arts, 2020&lt;br&gt;Digital&lt;br&gt;P5JS, ML5, and ImageNet" src="https://freight.cargo.site/w/900/i/976e063f149d2faa8e0c7dca0ff90a22576855bd8cabb8d943ca6067cfec1b88/download-10.png" /> This was an experiment in trust with the network and its actors/objects. In these projects I aimed the image selection at the MET’s online database of images. In the two versions discussed here I used ImageNet to run an image classifier in one and PoseNet (which attempts to build out a wireframe model of a person based on one image) in the other. In this project I never produced a final output that I would consider done, I abandoned the project before I got that far along. <img width="872" height="1200" width_o="872" height_o="1200" data-src="https://freight.cargo.site/t/original/i/f0b36d1bb7fcbc5fbe11afa14c5981555dab659b1b10739683434dbfad422d81/download-12.png" data-mid="116620269" border="0" alt="The Little Fourteen-Year-Old Dancer + ImageNetObject Detector Looking at Arts, 2020DigitalP5JS, ML5, and ImageNet" data-caption="&lt;b&gt;The Little Fourteen-Year-Old Dancer + ImageNet&lt;/b&gt;&lt;br&gt;Object Detector Looking at Arts, 2020&lt;br&gt;Digital&lt;br&gt;P5JS, ML5, and ImageNet" src="https://freight.cargo.site/w/872/i/f0b36d1bb7fcbc5fbe11afa14c5981555dab659b1b10739683434dbfad422d81/download-12.png" /> These tools were fascinating to be using. Not many designers seemed to be working in this space, and it felt somewhat unexplored; it felt like I could try something genuinely new. But I was also afraid that in a new space where I could try and create something new I could also legitimately fail. In that fear of real failure, I again took control away from the network and my tool-collaborators. I still did not trust them. I was still testing them, and wary of them. I was looking for and hoping to call them out on their failures. I secretly hoped to show that my humanness meant something more when looking at art, that I would see beauty and be free of judgment about the limits of what is acceptable in shape and form. I thought I would catch the network in a compromised ethical space making assumptions and categorizations that would show that it was, in fact, monstrous and bad. I assumed AI and machine learning were dragons, and that my work would show that I was right not to trust in it. It would show that I was right to pull back my care, to take care, to tread carefully. Unsurprisingly I got nowhere. FACEAPI HIERARCHY PROJECT – HEADLINE POSTER. <img width="981" height="740" width_o="981" height_o="740" data-src="https://freight.cargo.site/t/original/i/741c91d4969995bef083e5462b654c6146e1711d568767908b6fff0212704397/Screen-Shot-2021-06-15-at-3.37.46-PM.png" data-mid="116620273" border="0" alt="Headline poster generatoroster Generator, 2020DigitalP5JS, ML5" data-caption="&lt;b&gt;Headline poster generator&lt;/b&gt;&lt;br&gt;oster Generator, 2020&lt;br&gt;Digital&lt;br&gt;P5JS, ML5" src="https://freight.cargo.site/w/981/i/741c91d4969995bef083e5462b654c6146e1711d568767908b6fff0212704397/Screen-Shot-2021-06-15-at-3.37.46-PM.png" /> I abandoned this project because I found it to be too ethically fraught. But it really raises a lot of these questions about trust and care in our collaborative networks. I withdrew from the technologies due to a lack of care and a lack of trust in what it was doing. I could not find (at the time) anything of value in this network. I guess you can’t care about everything, but I suppose that if you can, holding that trust and care should be your aim. Then you are at least prepared for some type of negative result. Maybe if Victor Frankenstein held tha belief that he should have cared for and trusted, in some manner, his creation then he would have understood its response better. The FaceAPI Javascript module I used was ported for use in P5JS by the community group ML5js.org. This module is trained on images of faces to detect and predict the location of landmarks on people’s faces (like noses or eyebrows or mouths etc.). My initial project idea was to make a poster that would be bespoke to the viewer. Different parts of the poster’s content that rely on number inputs, such as type height or leading or location, would pull the information from values generated by the mapping of the module. That was the initial plan; I had not given the details a lot of thought. It was possible; I had not seen it before, it would be a good showcase of the collaboration. ML5JS is a progressive and caring community. They are committed to a sort of radical transparency about the work they create and share. They have introduced a version of a biography that they include with each tool to let people interested in engaging with those tools have a fuller understanding of them. For FaceAPI, by default, they did not implement the complete code as it was developed. “The ml5.js implementation of face-api does not support expressions, age or gender estimation.” These aspects of the tool are so flawed in concept and implantation they have chosen to avoid them, but not to retreat fully from the relationship. They have chosen to spend the time and energy to care for the network, to see possibility, to maybe create something of value. Even with this limited and cared for implantation of FaceAPI I pulled back. I abandoned the network and retreated to ethically solid ground. The first thing I built was the headline function. Using your camera, the module would measure the distance from the bottom point of your top lip to the top point of your bottom lip, and then it would take that value and create a text-height value to apply to the Headline (in this case, it is the placeholder text that reads Headline.) The implications of what I was going to have to do next occurred to me at that point. I was going to have to give values to different measurements from the faces of audience members participating in the creation of the poster. The idea of giving a literal value to aspects of facial features was enough to end the project at that point. I could find no value in the algorithm. Its flaws seemed unfixable. I often think about this project. I walked away from it for being a monster in my eyes. My knee-jerk reaction was to pull away and dismiss it as broken and flawed. But what the community at ML5JS does is more like the trust and care, the careful and caring trust, that I have come to embrace in my current work with machine learning. They have worked with technology; they have cared for it and made it better. The poet Rainer Maria Rilke once wrote, “Perhaps all the dragons in our lives are princesses who are only waiting to see us act, just once, with beauty and courage. Perhaps everything that frightens us is, in its deepest essence, something helpless that wants our love.” I often think about this project, and I think about that idea of dragons that are really princesses, of monsters that actually just waiting for us, but unloved—and I wonder about the dragon I saw there and feel like I need to try again. I need to be open to the possibilities that come with keeping doors open, even just a crack. The end. ︎︎︎︎︎NextChapter 5 — Floating on Oceans. https://christopherswift.work/Chapter-5-Floating-on-Oceans Tue, 17 Aug 2021 01:47:59 +0000 CONTROL https://christopherswift.work/Chapter-5-Floating-on-Oceans <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/37cc86b32e5f7a04e82395170cb8a82259b6c3d690904da7f1c1b46f2f9ed024/img000000028.jpg" data-mid="116620336" border="0" alt="img000000029.jpgRunwayML + Trendlist Typographic Posters 1, 2020DigitalP512 x 512px digital poster" data-caption="&lt;b&gt;img000000029.jpg&lt;/b&gt;&lt;br&gt;RunwayML + Trendlist Typographic Posters 1, 2020&lt;br&gt;Digital&lt;br&gt;P512 x 512px digital poster" src="https://freight.cargo.site/w/1000/i/37cc86b32e5f7a04e82395170cb8a82259b6c3d690904da7f1c1b46f2f9ed024/img000000028.jpg" /> Chapter 5 Floating on Oceans. “ It’s like I’m reading a book, and it’s a book I deeply love, but I’m reading it slowly now so the words are really far apart and the spaces between the words are almost infinite.”― Samantha, Her This essay covers a series of amazing collaborations and leaps of creativity. Machine learning programs broadly fall into two categories, detection/classification or generative. Algorithms like faceAPI and poseNet that I had worked with in previous projects are primarily detection models. Those models had led me to ways of thinking that were non-creative, judgmental, strict, conservative, and mean-spirited in nature. I did not trust the biographies and histories of them, the ideas behind and controlling them, and I did not trust that they could be used for anything worthwhile. They seemed to lead to diminishing and critical spaces, towards a type of control and structuring that I find to be antithetical to a creative, trusting, and caring collaboration. The other broad type of generative algorithm is almost exactly the opposite. It is wild, massive, complex, free, and untamed. Working with generative machine learning was something entirely new. I did not know what I was looking at most of the time. I deployed a high-level machine learning algorithm, filled it up with modern graphic design and film examples, and got lost in what it created with those inputs. The generative aspect of machine learning does something like creativity, but a version of creativity that makes the word seem almost absurd to use. It is creative, like waves in the ocean are creative. But it is also full of agency, as waves in the ocean are full of agency. Machine learning does something that I can tangentially refer to as creative and not as an insult; I truly don’t have the vocabulary or knowledge to fully describe what is happening. I do know that it is not like other tools I have encountered. It is not like the beauty I can find in outputs of advanced math or the surprise and delight at a randomly juxtaposed pair of cut-up images in a collage. There is something that feels awesome, profound, exciting, overwhelming. And really, really big. <img width="2048" height="1333" width_o="2048" height_o="1333" data-src="https://freight.cargo.site/t/original/i/62b6e0530bcbe4affdd719a9825225d40641de4d4ebebe67d07f2ed499ce5432/gettyimages-502246457-2048x2048.jpeg" data-mid="117603891" border="0" alt="Picture this: Jeremy Lynch displays photographs he says he developed using only the polluted water of Lake Ontario.The worse the water, the better the results.Spremo, BorisPicture, 1990,English Rights and Licenses Toronto Star License Provenance From the Toronto Star Archives" data-caption="&lt;b&gt;Picture this: Jeremy Lynch displays photographs he says he developed using only the polluted water of Lake Ontario.&lt;/b&gt;&lt;br&gt;The worse the water, the better the results.&lt;br&gt;Spremo, Boris&lt;br&gt;Picture, 1990,&lt;br&gt;English Rights and Licenses Toronto Star License Provenance From the Toronto Star Archives" src="https://freight.cargo.site/w/1000/i/62b6e0530bcbe4affdd719a9825225d40641de4d4ebebe67d07f2ed499ce5432/gettyimages-502246457-2048x2048.jpeg" /> In 1993 I saw an art show that featured the effects of what would later come to be referred to as the Anthropocene. The measurable, “unnatural” impacts that humans have had on the world. One image showed the decayed remnants of a water bird of some sort that had ingested large amounts of plastic. The bird’s body, now reclaimed mainly by the surrounding environment and the rough shape of the bird in a pile of plastic that will outlive everyone. Some of these images have stuck with me for my entire life, including a series of photographs printed with a film that had been developed in the waters of Lake Ontario. A photography student, Jeremy Lynch, developed the photos in heavily polluted areas of the lake water in downtown Toronto. These projects were my first (sort of) realization or exposure to seeing and thinking about a network that did not center around humans, or me, almost at all. The network of agents at play in the waters of Lake Ontario’s Toronto shores existed without any consideration of me. The chemicals and currents, the temperatures and international trade agreements, the rusting ships in the water, the closing auto plants across the lake in Detroit—they all interacted on various scales in various ways in networks of action and agency that I was only a small part of, if at all. It was like a speculative poem about the complex relationships of these nonhuman actors, with the photographer (Lynch) as only a small part of his project. The way I understand neural networks to function is like this. I provide a data set to the algorithm, such as a series of photos of myself. In some of the pictures I have my hand raised, in some I don’t. The algorithm detects differences in those images (hand or no hand), and then it determines a measurable contrasting aspect (again, hand/no hand). I can then show the program a new image it has never seen of me, and it will try and determine if my hand is raised or not. What it is actually measuring is in a black box that I don’t understand, but for this example, the algorithm can be thought to be seeing an aspect of the image that is along one dimension. The hands in the new images are either up or down. The machine learning models that are used in generative adversarial networks are in an n-dimensional space that is 512 parameters or 512D. The computer science of it all is beyond my understanding, but I gather that the computer is able to consider the various datasets it is being trained on in a way that is considerably more complex than I am able to do. What it is doing inside of that black box is an area of research the people are working on explaining, with the idea that it would be best if we had an idea about how this all worked. But this is like exploring and explaining the oceans; they are vast and complex and maybe only understandable in metaphor. In the book What Algorithms Want by Ed Finn, interactions with machine learning are described with various metaphors of a person floating in the ocean. A person can swim on its surface, dive under that water briefly, or float on its surface in a boat. In doing so, the person can interact with its surface (or near-surface); they can smell and taste it, they can see the color of the water and the waves cresting and falling around them, but they can only interact with a very small aspect of the ocean directly. The rest, the vastness and unknowable teeming mass of it, has to be understood through metaphor. The scale is awesome. Awesome in the staggering way. An object that defies simple descriptions and that can only be seen through a lens of metaphor. The speed with which this ocean moves is equally humbling. A universe of possibilities made and unmade in spaces of time so narrow that we can’t experience them as discrete packets. The speed and complexity of the algorithmic work of generative AI machines is staggeringly fast. When the technologies and algorithms of High-Frequency trading (HFT) are explored, researchers find that the programs are mostly not doing anything. The speed at which they do the work of the stock trading is so fast that they are hard to detect when seen at a human scale. Near the end of the 2013 film Her by Spike Jonze, the AI Samantha says to Theodore: “It’s like I’m reading a book, and it’s a book I deeply love, but I’m reading it slowly now so the words are really far apart and the spaces between the words are almost infinite. I can still feel you and the words of our story, but it’s in this endless space between the words that I’m finding myself now. It’s a place that’s not of the physical world—it’s where everything else is that I didn’t even know existed. I love you so much, but this is where I am now. This is who I am now. And I need you to let me go. As much as I want to, I can’t live in your book anymore.” This speculative agency of the machine in Her gives another view and set of metaphors about interaction with an ocean, about the vastly different ways we might interact with the machines (but also maybe how we might imagine we interact with almost everything.) The spaces between the words, like the “down-time” of the HFT algorithms, give us a way to understand the scale of the complexity, scope, and possibility of these tools. Working with the generative machine learning algorithms helped me to take leaps of creativity and imagination into spaces I had not seen, or thought to look for, before. Generative Adversarial Networks (GANs) — developed in 2014 by Ian Goodfellow — are a type of machine learning model that uses two sub-models to train against each other. One of the models attempts to create something new that can trick the second model’s authentication, the other tries to test if the object is real or fake. They work back and forth, refining the quality of the fake and of the test over and over. The parameters of the creation and of the testing are enormous and for the most part not understandable by humans. These tools are very complex, but a few WYSIWYG style applications have been developed recently. My early projects working with GANs used the tools developed by RunwayML that make the process of GAN development a lot easier. I created three main projects with GANs at this stage in my thesis work. The systems I used for these early generative machine learning projects required a data set to train on. The initial data would be used by the testing sub model to learn what sorts of parameters it should look for. The creative sub model would create an image (it usually starts with a sort of grainy and blurry color gradient of random colors and intensities) to try and get it past the testing model. Developing the dataset is a very labor intensive task. Ideally the training set is a structurally similar image with the same dimensions and roughly the same figure-ground relationship. The most famous of these data sets (used to create StyleGAN) is a large set of photos of peoples faces. They are all looking at the camera, the images are cropped in such a way that each person’s eyes are in the same location and their heads take up roughly the same amount of space in the square image. In my excitement I did not do a lot (any?) of this prep work. I wanted to see what the machines could do. I was still very sceptical of what was possible, but also curious and eager to test it out. To create my dataset I downloaded every photo from the website trendlist.org (this is referred to as “scraping” and is a legally dubious method for image gathering.) My intention was to explore what the algorithm could do with this varied dataset. Could it make something “good”? Would it generate new art that I would consider to be of value? <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/c5d21eb0b6187cc5c8e7b568c0fcfaa7266d8b223a598b7da29a4be5f56bfa81/img000000040.jpg" data-mid="116620274" border="0" data-scale="66" alt="caption&quot;img000000029.jpgRunwayML + Trendlist Typographic Posters 1, 2020DigitalP512 x 512px digital poster&quot;" data-caption="caption&quot;&lt;b&gt;img000000029.jpg&lt;/b&gt;&lt;br&gt;RunwayML + Trendlist Typographic Posters 1, 2020&lt;br&gt;Digital&lt;br&gt;P512 x 512px digital poster&quot;" src="https://freight.cargo.site/w/1000/i/c5d21eb0b6187cc5c8e7b568c0fcfaa7266d8b223a598b7da29a4be5f56bfa81/img000000040.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/ab6979876587f80b41c31415bab662400a92797c9e648922a7f117b5c78f56b9/img000000041.jpg" data-mid="116620275" border="0" 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src="https://freight.cargo.site/w/1000/i/b78b8975c770c92e99ee57b43521a421f8ff478e069142bd6de2685e3291e517/img000000011.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/7d5413e7330b6742c46d0988568397a93cfbe99ab7aac9de6e683c1af05e8a96/img000000012.jpg" data-mid="116620301" border="0" src="https://freight.cargo.site/w/1000/i/7d5413e7330b6742c46d0988568397a93cfbe99ab7aac9de6e683c1af05e8a96/img000000012.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/fc7c8c903b2befe552f2852d4c1597fd2b040ac69254acd8ce98a8ff64232e77/img000000013.jpg" data-mid="116620302" border="0" src="https://freight.cargo.site/w/1000/i/fc7c8c903b2befe552f2852d4c1597fd2b040ac69254acd8ce98a8ff64232e77/img000000013.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/52c3dc9ee2b1b7619eb57feba1e097d6594075380e2fa8ab1160f173b7a35930/img000000014.jpg" data-mid="116620303" border="0" src="https://freight.cargo.site/w/1000/i/52c3dc9ee2b1b7619eb57feba1e097d6594075380e2fa8ab1160f173b7a35930/img000000014.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/e01a3dc4493bb95f5a7d359ba1f4ebaa8c4cf6a90084acf9d8b85b4a535efdc2/img000000015.jpg" data-mid="116620304" border="0" src="https://freight.cargo.site/w/1000/i/e01a3dc4493bb95f5a7d359ba1f4ebaa8c4cf6a90084acf9d8b85b4a535efdc2/img000000015.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/7babf071d11cf168f9d34ab0462e87b9960413cd03531dc8c086ad8ddc277485/img000000016.jpg" data-mid="116620305" border="0" src="https://freight.cargo.site/w/1000/i/7babf071d11cf168f9d34ab0462e87b9960413cd03531dc8c086ad8ddc277485/img000000016.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/e83789b9fc0554f2989e820dcddc3fb97ea6d85729bcbaf691472af6fce040ce/img000000017.jpg" data-mid="116620306" border="0" src="https://freight.cargo.site/w/1000/i/e83789b9fc0554f2989e820dcddc3fb97ea6d85729bcbaf691472af6fce040ce/img000000017.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/2b8b172b6c252473651dde80c0eedfd4e1f6c9e18ccb414a4753c35b1762c98e/img000000018.jpg" data-mid="116620307" border="0" src="https://freight.cargo.site/w/1000/i/2b8b172b6c252473651dde80c0eedfd4e1f6c9e18ccb414a4753c35b1762c98e/img000000018.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/42d110f2aed1d9b0a0e1ae27d211b6acffcbc31a633c303b7d58bdf3b7ab6263/img000000019.jpg" data-mid="116620308" border="0" src="https://freight.cargo.site/w/1000/i/42d110f2aed1d9b0a0e1ae27d211b6acffcbc31a633c303b7d58bdf3b7ab6263/img000000019.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/ba0e643a7e050564fa2bdc24a652e6371079cfe51217cd011c50240fb520976f/img000000020.jpg" data-mid="116620309" border="0" src="https://freight.cargo.site/w/1000/i/ba0e643a7e050564fa2bdc24a652e6371079cfe51217cd011c50240fb520976f/img000000020.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/917b03a325c560f2fd259d7d7437839420d08fd34a3e7a30f153a94ddce3d1c8/img000000021.jpg" data-mid="116620310" border="0" src="https://freight.cargo.site/w/1000/i/917b03a325c560f2fd259d7d7437839420d08fd34a3e7a30f153a94ddce3d1c8/img000000021.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/159dff564d0e85d256488a8698447bd7d99b7fd622bca39ca0774b9b5415836a/img000000022.jpg" data-mid="116620311" border="0" src="https://freight.cargo.site/w/1000/i/159dff564d0e85d256488a8698447bd7d99b7fd622bca39ca0774b9b5415836a/img000000022.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/29b2b243d2fb2759c67c2b055774202292e026c29dcf3fde63ed3f401b276641/img000000023.jpg" data-mid="116620312" border="0" src="https://freight.cargo.site/w/1000/i/29b2b243d2fb2759c67c2b055774202292e026c29dcf3fde63ed3f401b276641/img000000023.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/4deed41b5a5f7407998977637a6593389e7b854df25d88860b5c69bd8e314744/img000000024.jpg" data-mid="116620313" border="0" src="https://freight.cargo.site/w/1000/i/4deed41b5a5f7407998977637a6593389e7b854df25d88860b5c69bd8e314744/img000000024.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/25e61889e06a8c2b701a4db220df0bfe5e7d24cdb3d4f9b242f652632676d62d/img000000001.jpg" data-mid="116620314" border="0" src="https://freight.cargo.site/w/1000/i/25e61889e06a8c2b701a4db220df0bfe5e7d24cdb3d4f9b242f652632676d62d/img000000001.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/1ca1c46abbc0289d4356b9c8cc4bea6b841b860eab442f1527e879b1ed3b4eab/img000000002.jpg" data-mid="116620315" border="0" src="https://freight.cargo.site/w/1000/i/1ca1c46abbc0289d4356b9c8cc4bea6b841b860eab442f1527e879b1ed3b4eab/img000000002.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/3f022b62488de13051ea17a9e6eb4f2e9c928e714b3bde07ec7b2e1819bd1e9f/img000000003.jpg" data-mid="116620316" border="0" src="https://freight.cargo.site/w/1000/i/3f022b62488de13051ea17a9e6eb4f2e9c928e714b3bde07ec7b2e1819bd1e9f/img000000003.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/78da9dbf9f24499aeb53621e3570ccfc0dca0c7fb2f12c838bc9c989fb26cf6d/img000000004.jpg" data-mid="116620317" border="0" src="https://freight.cargo.site/w/1000/i/78da9dbf9f24499aeb53621e3570ccfc0dca0c7fb2f12c838bc9c989fb26cf6d/img000000004.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/7c5546f0a22990508c17824d8d3cbf71bae74b8f45fc768351e3eaa56af18a2b/img000000005.jpg" data-mid="116620318" border="0" src="https://freight.cargo.site/w/1000/i/7c5546f0a22990508c17824d8d3cbf71bae74b8f45fc768351e3eaa56af18a2b/img000000005.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/920a878e8719e7c1b693f5f51f584c19aca9805eb160a4ae55bd5abba15a774d/img000000006.jpg" data-mid="116620319" border="0" src="https://freight.cargo.site/w/1000/i/920a878e8719e7c1b693f5f51f584c19aca9805eb160a4ae55bd5abba15a774d/img000000006.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/3f28ccaba7a7108413500e3a8b27417bdfec35f11cb41be9f4bb39431114ec26/img000000007.jpg" data-mid="116620320" border="0" src="https://freight.cargo.site/w/1000/i/3f28ccaba7a7108413500e3a8b27417bdfec35f11cb41be9f4bb39431114ec26/img000000007.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/a5d08e7b90e433a260ace93d6540b478b8b28f973dfb9ef48deaecd529bc17c8/img000000008.jpg" data-mid="116620321" border="0" src="https://freight.cargo.site/w/1000/i/a5d08e7b90e433a260ace93d6540b478b8b28f973dfb9ef48deaecd529bc17c8/img000000008.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/254757002818bc403bc334aff901da0ee7813ee71110d0ecb8f29e9aa0ab9f1a/img000000009.jpg" data-mid="116620322" border="0" src="https://freight.cargo.site/w/1000/i/254757002818bc403bc334aff901da0ee7813ee71110d0ecb8f29e9aa0ab9f1a/img000000009.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/5c5a894ee1beaefb6a65e89b3ff73928c829c53d043075ac9890f6a23ef5dc18/img000000010.jpg" data-mid="116620323" border="0" src="https://freight.cargo.site/w/1000/i/5c5a894ee1beaefb6a65e89b3ff73928c829c53d043075ac9890f6a23ef5dc18/img000000010.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/2a10dd7e9cbe9b78c0d9186a56b6d4ac88fc6a5249c2310d5e2f3c1cc0b95819/img000000000.jpg" data-mid="116620324" border="0" src="https://freight.cargo.site/w/1000/i/2a10dd7e9cbe9b78c0d9186a56b6d4ac88fc6a5249c2310d5e2f3c1cc0b95819/img000000000.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/6da3277f97213aba7d3d9f0d2cc60e96de4e3ef978f4f3b4d9f055958903ee29/img000000041.jpg" data-mid="116620325" border="0" src="https://freight.cargo.site/w/1000/i/6da3277f97213aba7d3d9f0d2cc60e96de4e3ef978f4f3b4d9f055958903ee29/img000000041.jpg" /> The outputs are bizarre, odd, ugly, beautiful; they are incredible and unexpected. The dataset was a mess. The images are all incredibly varied. Portrait poster, double-page spreads from zines, product shots photographed at low angles, various background colors and dimensions, very little was similar and nowhere near close enough to create what I imagined it would create. Luckily I was completely surprised by what it (we) made. <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/89d2036d849d651494db3ce3b76f3a39b336aa9dfdab56e992e4b6a26273e3e2/img000000042.jpg" data-mid="116620326" border="0" data-scale="72" src="https://freight.cargo.site/w/1000/i/89d2036d849d651494db3ce3b76f3a39b336aa9dfdab56e992e4b6a26273e3e2/img000000042.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/816cfe3c3ab212994adcee5d27199b2aa14af834d171f16d7ea21831fa596fde/img000000043.jpg" data-mid="116620327" border="0" src="https://freight.cargo.site/w/1000/i/816cfe3c3ab212994adcee5d27199b2aa14af834d171f16d7ea21831fa596fde/img000000043.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/4821b2cbc37e3c1b370a91a5458ad207ba319145167d5a4b6e4e292748b144d2/img000000044.jpg" data-mid="116620328" border="0" src="https://freight.cargo.site/w/1000/i/4821b2cbc37e3c1b370a91a5458ad207ba319145167d5a4b6e4e292748b144d2/img000000044.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/f1cac12e91fcfbfe235e04dd1e69bf4a7bd5e792838945a125df434570f700fe/img000000045.jpg" data-mid="116620329" border="0" src="https://freight.cargo.site/w/1000/i/f1cac12e91fcfbfe235e04dd1e69bf4a7bd5e792838945a125df434570f700fe/img000000045.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/39f1635e299b6a3ed3afce71d6f3420acb18b587b86bb2cfeac2ab1f9fbbb5a3/img000000046.jpg" data-mid="116620330" border="0" src="https://freight.cargo.site/w/1000/i/39f1635e299b6a3ed3afce71d6f3420acb18b587b86bb2cfeac2ab1f9fbbb5a3/img000000046.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/3e8747d734fed5fa335e3f56406ce07a5d8e8fe52f140b5e209db4a5dd0cb3c9/img000000047.jpg" data-mid="116620331" border="0" src="https://freight.cargo.site/w/1000/i/3e8747d734fed5fa335e3f56406ce07a5d8e8fe52f140b5e209db4a5dd0cb3c9/img000000047.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/8090f985e1349465bb23083046651b66c40590910432aa043c446f1326f3156e/img000000048.jpg" data-mid="116620332" border="0" src="https://freight.cargo.site/w/1000/i/8090f985e1349465bb23083046651b66c40590910432aa043c446f1326f3156e/img000000048.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/0befeb9e0794232ddc7a1bfabb95e782ff4db67acf1d77ee444799945bb80175/img000000049.jpg" data-mid="116620333" border="0" src="https://freight.cargo.site/w/1000/i/0befeb9e0794232ddc7a1bfabb95e782ff4db67acf1d77ee444799945bb80175/img000000049.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/516efc335dd46e5d77a3f30738cb1fa59a44b567de12fe4ef931c3ae1ccd9cec/img000000026.jpg" data-mid="116620334" border="0" src="https://freight.cargo.site/w/1000/i/516efc335dd46e5d77a3f30738cb1fa59a44b567de12fe4ef931c3ae1ccd9cec/img000000026.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/e153c1103866334d4281e38e20349d62ffd42df8dd2b15b11a78b219f8430bcd/img000000027.jpg" data-mid="116620335" border="0" src="https://freight.cargo.site/w/1000/i/e153c1103866334d4281e38e20349d62ffd42df8dd2b15b11a78b219f8430bcd/img000000027.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/37cc86b32e5f7a04e82395170cb8a82259b6c3d690904da7f1c1b46f2f9ed024/img000000028.jpg" data-mid="116620336" border="0" 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data-src="https://freight.cargo.site/t/original/i/7c226a2d1e2cafe4105ecbcd7bb73b0a49adbb639ac2c9b0b694eb9a9e5fc6fb/img000000007.jpg" data-mid="116620371" border="0" src="https://freight.cargo.site/w/1000/i/7c226a2d1e2cafe4105ecbcd7bb73b0a49adbb639ac2c9b0b694eb9a9e5fc6fb/img000000007.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/c2dd5ae41e31986eaa031db05c8e9d95664ce5af7c42f026ee92562000572d83/img000000008.jpg" data-mid="116620372" border="0" src="https://freight.cargo.site/w/1000/i/c2dd5ae41e31986eaa031db05c8e9d95664ce5af7c42f026ee92562000572d83/img000000008.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/fe9798b3029408d2ce0a02f4b94b83c50d4efde8c68ea8a855e3f0b0c97f5ab1/img000000009.jpg" data-mid="116620373" border="0" src="https://freight.cargo.site/w/1000/i/fe9798b3029408d2ce0a02f4b94b83c50d4efde8c68ea8a855e3f0b0c97f5ab1/img000000009.jpg" /> <img width="1024" height="1024" width_o="1024" height_o="1024" data-src="https://freight.cargo.site/t/original/i/3dab40503ca84469d8a3397ce0e821d202651ffd02843ad81ea11a2f1e881b4d/img000000010.jpg" data-mid="116620374" border="0" src="https://freight.cargo.site/w/1000/i/3dab40503ca84469d8a3397ce0e821d202651ffd02843ad81ea11a2f1e881b4d/img000000010.jpg" /> The second set was slightly more controlled. This time I scraped the dataset of images from the website typographicposters.com. I then did some post-processing on the images to make them more uniform, placing them on the same square background. In theory, these are all posters with type as the primary focus, all roughly the same page shape and figure/ground relationship in the image. To my eye—the eye of a person with graphic design training—these images, in some manner, had measurably repeating and contrasting elements. But the results were similarly strange. What I had hoped for or at least expected, what I imagined the GAN would develop, was some sort of new poster. Years ago I had developed another project that used the machine learning-based Content Aware Fill tool (available in Adobe Photoshop) to generate new parts of famous posters, and they had repeated various aspects of the original in interesting ways. The Adobe tool created new sections of a poster, based on elements of the whole. I had guessed that something similar would happen here. And maybe it did actually do that, but in a visual language that I could not understand. It found aspects of the posters to repeat, but they weren’t the aspects that for me made up a poster. In this my machine-collaborator began to reveal itself and its ideas, and it had different thoughts on poster design than I did. In the third attempt I tightened my grip; I attempted to control the process as much as I possibly could. The previous attempts had felt like failures. They did not produce what I had anticipated. Yes they had made something new, but it was not what I wanted. This time I considered the best way to gather a large number of images that all looked very similar. My method in this was to use still images exported from a film that used a “locked down” camera. The Tom Waits and Iggy Pop scene from the 2004 film Coffee and Cigarettes, written and directed by Jim Jarmush, would provide the large image set I needed. The data set was as good as I could produce (still small, but very similar in content). I don’t know what I expected to see at the end of this process. What it produced was amazing, novel, and broken. It hinted at an understanding of the training data, or rather what it thought was important, but the output was completely alien to me. The system had worked beautifully, it had interpreted the data set and produced unique outputs. I now know that the failure was a failure of seeing on my part. Looking back on them, these are bigger successes than I had originally understood them to be. My failure to recognize the value stemmed from my expectations about what this creative network was going to make. At this point, I wanted to have a lot of control over the outputs, to let them generate new materials, but inside of a very narrow space of what I would consider successful. But that’s because I was being a controlling controller, squeezing with more and more humancentric force; I did not know then what I know now about the creative value of a loosened grip. The end.︎︎NextChapter 6 — Infinite Art Bot. https://christopherswift.work/Chapter-6-Infinite-Art-Bot Tue, 17 Aug 2021 01:48:05 +0000 CONTROL https://christopherswift.work/Chapter-6-Infinite-Art-Bot <img width="1045" height="579" width_o="1045" height_o="579" data-src="https://freight.cargo.site/t/original/i/e93daa723a08540bf6e38c2fc592266502eec8b0b1c7282e59cb91cbb5b036f5/Screen-Shot-2021-06-29-at-2.58.25-PM.png" data-mid="116620375" border="0" alt="screen shot of instagram.com/infinite.art.botInfinite Art Bot, 2021social media postsP5JS, RunwayML, Puppeteer, Node.js" data-caption="&lt;b&gt;screen shot of instagram.com/infinite.art.bot&lt;/b&gt;&lt;br&gt;Infinite Art Bot, 2021&lt;br&gt;social media posts&lt;br&gt;P5JS, RunwayML, Puppeteer, Node.js" src="https://freight.cargo.site/w/1000/i/e93daa723a08540bf6e38c2fc592266502eec8b0b1c7282e59cb91cbb5b036f5/Screen-Shot-2021-06-29-at-2.58.25-PM.png" /> Chapter 6 Infinite Art Bot. “ Our job is to amplify the black noise of objects to make the resonant frequencies of the stuff inside them hum in credibly satisfying ways. Our job is to write the speculative fictions of these processes, of their unit operations. Our job is to get our hands dirty with grease, juice, gunpowder, and gypsum. Our job is to go where everyone has gone before, but where few have bothered to linger.”― Ian Bogost, Alien Phenomenology, Or What It’s Like to Be a Thing This essay is about the first real success I found in this attempt at trust and care and the amazing results of that. For a brief time, I watched intently as a new sort of cyborg, a creative nonhuman acted with an agency that, while not totally intended for us to see, produced art or something very close to it. A short and creative life of sorts, never able to exist on its own, but taking those first steps towards agented creativity. The infinite art bot was the first project in which I tried to fully embrace my decentered place in a network of making. The project was intended to exist and run without me, a mixture of agencies and relations, producing new and unique expressions with autonomy. The Infinite Art Bot is a collection of programs, media platforms, archives, billionaires, non-profits, Instagram scrollers...a list that might include almost everything really. My intersection with this wide network of actors was aimed at creating an Instagram “bot” that would post visual outputs on its own accord. The new and unique visual outputs would be generated using the attnGAN model (running on the RunwayML platform as long as I had money in my account to cover the costs of the server requests), running a text-to-image algorithm. The process was this: a sentence that I had written for my writing semester with Natalia is chosen at random by a P5JS program. The sentence runs through a text-to-image model resulting in a small image-based visualization of that text (the scale of the black box and the amount of research and work that makes this work is genuinely massive in scope and scale, my interaction with it is akin to a raindrop in the ocean). The image and text are downloaded to a folder on my computer, which the program is pointed at to look for images to upload. Instagram doesn’t actually allow bots to run on the platform, so this process uses another program called Puppeteer that allows a program to launch an invisible version of Chrome (referred to as “headless”) that can be programmed to interact with websites. This version logs into Instagram and adds the image found in the designated folder as the image post, then adds the randomly selected text from my writing (the “prompt” for the AI generated image) and a series of pre-assigned tags, and then effectively hits “send.” If it all works, the @infinite.art.bot Instagram account has a new post. The program constantly ran into snags. RunwayML sometimes takes a long time to “wake up,” resulting in a black square being downloaded to the image folder for use. I had to run the program myself. I was never able to automate the initiation of the system (I wanted the program to run as often and whenever it chose, but I stopped the project before that aspect was developed fully.) But it did mostly work, better than anything I had worked on before. With a few key-strokes, the words I had written (for someone specific to read in a very narrow context) ran through a massive ocean of computing power and data, emerging from a very opaque black box with an image imagined by an alien mind, cheated onto a media platform: an unclear expression of a collaborative network trusted to create something of aesthetic worth (with exactly zero human curation). This project relies on inputs from various actors to work. All projects, when considered through a new materialist or object-oriented ontological lens, depend upon a range of normally unseen and unconsidered actors. This project tries to linger on, tries to amplify in credible ways, the work of a nonhuman creative network and its actors. The small programs I started with a year ago existed on a small and mappable network. Some of the paths laid out, like those of P5JS, were huge and complex, but the majority of the system lived in my laptop. The network of connections from any modern smart device (like my laptop) is global in scope and crosses political, scientific, economic, and other boundaries. They are Latour’s hyper-objects, not just one static, graspable thing but a thing across traditional ontological categories and boundaries, once thought to be impossible to cross. I am going to set aside the investigation into the hyper-object nature of laptops generally (and my six-year-old work issue laptop specifically) with the understanding that they are in a number of ways black boxes, but that they are the same black box for the vast majority of graphic designers in the world. With that then set aside, the programs I was writing were primarily self-contained. I understood the inputs, I was responsible for them in various ways. The sentences I had written (not at all for this purpose) added an element of structure to the project. Essays I had written for Natalia, essays written in response to her prompts, many of which were taken from my copy of Writing for the Design Mind, provided human-made content for the bot. Each sentence might be the one used as the prompt to the text-to-image program; I wrote them, but I did not choose them. That they might be used this way was not at all my intention when writing them, but maybe that highlights the lack of importance of an author’s intentions—of my intentions—in some important way. The other writing I did for this project was writing code, in javascript, for the P5JS library I was running my programs in. What writing means in these two spaces is in practice very different feeling, but in a metaphorical space of thinking about writing, this opens up something interesting for me. Writing the words into life in code, where the words change things (they literally make things happen), where a value written can change the color of a thing, its size, its shape, its location. I find this to be an interesting thing to consider. Code performs as a performative utterance; the words as written make the thing real. Like the oft-used example of a performative speech act, the words “I now pronounce you man and wife” when spoken during a marriage ceremony, when writing code, the words perform the act. These inputs I understand. The elements are known, I am in control of them to a large extent. Aspects of the higher level and more abstract aspects of Javascript are opaque, but they are learnable, discoverable. This project differed from my smaller localized programs. This network was tied into numerous large and unknowable black boxes. The text-to-image model attnGAN is massive and complex. I know some of how it works, I can affect it, but my input is no longer the performative utterance of my simpler programs. The words I write are now much more like the writing in my essays. They suggest rather than declare, they are shared and interpreted by a second party. In this case, the interpretation and translation is closer to communicating with an alien. The software also runs through a commercial provider. RunwayML is a company that provides a simplified kind of access to machine learning tools. While helpful, it is another layer of opacity, one more collection of layers added to the network. I am not sure how they create the clean UX of the interface, not sure what is lost or given up to achieve it. It is another reassuringly tidy black box. The inputs for this project, some known and used as I might have intended, others used or repurposed in odd fashion, were all strange and sometimes chaotic feeling. Strange things go in, stranger things come out. Defining what the final output of this project was and who it was for is unclear. The bot itself, the GAN produced images, the posts on Instagram...these are all in some ways the final output depending on the perceived audience. The text, initially for Natalia, taken largely out of context, was the output intended for the GAN model, which prompted the new image ready for upload, triggering the publication of the image and text...each aspect of the network working relationally with the rest, until finally bringing in the audience (Instagram scroller) at the end of the process. An audience seeing, interacting, decoding, and reading the image is also a creative act; a part of the meaning making. The images that the bot created were never intended to be edited or reviewed—although I did delete one post that had something that looked a lot like a swastika in it, and I also removed the all black outputs created due to technical errors with RunwayML (I didn’t see them until I refreshed Instagram). The outputs of this project are closer to atonal jazz or automatic drawing. If you can see something of interest or hear something pleasing, that is just as much about your personal interpretation as it is about the output. The images generated from the attnGAN are never obvious representations of the content. They are disconnected abstractions of form and color. They are melting and horrible and abstract and beautiful. They are alien. They are maybe not really for us; it often feels like they aren’t. They are brave and expressive and have no fear (the antithesis of an Instagram influencer). This project was a success or very near to one in my mind. The collaboration was rooted in a place of trust and care in a way that I had not been able to make happen or participate in in prior projects (save, perhaps, the first: my Camera Obscura project). Seeing the images that the model produced, strange as they are, was a clarifying moment for me. The near autonomy of the process, the clarity of the network—stretching out in every direction, but not with me at the center or top—showed me the kind of work that this collaborative trust and care could produce. This move away from control (even if only imagined control) was freeing and exciting. My imagination leapt. This project ended one day while I was walking Dave Peacock through the details of the network. I made a change to the code, and it broke. It ended. It would have been very easy to fix the code and bring the network back online, making and posting strange melty dream-like images, but I again abandoned them, I withdrew my care. AttnGAN, the machine learning model that was doing the text-to-image work, was just about three years old at this point (a very old program in the world of machine learning), and the non-profit OpenAI had just announced the new model’s CLIP and Dall-E. The leaps in ability are almost impossibly dramatic in these new models. I decided to focus on these for my future projects, and I left @infinite.art.bot broken and finite. The end. ︎︎︎︎︎︎︎︎︎NextChapter 7 — CONTROL V1 a booklet about care. https://christopherswift.work/Chapter-7-CONTROL-V1-a-booklet-about-care Tue, 17 Aug 2021 01:48:07 +0000 CONTROL https://christopherswift.work/Chapter-7-CONTROL-V1-a-booklet-about-care <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/94ca1d62ae2e97d48b6f489b61c1714d87743c43d51a0fbc9fa40e683f193fe0/a_pair_of_running_shoes_by_William_Blake2.png" data-mid="116620376" border="0" alt="A Pair of Running Shoes by Williams BlakeA Pair of Running Shoes by X, 2021Digital Latent3Visions: CLIP+Taming.ipynbdeveloped by: @advadnoun" data-caption="&lt;b&gt;A Pair of Running Shoes by Williams Blake&lt;/b&gt;&lt;br&gt;A Pair of Running Shoes by X, 2021&lt;br&gt;Digital&lt;br&gt; Latent3Visions: CLIP+Taming.ipynb&lt;br&gt;developed by: @advadnoun" src="https://freight.cargo.site/w/512/i/94ca1d62ae2e97d48b6f489b61c1714d87743c43d51a0fbc9fa40e683f193fe0/a_pair_of_running_shoes_by_William_Blake2.png" /> Chapter 7 CONTROL V1 a booklet about care. “ Curiosity is a vice that has been stigmatized in turn by Christianity, by philosophy, and even by a certain conception of science. Curiosity is seen as futility. However, I like the word; it suggests something quite different to me. It evokes “care”; it evokes the care one takes of what exists and what might exist; a sharpened sense of reality, but one that is never immobilized before it; a readiness to find what surrounds us strange and odd; a certain determination to throw off familiar ways of thought and to look at the same things in a different way; a passion for seizing what is happening now and what is disappearing; a lack of respect for the traditional hierarchies of what is important and fundamental.”― Foucault, Michel. “The Masked Philosopher.” Ethics: Subjectivity and Truth. The Essential Works of Michel Foucault 1954-1984, Vol. 1. Ed. J. Faubion. Trans. Robert Hurley et al. Harmondsworth: Penguin, 1997. 325. Print. This essay is about trust and care. It is about curiosity and exploration and sharing. This project was like planting a garden, but a garden that exists in fast-forward. Time in this garden moves at speeds I don’t understand, generations of plants evolve before my eyes, brand new species blink in and blink back out, a wild unkempt thriving thing, out of my control, doing amazing things; beautiful and surprising without need for me. This project was made of the odd and the strange, it ignored traditional hierarchies, took the strange and made it stranger. It was made of curiosity. It is a true collaboration, in which I trusted that my nonhuman collaborator and me could make something worthwhile, and maybe great. I helped organize part of the network, made some connections, gave some directions (a lot of which were seemingly ignored), I did my part, and then I trusted the network. This project is a combination of two major components. The first is a collaboration with a brand new generative art program that uses probably the most powerful machine learning language model currently available to the public (CLIP developed by OpenAi) to work with a text-to-image based GAN to produce images. The second part is the text outputs created in collaboration with the language model GPT-2 developed by OpenAi. The two machine learning generated components are then accessed by a javascript program that I wrote to generate unique versions of a booklet titled CONTROL V1 in Adobe InDesign. <img width="1650" height="2550" width_o="1650" height_o="2550" data-src="https://freight.cargo.site/t/original/i/3551172c75c1382849e7252fb5adbe7905f2751d5c22941cae10c4b30136dcdf/Control-V3_Page_01.png" data-mid="117604203" border="0" alt="CONTROL V.1Code generated zine, 2021Adobe InDesign, JSX" data-caption="&lt;b&gt;CONTROL V.1&lt;/b&gt;&lt;br&gt;Code generated zine, 2021&lt;br&gt;Adobe InDesign, JSX" src="https://freight.cargo.site/w/1000/i/3551172c75c1382849e7252fb5adbe7905f2751d5c22941cae10c4b30136dcdf/Control-V3_Page_01.png" /> The images in CONTROL were all created while experimenting with a new text-to-image GAN called Big Sleep, developed by Ryan Murdock. This type of generative text-to-image creation was leaps ahead of the previous models I had used, such as BigGAN or styleGAN (used in the Infinite Art Bot project). The use of the advanced language model that had been trained on a massive dataset meant that the images being generated (based on my prompts) in the generator side of the GAN could be tested against a much more refined detection network on the other side of that adversarial network. The power of these new models to generate the images I attempted to describe is incredible. It is still an act of trust in the network, and very much a collaborative creative mode. I describe the things I want to see, and the model creates inside a massive latent space of possible outputs. The GAN is creating a universe of variations in that space. The images we see are small patches of that vast ocean, following a single string through a near infinitely massive textile of impossible complexity. The small community of machine learning based artists has taken to calling these descriptions “prompts” and the human artists writing them “prompt engineers.” Giving the model a text prompt such as “a motorcycle” might generate the following image. It might be a clearly depicted motorcycle or just as easily an abstract exploration of the ideas that might exist in the zeitgeist about motorcycles. Or it might show you the word “motorcycle.” The size and complexity of these models allow for suggestions to be made, but not directions. This is collaboration, it requires and creates a kind of curiosity with care and careful attention, a mode of making in which you can suggest and wait and trust the process, but you are not in control. <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/92a53b946a4441177a5f1c58bbdbe7e618b5951289358fe1a886fd786aefbba9/download-8.png" data-mid="116620377" border="0" src="https://freight.cargo.site/w/512/i/92a53b946a4441177a5f1c58bbdbe7e618b5951289358fe1a886fd786aefbba9/download-8.png" /> <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/841b9a729841672b9c354436142e32be7e96b27833ea862afbd09556bde40a8b/download-7.png" data-mid="116620378" border="0" src="https://freight.cargo.site/w/512/i/841b9a729841672b9c354436142e32be7e96b27833ea862afbd09556bde40a8b/download-7.png" /> <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/727ed69453b050d2e15540edde88139695df3a91b79f381def6b5d94221e047d/download-6.png" data-mid="116620379" border="0" src="https://freight.cargo.site/w/512/i/727ed69453b050d2e15540edde88139695df3a91b79f381def6b5d94221e047d/download-6.png" /> <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/e6e26799d224b32681c06e6df539c6177c6060ca2cfe5a61761c29539ae0a707/download-5.png" data-mid="116620380" border="0" src="https://freight.cargo.site/w/512/i/e6e26799d224b32681c06e6df539c6177c6060ca2cfe5a61761c29539ae0a707/download-5.png" /> <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/9b763f3510ddb194c9a65d990e4ec04017c0029f1f48b4494f26cb4019676899/download-4.png" data-mid="116620381" border="0" src="https://freight.cargo.site/w/512/i/9b763f3510ddb194c9a65d990e4ec04017c0029f1f48b4494f26cb4019676899/download-4.png" /> <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/77b247ea0b5145ca3f5cfdabdcf674f4d2c0cb46a6fcf77b76a707c766e007e7/download-3.png" data-mid="116620382" border="0" src="https://freight.cargo.site/w/512/i/77b247ea0b5145ca3f5cfdabdcf674f4d2c0cb46a6fcf77b76a707c766e007e7/download-3.png" /> <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/5c4da2f216a22110c331b88ccda645eb8b7dd9d83495823e97db190a331cd883/download-2.png" data-mid="116620383" border="0" src="https://freight.cargo.site/w/512/i/5c4da2f216a22110c331b88ccda645eb8b7dd9d83495823e97db190a331cd883/download-2.png" /> <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/9efae68233e4bc79ced9c4bf2dc7c4e682925ae88d0670b3f2e5b869e3d23768/download-1.png" data-mid="116620384" border="0" src="https://freight.cargo.site/w/512/i/9efae68233e4bc79ced9c4bf2dc7c4e682925ae88d0670b3f2e5b869e3d23768/download-1.png" /> <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/0f28f75ba9690fa2e8f4670b330882e5779eccb8cee17c2e5a09f24891be6143/download.png" data-mid="116620385" border="0" src="https://freight.cargo.site/w/512/i/0f28f75ba9690fa2e8f4670b330882e5779eccb8cee17c2e5a09f24891be6143/download.png" /> What I am able to bring to the network is a lexicon of descriptive language and a grasp of the history of graphic design that is slightly different than many other prompt engineers have access to. My prompts are of a different sort than those I’ve seen in the generative art discords; and what I’m looking for in the outputs also seems different. My initial experimentation with these new models was based on a series of prompts using the structure “A pair of running shoes in the style of X.” X, in this case, was the name of a famous person in the history of graphic design. The first name I tried was William Blake. Blake, in truth, is not a name I usually think of in the history of graphic design, but I chose him as my first prompt at 9:36 am on January 20th, 2021. <img width="512" height="512" width_o="512" height_o="512" data-src="https://freight.cargo.site/t/original/i/94ca1d62ae2e97d48b6f489b61c1714d87743c43d51a0fbc9fa40e683f193fe0/a_pair_of_running_shoes_by_William_Blake2.png" data-mid="116620376" border="0" alt="A Pair of Running Shoes by Williams BlakeA Pair of Running Shoes by X, 2021Digital Latent3Visions: CLIP+Taming.ipynbdeveloped by: @advadnoun" data-caption="&lt;b&gt;A Pair of Running Shoes by Williams Blake&lt;/b&gt;&lt;br&gt;A Pair of Running Shoes by X, 2021&lt;br&gt;Digital&lt;br&gt; Latent3Visions: CLIP+Taming.ipynb&lt;br&gt;developed by: @advadnoun" src="https://freight.cargo.site/w/512/i/94ca1d62ae2e97d48b6f489b61c1714d87743c43d51a0fbc9fa40e683f193fe0/a_pair_of_running_shoes_by_William_Blake2.png" /> The outputs from this project changed everything in my research and making. It redirected the work I focused on for the next year. The outputs are never what would typically be considered perfect, or even desirable. A generous reading of them is that they are poetic. They hint at ideas of the thing prompted towards. They contain the grammar of the thing, elements of the whole but put together by an intelligence that does not have a recognizable (to me) understanding of what works and what does not. The text for the publication was generated using the language model GPT-2 developed by OpenAi and published in November 2019. The model is trained on a massive dataset (1.5 Billion parameters) to create text outputs that are very high quality. Given a prompt like “it was raining cats and” the model would very likely generate “dogs.” The longer and more complex the request, the more likely it is to break down and create a nonsense response. I used a modified version of the model that was given new text parameters to learn from. For the new training set, I used 15 years worth of content from the publication Design Issues. GPT models start with a prompt from an outside user and then generate the requested length of text starting with that prompt. For this project, I started with the prompt “Collaborations between tools and makers, between those with understood agency and misunderstood agency, between the designer and the designed objects,” and then after that used the last fragment of the previously generated text to prompt the next, over and over again. The phrases, sentences, and paragraphs generated in this way are similar to the images the generative machine learning network creates. They are poetic. They have meaning because we might choose to find meaning in the words. They seem meaningful and are expressive of something, but always not quite right. They are alive with possibility and are often fantastic and cool. They are also outside of my understanding, and they often appear unintelligible. But within that gap of understanding of generated image and text is exactly the place where this collaboration makes space for creativity. Some examples of generative text from CONTROL V1: “Although the metaphor of progress involves the prevalent role of aesthetics, the art of the decorative arts movement and accomplishing a hollow graphic design.” “This strategyform is simple: it is the primary impact on consumer action and a philosophy of design. In the practitioners, the concept of design and typography, the accompanime of something more efficient and destroyed.” These mean nothing if that is what I want them to mean, but if I care, if we carefully attend to meaning making, if we trust that our collaborators are princesses and not dragons, that our creative network is greater (bigger, richer) than we might assume it to be, that we are maybe part of something that is happening right now, that is strange and odd and curious, than we might find meaning and value in this unexpected place. I wanted to present this content in a manner that also expressed my interest in letting go of control, that explored a trust of the network, and that showed care. A traditionally laid out two-page spread with a scalar grid system was the antithesis of how I wanted to approach this. I wanted to ignore traditional hierarchies of what is important and fundamental in the creation of this booklet. I wanted to get as far away from the detail work, that I think is used to enact our control, as possible. To create the final outputs, I wrote a javascript program that starts by creating a half-letter sized booklet (I picked this size for pragmatic reasons around cost and ease of output), then sets new margins for each page, and creates new versions of the various paragraph styles to apply to the content in various ranges. The title size is different for each new creation, while the main body paragraph is modified in each paragraph. Each page may have a randomly selected image from the “A Pair of Running Shoes by X” project placed randomly on the page. Each paragraph can change in text size, location, character spacing, and rotation. The folios slowly move down the pages at various velocities. Each booklet is unique with each running of the program. Ideally, this booklet is “viewed” in the manner of an artwork, or maybe a design/art zine. The content can be unclear, the intentions maybe obscured somewhat, but hopefully engaging in a fashion and enjoyable to explore, if not read cover to cover.Metaphors about the ocean seem to fit machine learning well. The size, the unknown/unknowable, the attempts at mapping, the narrow ways in which we might understand it, these all help me to think about the core concepts of AI. I find particular clarity in a project like this when understood through the metaphor of surfing. Surfers must have a knowledge about how to read the water, understand the meaning of a specific waves crest, shape, and speed, to scan the surface, and make guesses at what is happening below the surface in order to surf. The surfer interfaces with the ocean at its surface and near the shores; they dip in and out and are raised and dropped, pushed and pulled by the water. They work with the ocean, never in control of anything other than themselves, always interpreting and responding to this huge and fundamentally unknowable thing, in collaboration. There is no hope for them other than to work with the ocean, they can’t make it do anything. They have fun, and they look cool. This is not what the ocean exists for, but it is an exciting way to collaborate with its vastness. This is what I imagine myself to be doing when I dip into creative practice, collaborating with the ocean of potential making that is GPT-2. The end. ︎︎︎︎︎︎︎︎︎NextChapter 8 — Speculative Anthropology. https://christopherswift.work/Chapter-8-Speculative-Anthropology Tue, 17 Aug 2021 01:48:08 +0000 CONTROL https://christopherswift.work/Chapter-8-Speculative-Anthropology <img width="800" height="600" width_o="800" height_o="600" data-src="https://freight.cargo.site/t/original/i/dabb022af351f1c0ad04814de15e30c6867ebaef1a74ac3b3e05d5595beb8a3e/dsc02651_673235052.jpg" data-mid="117710855" border="0" src="https://freight.cargo.site/w/800/i/dabb022af351f1c0ad04814de15e30c6867ebaef1a74ac3b3e05d5595beb8a3e/dsc02651_673235052.jpg" /> <img width="800" height="600" width_o="800" height_o="600" data-src="https://freight.cargo.site/t/original/i/60d73b1ce66551b490919c3216e0726c0df1f430cc253f9263377d6981548463/dsc02652_1039787067.jpg" data-mid="117710856" border="0" src="https://freight.cargo.site/w/800/i/60d73b1ce66551b490919c3216e0726c0df1f430cc253f9263377d6981548463/dsc02652_1039787067.jpg" /> <img width="800" height="600" width_o="800" height_o="600" data-src="https://freight.cargo.site/t/original/i/b8ef5f17d06f1c6876873e1bde2cf8c51beae8ac4a0cac9d4bed03ab8e96dbbb/dsc02653_983587738.jpg" data-mid="117710857" border="0" src="https://freight.cargo.site/w/800/i/b8ef5f17d06f1c6876873e1bde2cf8c51beae8ac4a0cac9d4bed03ab8e96dbbb/dsc02653_983587738.jpg" /> <img width="800" height="600" width_o="800" height_o="600" data-src="https://freight.cargo.site/t/original/i/c923f530d15d78dbd4b4a80f407db5aad6364436cc55b457a4735f5ca4179106/dsc02654_1163010357.jpg" data-mid="117710858" border="0" src="https://freight.cargo.site/w/800/i/c923f530d15d78dbd4b4a80f407db5aad6364436cc55b457a4735f5ca4179106/dsc02654_1163010357.jpg" /> Chapter 8 Speculative Anthropology. I can’t help but dream about a kind of criticism that would try not to judge but to bring an oeuvre, a book, a sentence, an idea to life; it would light fires, watch the grass grow, listen to the wind, and catch the sea foam in the breeze and scatter it. It would multiply not judgments but signs of existence; it would summon them, drag them from their sleep. Perhaps it would invent them sometimes—all the better. All the better. Criticism that hands down sentences sends me to sleep; I’d like a criticism of scintillating leaps of the imagination. It would not be sovereign or dressed in red. It would bear the lightning of possible storms. — Foucault, Michel. “The Masked Philosopher.” Ethics: Subjectivity and Truth. The Essential Works of Michel Foucault 1954-1984, Vol. 1. Ed. J. Faubion. Trans. Robert Hurley et al. Harmondsworth: Penguin, 1997. 323. Print. When I was growing up in Toronto, the West End of Queen Street was the very coolest place I had ever been. All the good record stores, vintage clothes, comic shops, they were all there (this is probably not true), and as far as I knew as a 14-year old that liked sort of obscure music and movies, this space was magical. The record store that I loved the most was Penny Lane records, it was a little further out of the way, but they had a rack of cassette tapes that made them worth all of the trips. These tapes, as far as I know, could only be purchased here. They were all bootleg recordings of live shows. The quality of the tapes was something only a real fan could look/listen past. They sounded like the worst version of the worst live album ever recorded. Conversations of the audience members near the bootlegger, the recordings just stopping and starting for reasons I would never know, the sound picked up on a recorder small enough to smuggle into the show, these all added to the magic of these recordings. These recordings were not for everyone. These would never play on the radio (maybe very cool college radio); no one’s cool aunt could buy this at the HMV. These recordings were special to me. I loved these tapes. My favourite band, The Smiths, had broken up when I was 12 years old. I had just missed them by a couple of years. Listening to the live shows on these hilariously bad recordings made me feel special, and like I could have some sort of connection to this band, this show, these other fans that was more personal and meaningful. When I started working with generative machine learning models, I felt the same sort of rush of discovery and connection. Where others saw an ugly melty failure, I heard/saw/felt the bootleg tapes. It was all there, but not perfect in the way a commercial work would be expected to be, it was slightly out of register, with a few typos, with some parts crossed out, it mumbles some words, it felt like a connection, a conversation, and it felt a little like magic. This work relies primarily on a network of machine learning tools to create the outputs. These text-to-image tools rely on a collaboration with the human to be a source of ideas, interests, and questions. At its most basic level, I input my prompt into a text field, and then the massive network creates images. This network does not rely on my abilities or skills in graphic design to generate outputs, nor does it really need any programming understanding to function. It simply requires me to communicate with it. I had worked with text-to-image models on previous projects, and they produced some compelling work. They functioned like automatic drawing in many ways. They required a lot of the audience, asking that they find something of value and meaning inside of something that would appear to be effectively meaningless. These earlier attempts were like reading a book of poetry in a language you did not understand, parts of the structures and shapes might be intriguing, but the intention could never be parsed. The new network VQGAN + CLIP was like a Rosetta Stone. What seemed like an impossible or at least improbable idea was suddenly accessible. Then, at the time, non-profit OpenAI published two project announcements in January 2021, CLIP and Dall-e. CLIP was a new kind of detection model that could caption images very well, and it could do it using a very new method called “zero-shot learning”. Zero-shot means that CLIP does not have to have been trained on a particular data-set to work. One-shot and Few shots are given a starting place to learn from. CLIP can caption images it has never “seen” before. VQGAN was developed by Patrick Esser, Robin Romback, and Björn Ommer at IWR Heidelberg University in December 2020. It can make new high-resolution images based on image data. This model was important because it used a technique thought to be only applicable for language models and applied it to images, which resulted in much larger resolution images that could be more complex. Katherine Crowson and Ryan Murdoch both, separately, combined the two models to have CLIP guide the image generation of VQGAN through a text prompt. This allowed for a massive step forward in the quality of text-to-image technology in its ability to output higher quality images and to better understand the text prompts provided. This moved from the completely alien abstraction of early GANs to something like a confused conversation between agents capable of conversations, but really far away, slightly out of tune and out of register in ways that I don’t understand. “CLIP is a model that was originally intended for doing things like searching for the best match to a description like “a dog playing the violin” among a number of images. By pairing a network that can produce images (a “generator” of some sort) with CLIP, it is possible to tweak the generator’s input to try to match a description.” (@advanoun) One of the reasons that VQGAN was such a big deal was that it allowed for larger images to be used in the process without using massive amounts of computing power. The challenging thing to understand about these image-generating models is the scale. If you take a tiny image, say 10px by 10px, you are looking at a matrix of possibilities that is 10x10x3 (each pixel mapped to a location that can be in any one of three colors or a combination of those). Each of these possibilities creates a level of complexity. By using a technique called Transformers it allowed for larger images to be created and the complexity and scale of the universe of possibilities to be easier navigated. While it was still massive, this “latent space” could be mapped metaphorically. The multidimensional space that holds all of the possible iterations of a model is like a small galaxy, maybe a small universe. The complexity can hold almost everything. While I can understand and navigate a 3D space pretty well, and 4D space gets a little trickier, and 5D space becomes an interesting thought experiment, the shape of these latent spaces in 512D space means almost nothing to me. It is so far away from my ability to consider it to be gibberish. This collaborator, this other someone or something that we are communicating with through massive space and with strange translations, they are something very close to alien. The way that value is assigned to aspects of images or language has nothing to do with how I understand it, nothing to do with logic or syllogisms. The collaborator cannot “show me the work” in a way I can appreciate any more than the ocean can explain to the surfer what the meaning and reason behind the next rising wave might be. One of the more famous GAN’s is called StyleGAN. Developed by Nvidia, it can create life-like images of peoples faces that are so convincing that you can usually only tell it is generated and not a photograph is by looking at small edge details around the hair and background of the image or maybe around where someone’s glasses sit on the ears. Inside of the latent space of this GAN is the possibility of every face of every person ever. Future and past, it contains every single one. We would just need to search for a long time to find a particular someone. The paths that we travel along the 512D space as we create a new set of images with its near-infinite branches of the latent space where maybe everything ever can be found if we looked long enough and hard enough, or perhaps just got lucky. I propose considering the latent space of these models as a sort of way to look at everything that might have been or might be. A view into possible worlds, alternate timelines, multiple universes. If every choice creates a new branch of possible worlds, then everything is possible. This is a sort of speculative fiction, or science, or philosophy. This project aims to consider this idea seriously as a starting point or prompt to explore that unknown space and those possible timelines. These explorations of the latent space suffer a similar problem of the bootleg tapes of Smiths concerts I would listen to. They are low quality; they are messy, out of tune, raw and strange. But like those recordings, they feel essential and alive, full of possibility and energy and passion. Like old camera and film technologies, the images are not “perfect” representations of the asked-for thing, but I think it is a mistake to see that as the measure of value in this case. The technology will get there soon; the thing described will be generated in a photorealistic and pixel-perfect representation, but doing so will become flat and dull without nuance and voice. The messiness expresses something vital and exciting in my view. I want to talk with this network and ask them to make music and art and gig posters for my favorite bands with me. The fuzziness (meltiness, out of focus, etc.), its messiness provide a sense of honesty and realness that is affecting. The misunderstandings and confusions, the disagreements create a sense of real-life, meaningful communication between agental beings. I am going to talk to it about things that matter deeply to me, things that I “know” in lots of ways, songs that I have heard a thousand times, I know the music, but I also know the feeling of listening to the album, the way it evokes feelings about my best friends and crumbling family life in my teenage years. It is not a measurable and data-driven knowing that I am sharing; it is something else than that, maybe everything else. These are things I care for, things that I love, the things that made me who I am in many ways. And while maybe there are more significant concerns and uses of this network of technologies, they are not my interests. When I met HAL, I did not want to talk about questions of phenomenology. I wanted to make cool posters and start a cover band. This project’s outputs have been expansive. It has produced hundreds of posters, which was my primary aim at the start, poetry, song titles that led to lyrics that led to songs being recorded, music videos, short movies, and poetry recitations by AI-generated performers. Each of the output types used a different network of collaborators and different methods to produce the results. The posters were created using various text-to-image models but primarily Latent3Visions: CLIP+Taming.ipynb developed by Ryan Murdoch running on Google Colabs. After setting up the needed libraries and support programs, I input my text prompt into a text input field and assign a weight to that input. This “weight” is sort of how much attention the program should pay to this input. If the input was something like “a painting of a loaf of bread by Hannah Höch” with a weight of 1, then the image would trend towards those words as a focus but also pay attention to other connections the network might make. This weight function for this input has a range of -5 to 5, where a negative number seeks to ignore the input. In the case of the above prompt, whatever the opposite of bread and collages are would be produced. Maybe a 3D architectural model of a fish. I can then add secondary text prompts to flesh out the details that my first statement does not contain. For the example prompt, I am might include “collage, flat, baking, kitchen, torn paper, juxtaposition,” and then I assign a weight to this as well. Past the first text prompt, these are not mandatory inputs. The following inputs are image-based. If I wanted to narrow the vector of paths through the latent space, I could give the model an image to refer to. Any image can be pointed to and given a weight value. I can also provide a negative image value to stay away from. This sort of prompt and weighting is the primary starting place for most of these GAN’s. Additional information such as learning rates, decay numbers, height, width, and the total number of iterations is added in various ways depending on the system. Most of the GANs can be left to generate images, some have additional steps and needs, but generally, that is all that is needed. The language-based outputs such as poems and song lyrics were generated in collaboration with GPT-3 developed by OpenAI. I was granted access to the closed beta through an open application process. The GTP-3 beta is accessed through a website but has similar prompts and weight input fields. After setting initial values, I simply frame my text prompt. The following is an example of the prompts: Lyrics to The Smiths song “How can she find time to be so unkind?” Lyrics by Morrissey Verse 1: That would be enough information to give the program-specific points of interest and a structure to refer to. GPT3, in this case, responded with: Lyrics to The Smiths song “How can she find time to be so unkind?” Lyrics by Morrissey Verse 1: I was amazed to hear her say, That she thought that I’d be pleased to know That she had started seeing someone new, And just how happy he made her feel. Chorus: How can she find time to be so unkind? When I’m feeling so lonely in my mind. How can she find time to be so unkind? When I’m feeling so lonely in my mind. Verse 2: I was shocked to hear her say, That he had been round to meet her folks, And they liked him, but they’d never quite seen him before, And she said that they could really be a couple. The system uses a complex method of language understanding called “attention” that allows the model to assign values to each word in the prompt and to create a matrix of these values that allow the model to diagram the sentence in a way (it is not using this structure really, but it is a close metaphor for what it is doing). With this ability, it can look backward and forwards to words it might generate and has generated and measure the fit of those words. These tools are not for just one thing. Aimed at different problems, they are capable of solving all sorts of issues. Ideas intended to solve language problems can be applied to images, to music, to probably anything. A brick has many uses, building walls or bridges, propping open doors, smashing windows. Maybe all tools are this kind of multiple, but it takes a sort of imagination to figure those uses out. The digital nativeness of machine learning might be why this network of tools and ideas can be so multiple in its uses. The limitations of imagination that surround our current modern digital tools (Adobe CC suite) might be because they are often trying to solve a physical, pre-digital world problem with computers. They are an attempt at a translation that is limited by both the original nature of the thing and the constraints of this new one. These machine learning tools are not trying to solve a single and existing problem using new methods and technologies. They are instead a new way of thinking about the world. My process then for this project has been to attempt to trust these networks of collaborators with these things that I care deeply about. To have amazing, frustrating, funny conversations with this alien someone. These conversations are complex; they are multilayered, with stops and starts that make things rough in a way that the modern world of polished interactions tries to smooth over with simple and clean interfaces, interactions, and design. My sides of these conversations have been prompts that are often along the lines of “A RoboCop movie poster in the style of Armin Hofmann” or “A Point Break movie poster by Hanna Höch.” They are a mixture of things I loved in my youth asked to be reframed and reconsidered through the lens of the things I care about in my adult life. This project has been one of partnerships and collaborations. I have had what feels like (and maybe is) conversations with a network that I am only a part of. The outputs have been meaningful to me. I have had to spend time considering the network’s, often unexpected, responses. The process has also clarified the nature of these networks for me. While machine learning models are the most obvious example of an agental tool, their abilities so obvious, it more than anything shows that this shifting of perspective should be applied to how we see all of the tools we “master” and how we view our roles in the creative network of tools, ideas, people, objects, and all of our collaborators (human and non-human.) When I was working at Rhode Island School of Design, I overheard a graphic design student say that they had “made a book.” I have been thinking about this statement for a long time, and on and off, I reconsider it. What does it mean for a designer to “make a book?” This student did not make the paper, the ink, the typeface, the historical structures of classical page shapes and margins; they likely did not write the text; they may have sewed the signatures (having learned the skill at RISD). So then, what does it mean to say that we “made a book.” Like any cultural creations, they are not made whole-cloth, pulled from our imaginations fully formed and wholly original. They are a collection of culture, a circle drawn around a selection of everything, that is then presented as a made new thing. Without considering what those points we have circled mean, we might think that we are the ones in charge, that the drawing of the circle is the most crucial aspect, that without us to direct these disparate elements they are meaningless and without agency. This project has chosen to consider the collaborators that we believe to be our “tools.” Questioning that relationship and that need to control and master our partners. Considering an alternative to our current thinking and exploring the results of moving away from a need for control and moving towards a place of care and trust. A decentered graphic designer who is part of a network of making, made up of collaborators, human and non-human, that wants to see where we might go if we let go and trust that if we show care for our team, we will end up somewhere great. The end.