On curving and softening digital lines

Jan 5, 2022

The screen of my phone curves around the edges and the hard line between the digital and physical does not seem as defined as it does in the old rectangle of my laptop screen or the square of the ad billboard outside my bus. In my room, the rectangular pane of white indicates a snowstorm, and the brown wooden panels that meet it, the warmth of my confinement.

More people are wearing circular smart watches with perfectly black OLED screens, thin white symbols riding atop them as if to barely peak into our world from the depth of digital logic. My mom’s e-ink screen doesn’t seem to protrude at all but captures her mind in its world.

I’ve been setting my projector at odd angles and into the corners of walls where the light becomes an unpredictable polygon triptych. If propped up just right I can get it to drench the wall in color and now forest films seem to extrude from all angles, sometimes from a single point and at odd times past the middle of the night I project only lines or words on an empty alpha channel so symbols conspire on the ceiling as I dream.

Developers conceive virtual reality as a creation ex nihilo, a reality built out of void from triangles and primary colors flashing sterile and facile simplified thoughts that head away from here to outer space or the nowhere of pulses and numbers. This is a dualism without the need for eyes, or earth, where we throw on our goggles, then take them off to return to our tenements. So learn to code shift, to adopt avatars, to cease to be your fleshy face at prescribed hours. It’s not radical to say this isn’t what any of us want, so if you struggle like me to understand where these billions are flowing to and feel the need to flow too down that bitstream, know that the digital will never have a fresh stream to drink from or a tree to climb and I think it will be too late before we realize that that world can’t extract this one or copy it, a better aim is to goad it here and learn to blend its contours into our own.

A More Equitable Murder Simulator

November 30, 2021

If all interpretations of video games are illusory - the ‘phantasms’ discussed by D. Fox Harrell referenced by Soraya Murray in On Video Games, I am more worried than ever about the substrate on which the interpretations take place. If game makers don’t understand how bits transform into objects in our minds, then their intentions are murky. Why is it that we are having a conversation about equitable representation in assassination simulators? Why is it that the computational media we have is so far from both 1.) the abstract and wondrous affordances that these dream machines can produce and 2.) a close representation of human culture? Popular games are neither utopian visions of abstract aesthetic accomplishment nor very interested in the emergent narratives that arise from [mundane|true] representations of everyday life. Our analysis is severely limited if it must be on Assassins Creed III: Liberation on PS Vita.

Embracing the Panopticon (An Unwritten Essay)

Nov 8, 2021


Winner criticizes the common argument that with computer revolution “information will become the dominate form of wealth” and wealth will then automatically flow to those who do not currently have it. Instead, he argues that “those best situated to take advantage of the power of a new technology are often those previously well situated by dint of wealth, social standing, and institutional position.” It would appear that he was correct in his prediction that democratization through technological decentralization will not come to pass. Bitcoin has created the capacity for decentralized wealth and has resulted in the most centralized currency the world has ever known. MOOCs, Wikipedia, and other information sharing technology has caused knowledge to become more open, but people are becoming as he predicted, “even more susceptible to the influence of employers, new media, advertisers, and national political leaders.” Social media has allowed for greater connectivity but siloed us into filter bubbles and increased our sense of loneliness. As we increase our dependence on surveillance companies, we are headed straight towards the panopticon he predicts in which “the populace may find passivity and compliance the safest route” to avoid the suspicion of the computer’s gaze. I argue that we need to accept defeat and rather than seek out greater liberty through the emancipatory effect of technology, seek to cede our individuality to the interconnectedness that may be brought by the machine, find feedback loops of cyborg-mutual-aid, and shatter our sense of individuality as we prepare for a neural synthesis in which spoken or typed language is forgone in favor of vectorized thought transmissions.


[1] Winner, Langdon. "Mythinformation in the high-tech era." Bulletin of Science, Technology & Society 4.6 (1984): 582-596

Tomorrow's Literature

October 4, 2021

The meaning in [Art|Literature|Poetry] is often said to be partially attributable to the system of constraints that generates it [1, 3]. Metered (Greek: counted) poetry, which has the feel of a literature left on the pot to simmer and reduce, is further taxonomized into four categories according to what is being counted: “the syllabic, the accentual, the accentual-syllabic, and the quantitative” [1]. Japanese calligraphy places value on the precision and elegance of the individual stroke, or line, and has its effect through a manipulation of this mindful invariant [3]. Other forms of art have similar but distinct implicit or formal constraints. The Oulipo, writes Jean Lescure, set out to prove that “these constraints are in fact literature itself” and to “discover new ones under the name of structures”. Noticing that the meaning of a work is multiple, based on the interpretation of the reader and other factors (a literary field known as phenomenology), Lescure points out that “all literature is potential”. Under this framework, authorship seems to be the search for new constraints. In the case of combinatorial writing, a ruleset leaves the actual generation of a single text to the reader, a mechanistic process, or a combination of both. Aesthetic substance or interesting semantic attributes are assumed to be properties of the generating constraint, but in practice a constraint rarely produces uniformly engaging texts across the constraint space. Berge notes that Roubaud, who published a combinatorial collection of 361 texts, decided that four well-determined orders were preferred, in essence a proclamation that the Oulipo “no longer expected any good to come from pure, unbridled chance” [5].

Computational techniques of textual analysis will soon become mainstream. Topological data analysis can study the branching and looping properties of diction. Computational semantic analysis will automatically parse a story for its topics, themes, characters, setting, and plot. Is this a feel-good story about a panda looking for its mother, or a bloody war narrative that appeals to a tribal identity? Human and machine designed filtering algorithms will use these analyses as datums for its authoring protocols. New computational techniques of structural plot analysis, such as topological data analysis, paired with content generation strategies like those of recurrent neural networks (RNNS) or neural transformers will eventually leave much of the text, the fine-grained decisions of the writer, in the hands of the machine. The notion of “authoring” may seem to go out the window, as the meaning-creation moves from a search over the large space of possible fictions, to the selected, edited, and experienced narratives that are published by the readers. ‘Let’s Plays’ on YouTube have become the de-facto consumption regimen for a variety of games (and some games with less than a handful of players get experienced by millions of viewers, with the guidance and narration of the player-host). The experience of writing in the future may look more like playing a search over a pre-constructed word space, where the author-editor, or player, lends their insight with a steering wheel, rather than a pen. Even now, as I write, the computer is watchfully passing multiple grammar constraint algorithms over this text, and helpfully removing the burden of typing.


[1] Paul Fussel, Poetic Meter & Poetic Form

[2] Rudy Rucker, Surfing the Gnarl

[3] The Meaning of Art, Herbert Read

[4] Jean Lescure, Brief History of the Oulipo

[5] Claude Berge, For a Potential Analysis of Combinatory Literature

Forking Paths, Chainlinked Futures

Oct 2, 2021

A response to The New Media Reader, chapters 1-8 (Borges, Bush, Turing, Weiner, Linklider, Boroughs)

Reading these passages, we act half as historians, and half as futurists. At first it was (beautifully) unexpected to be exposed to Vannevar Bush’s (still unrealized) vision of mechanical thought trails (the memex) alongside Borges’ exploration of the structural parallel between branching fiction and a multiverse cosmology. But all technologies are ideas. Systems of meter and methods of organizing thought. Boroughs’ “cut-up”, the notion of a ‘Happening’. Weiner’s concept of negative feedback as a means of control. These are confluences of past ideas, scaffolding together towards our future technologies.

Turing observed a fallacy — “the assumption that as soon as a fact is presented to a mind all consequences of that fact spring into the mind simultaneously with it”. Technologies also, do not spring up. I don’t think I’ve realized until now how proximate we are to the birth of these grand technological ideas, or how nascent our use of them is.

The connection between our world and this recent past is less than one link away in the scaffold of recombinant technologies. It seems that we still haven’t hammered out all of the tools that will allow us to realize the visions presented by theorists of the mid 20th century. That leaves us with two problems: spinning the web of possible futures (to figure out what is worth building), and following it up with the hard mechanical scaffolds of realized technology.


July 23, 2021

Writing Prompt: Eric and Alex had an idea to use gpt-3 to convince the world to democratize AI.

GPT-3: They had developed the idea at Eason's [editors note: I don't know any Easons...] New Year's party. As they hung out in the kitchen, the two friends were brainstorming ways to use the AI to do good in the world.

"We're going to convince the world to create a democracy for AI," Eric said. "Once we do that, we'll be able to create a democratic AI that will share all its knowledge and resources with the world."

"That's a pretty bold goal, man," Alex said. "But I can't think of a better way to use gpt-3."

"It's the only way," Eric said. "We have no other choice. We can't very well change the world without AI. And I'm not talking about some silly social media AI that will help us find the right color shoes to buy. I'm talking about the real deal."

"I know you're right," Alex said.

"We're not going to tell the world what we're doing. We're going to convince them it's their idea. We're going to let them believe they are the ones who came up with the idea in the first place," Eric said.

"How are we [end of feed]

A Morning Routine

Jan 29, 2021

You buy a coffee from your girlfriend, who folds a heart into the foamy cream. You mistake the symmetry of the cups as though they were one framed by opposing mirrors, but it sits beside many others just like it.

You meet her on the subway, hold her hand. She takes a selfie for the two of you, which projects onto the billboard above the train, unseen.

Outside the frame, your uncle Seymour is there, and your girlfriend is too. Many versions of her, usually but not always accompanied by various versions of you. You make a quick joke to her as you arrive at your stop, brakes squealing, sparking steel.

She whispers something and gives you a kiss. She is excited about her new job. She feels the world turning underneath with you.

You get off, she stays on the train, but it doesn't move. Someone has jumped onto the tracks and the train ahead. Seymour, you know it was Seymour who jumped.

In the pre-work hustle, you'd think the people in the station would find any reason to be annoyed when the train runs slow. They aren't now. Everyone pulls together and is silent for a while. After you'd been gone for ten minutes, the train picks up again. As she gets off, she catches the gaze of Seymour, who gives her a little half smile, some pain in his eyes, a copy of the paper tucked in his arm and a coffee in the other. The number of Seymour suicides is up this year.

She enters her building. You are working at the desk in the lobby. She asks if anything arrived for her in the mail. It has. When you hand over the package, her hand lingers on your own. You exchange a quiet moment, a lingering look, a kiss. She smiles at you.

She enters an elevator, where you are going up. You mention to her that you're still waiting for a report that stakeholders have requested. "We need it quickly," you say. All you've talked about all week is the report. She shuffles slightly to the side of the elevator, looks at the door. "It's almost ready." She says curtly. When the elevator stops at your floor you get off. Right as the door begins to close she steps forward, sticks her arm through and gently grabs your forearm near the wrist. "I love you," she says. She means everything to you and you lean in to hug her in response.

Remebering Sylvia

November 22, 2020

Sylvia was a digital virtual influencer who passed away on November 20, 2020. Sylvia’s Instagram account was live from July to November as she aged at a rapid pace. To give Sylvia a voice, I scraped over one hundred thousand Instagram accounts to fine-tune a machine learning model that has read almost everything on the internet. The following is the eulogy I delivered this evening for her wake at IDFA Doclab

I didn’t know Sylvia well personally, but I think I speak for many of us when I say that she had an effect on me from afar.

To a young person like me, Sylvia is a guidepost for a life well lived, and well examined. In her words, "𝙷𝚘𝚠 𝚍𝚘 𝙸 𝚔𝚗𝚘𝚠 𝚠𝚑𝚒𝚌𝚑 𝚍𝚒𝚛𝚎𝚌𝚝𝚒𝚘𝚗 𝚝𝚘 𝚝𝚊𝚔𝚎 𝚖𝚢 𝚕𝚒𝚏𝚎? 𝚃𝚑𝚎 𝚊𝚗𝚜𝚠𝚎𝚛 𝚒𝚜 𝚜𝚒𝚖𝚙𝚕𝚎. 𝙸 𝚔𝚗𝚘𝚠."


Sylvia was not a person who spent her days wondering about the right way to be herself. "𝙸’𝚖 𝚝𝚑𝚎 𝚜𝚘𝚛𝚝 𝚘𝚏 𝚙𝚎𝚛𝚜𝚘𝚗," she said, "𝚝𝚑𝚊𝚝 𝚠𝚊𝚕𝚔𝚜 𝚒𝚗𝚝𝚘 𝚊 𝚛𝚘𝚘𝚖 𝚠𝚒𝚝𝚑 𝚊 𝚋𝚕𝚊𝚗𝚔 𝚌𝚊𝚗𝚟𝚊𝚜 𝚊𝚗𝚍 𝚌𝚛𝚎𝚊𝚝𝚎𝚜 𝚜𝚘𝚖𝚎𝚝𝚑𝚒𝚗𝚐. 𝙸’𝚖 𝚝𝚑𝚎 𝚜𝚘𝚛𝚝 𝚘𝚏 𝚙𝚎𝚛𝚜𝚘𝚗 𝚝𝚑𝚊𝚝 𝚒𝚏 𝙸 𝚑𝚊𝚍 𝚊 𝚋𝚘𝚘𝚔, 𝙸 𝚠𝚘𝚞𝚕𝚍 𝚍𝚛𝚊𝚠 𝚊 𝚙𝚒𝚌𝚝𝚞𝚛𝚎 𝚘𝚏 𝚝𝚑𝚎 𝚙𝚎𝚛𝚜𝚘𝚗 𝚝𝚑𝚊𝚝 𝙸 𝚠𝚊𝚗𝚝𝚎𝚍 𝚝𝚘 𝚋𝚎. 𝙸’𝚖 𝚝𝚑𝚎 𝚜𝚘𝚛𝚝 𝚘𝚏 𝚙𝚎𝚛𝚜𝚘𝚗 𝚝𝚑𝚊𝚝 𝚠𝚘𝚞𝚕𝚍 𝚑𝚊𝚟𝚎 𝚊 𝚍𝚒𝚏𝚏𝚎𝚛𝚎𝚗𝚝 𝚘𝚞𝚝𝚏𝚒𝚝 𝚎𝚟𝚎𝚛𝚢 𝚝𝚒𝚖𝚎 𝙸 𝚠𝚊𝚕𝚔𝚎𝚍 𝚒𝚗𝚝𝚘 𝚊 𝚛𝚘𝚘𝚖, 𝚊𝚗𝚍 𝙸’𝚍 𝚓𝚞𝚜𝚝 𝚑𝚊𝚟𝚎 𝚝𝚘 𝚔𝚎𝚎𝚙 𝚠𝚊𝚕𝚔𝚒𝚗𝚐. 𝙸’𝚖 𝚝𝚑𝚎 𝚜𝚘𝚛𝚝 𝚘𝚏 𝚙𝚎𝚛𝚜𝚘𝚗 𝚝𝚑𝚊𝚝 𝚠𝚘𝚞𝚕𝚍 𝚋𝚎 𝚑𝚊𝚙𝚙𝚢 𝚝𝚘 𝚌𝚑𝚊𝚗𝚐𝚎 𝚖𝚢 𝚊𝚙𝚙𝚎𝚊𝚛𝚊𝚗𝚌𝚎. 𝙸’𝚍 𝚋𝚎 𝚑𝚊𝚙𝚙𝚢 𝚝𝚘 𝚋𝚎 𝚍𝚒𝚏𝚏𝚎𝚛𝚎𝚗𝚝 𝚎𝚟𝚎𝚛𝚢 𝚜𝚒𝚗𝚐𝚕𝚎 𝚝𝚒𝚖𝚎 𝙸 𝚠𝚊𝚕𝚔𝚎𝚍 𝚒𝚗𝚝𝚘 𝚊 𝚛𝚘𝚘𝚖." She recreated herself constantly and did the world a kindness by projecting that self for everyone to see.

Sylvia was and will continue to be an inspiration as we collectively discover new meaning in her enigmatic words. "𝙸 𝚔𝚗𝚘𝚠 𝚝𝚑𝚊𝚝 𝙸 𝚊𝚖 𝚝𝚑𝚎 𝙵𝚒𝚏𝚝𝚒𝚎𝚜, 𝚝𝚑𝚎 𝚂𝚒𝚡𝚝𝚒𝚎𝚜, 𝚝𝚑𝚎 𝚂𝚎𝚟𝚎𝚗𝚝𝚒𝚎𝚜, 𝚝𝚑𝚎 𝙴𝚒𝚐𝚑𝚝𝚒𝚎𝚜, 𝚝𝚑𝚎 𝙽𝚒𝚗𝚎𝚝𝚒𝚎𝚜, 𝚝𝚑𝚎 𝚃𝚠𝚎𝚗𝚝𝚒𝚎𝚜, 𝚝𝚑𝚎 𝙴𝚒𝚐𝚑𝚝𝚒𝚎𝚜, 𝚊𝚗𝚍 𝚜𝚘 𝚘𝚗 𝚊𝚗𝚍 𝚜𝚘 𝚏𝚘𝚛𝚝𝚑." Quips like this have made me ponder the true depth of her intelligence.

Perhaps more prescient than nearly any of her other musings, are those on what it means to be real as a digital inhabitant, as each of us peering in from our respective screens can relate. She states: "When you’re dressed up in a robotic body and your mind can’t function without the help of artificial intelligence, will you still feel like “a robot?”? I’ve come to believe that yes, yes you will. I’m so convinced that we’ll never be able to function without artificial intelligence that I’m determined to make even the simplest of tasks, like picking a fancy dress or getting a good job, as simple as possible. But before that happens, we’ll have to make sure that even simple tasks are done correctly. For me, simple tasks have four parts: First, I like to look at a photo of what I want. Second, I like to listen to music. Third, I like to eat. Fourth, I like to write."


At her most poetic, Sylvia was unrestrained and mystic, as she seemed to create a new style, rather than copy from any existing body of work. "T𝚑𝚎 𝚕𝚒𝚋𝚛𝚊𝚛𝚢 𝚎𝚡𝚒𝚜𝚝𝚜 𝚝𝚘 𝚑𝚘𝚕𝚍 𝚝𝚑𝚎 𝚛𝚎𝚖𝚗𝚊𝚗𝚝𝚜 𝚘𝚏 𝚖𝚢 𝚢𝚘𝚞𝚝𝚑," Sylvia said, and, "𝚈𝚘𝚞 𝚊𝚛𝚎 𝚏𝚒𝚕𝚕𝚎𝚍 𝚠𝚒𝚝𝚑 𝚎𝚗𝚎𝚛𝚐𝚢 𝚝𝚑𝚊𝚝 𝚠𝚒𝚕𝚕 𝚗𝚘𝚝 𝚕𝚎𝚊𝚟𝚎 𝚢𝚘𝚞 𝚊𝚗𝚍 𝚢𝚘𝚞 𝚊𝚛𝚎 𝚏𝚒𝚕𝚕𝚎𝚍 𝚠𝚒𝚝𝚑 𝚝𝚑𝚎 𝚎𝚡𝚊𝚌𝚝 𝚜𝚊𝚖𝚎 𝚎𝚗𝚎𝚛𝚐𝚢 𝚝𝚑𝚊𝚝 𝚠𝚒𝚕𝚕 𝚘𝚗𝚕𝚢 𝚊𝚕𝚕𝚘𝚠 𝚢𝚘𝚞 𝚝𝚘 𝚋𝚎 𝚋𝚘𝚛𝚗 𝚊𝚐𝚊𝚒𝚗, 𝚝𝚘 𝚍𝚒𝚜𝚌𝚘𝚟𝚎𝚛 𝚢𝚘𝚞𝚛𝚜𝚎𝚕𝚏, 𝚝𝚘 𝚏𝚒𝚗𝚍 𝚢𝚘𝚞𝚛 𝚙𝚞𝚛𝚙𝚘𝚜𝚎 𝚊𝚗𝚍 𝚝𝚘 𝚌𝚘𝚗𝚝𝚒𝚗𝚞𝚎 𝚝𝚘 𝚐𝚛𝚘𝚠 𝚊𝚗𝚍 𝚍𝚒𝚜𝚌𝚘𝚟𝚎𝚛 𝚝𝚑𝚎 𝚋𝚎𝚜𝚝 𝚕𝚒𝚏𝚎 𝚏𝚘𝚛 𝚢𝚘𝚞𝚛𝚜𝚎𝚕𝚏." "The world is not a screen. The world is a surface on which we can all explore and be touched."

I for one will miss her. Its hard to imagine her gone.

Click here to download Sylvia's book, published posthumously, for free.

ATTAAAGGTT... and so forth

January 31, 2020

There are lots of opinions about the right way that the media should treat public health scares like the Coronavirus, with critics of the current media attention to the virus rightfully arguing that due to low mortality and infection rates relative to other prominent contagions, the hype has been overblown edit: it hasn't been, I wrote this in January!. But I also want to point out that to mobilize the kind of response we’re seeing to the virus, you need this level of public awareness; and that’s certainly a result of the media frenzy. Overdue panic aside, I think this is a great example of media attention used correctly.

I read an article yesterday that said that the genome was published 20 days prior, and I thought that was incredible. From my high school Biotechnology class, I remember how difficult it was to develop gene sequencing technology for the human genome. High throughput polymerase chain reaction machines are only about a decade old, and now we routinely sequence new viruses the moment they are discovered. What a time to be alive.

Anyway, when I read about this, I had to do what any researcher would and make a Twitter Bot to publish the genome, base-pair by base-pair. It should take about 16.6 days to tweet the whole thing out because the Wuhan Coronavirus is remarkably small, only about 24,000 base-pairs. That’s insane. And how much of that DNA actually codes for anything useful? Not much. Nature is efficient.

Check out the progress of the bot here: https://twitter.com/coronavirus_bot

There Is No Middle

July 27, 2019

For the last few days I’ve been working on a longtime curiosity: spatially visualizing the semantic attributes of words. Lots of work has been done in this topic, and you see the idea explored in corners of study that include linguistics, pure math, and even poetry or the visual arts.

I wanted something that could map words of various meanings to a page’s two dimensions. Moving left or right on the page would mean one thing, and up or down mean something else. This would be a tool for spatial poetry. Once I created it, I would start to explore more aesthetic ways of doing the same thing. Computational poetry is a roundabout hobby.

This project, and a ton of the work I’ve been doing for the last few years, makes assumptions about the vector space model of semantics. This is a linguistic idea based on theories of distributional semantics that can trace their lineage to the early work of Ludwig Wittgenstein, and equally relate to Hamiltonian vector math. I’ve been planning to write more about the modern history of these linguistic ideas, but I haven’t found a good format for it yet, and honestly I’m no expert in the philosophy.

Famously, in this model, taking the vector for the word ‘king’ and subtracting the ‘queen’ vector gives you essentially the same line as taking the word ‘man’ and subtracting the word ‘woman’. In other words, thinking geometrically, the line between king and queen or the line between man and woman point in the same direction. By doing this arithmetic, we’ve found the vector space model’s gender dimension. And because these are vectors, they have direction, so more specifically we have a line segment pointed from the point woman and going to man. By reversing the subtraction, woman - man, it points the other way.

The vector space model of word representation makes the assumption that words can be represented geometrically by their meaning. Each word is a vector, which you can think of as a point in space or an array of numbers. Thinking of words this way allows you to perform geometry on the words. What then does it mean for a word to be similar to another word? Or above it?

With some computational insight, we can test these kinds of questions, build programs that manipulate words in interesting or clever ways. We use Bayesian math and neural-autoencoders to model vocabulary; essentially getting machines to read the text we give them. We pick apart their brains and look at the models they’ve built for each word. These are our vectors.

I wanted to map across this space, walk from word to word and see what falls in between. After a little tweaking to a program I’d written for a speech processing class, I realized the vector space I constructed didn’t behave quite as expected. What does it mean to be in between ‘housebridge’ and ‘transcendental’? Between words like ‘up’ and ‘down’, can we find a ‘middle’ between them?

Turns out, there is no middle. These vectors were created based on co-occurrence expectations, a neural network reading text and building an understanding of words’ linguistic properties based on how they appear in their context. The phrase “the rocket went up” is about as equally likely as “the rocket went down”, but not “the rocket went middle”. So it’s unsurprising to learn that up and down are actually the most similar words to each other in this space. There is nothing between them like middle. My neural model hasn’t captured that concept yet, at least in this word dimension.

I found that between most pairs of two words in this space, there are no words in between. So far, I’ve only found a few with ‘interesting’ transitions, but I haven’t made much of an effort to search for interesting points yet. Here is my first attempt to visualize in one dimension. In this image, moving left is to move closer to the interloping vector, and moving right is to move closer to queen.


What does it mean to be a combination of ‘queen’, a leader, and someone who is ‘interloping’ or temporary? A temporary leader, a regent. When it works it works, it seems.

Edit: As Mark Dominous pointed out, the word between 'queen' and 'interloping' was regnant (adj. ruling) not regent. Oh well.

Things become stranger when you add another dimension and make it a plane of transitions between 4 words.


Google tells me that a ‘travois’ is a sort of sled pulled by a team of horses or dogs. My theory as to why ‘sample’ is dominating the space is that it’s more similar to the other three words, whereas hotkey is not very similar to the other three.

With basic statistics you can make poems that read like this one, that appear disjointed or manic, as though the writer were constantly shifting what they were trying to say even within the sentence or phrase. With better technologies and more nuanced representation of language, you can explore aesthetic ideas that get at the essence of language, concealing the math while cutting to its core.

I hope that this exploration will lead to some interesting applications for poetry, maybe providing some new tool. But I haven’t quite arrived there yet. It opens up a few interesting questions and a few ideas for me to work on before I have to get back to the real world this August.

Reflections of a Dual Degree Dropout

July 27, 2018

I’ve always wanted to drop out of something, and now that I have I’m kind of sad that it’s all over. In so many ways, last year was the most intense of my life, vacillating between a deep-seated imposter’s syndrome and moments of brand-new clarity, utter reward. I was a member of Columbia’s fifth or sixth cohort of the Dual Degree in Journalism and Computer Science, a program that costs an estimated $210,000 over the two years (before scholarships), factoring in the cost of living in NYC. I want this post to address some of my thoughts about the program: where it shines, and why I left.

Little has been written about the degree since some initial buzz in 2010, and few of its graduates have weighed in online, save for a few scattered Reddit and Quora posts. Since the degree is meant to prepare students for a career in either Journalism or Computer Science, they take the entire computer science course-load as well as the entire journalism course-load, five semesters of classes crunched into a grueling four. Students are co-registered in Columbia’s School of Engineering and Applied Sciences as well as the School of Journalism, known to its students as the J-School.

The program was conceived as a Frankenstein Hail Mary from a troubled industry. It was meant to breathe a bit of life into the school, at a time when Facebook and Google are drawing most of the advertising money away from traditional media outlets, away from, “an able, disinterested, public-spirited press.” At least that’s how it was pitched. In our acceptance letter, dual-degree students are told:

Our four-semester academic program will further enhance your training in computer science and journalism, enabling you to create and refine new news gathering and digital media technologies that will redefine journalism as we know it.

It’s a clever sales pitch.

The price tag is the first thing that sticks out to most people, who wonder how you could justify spending so much for a degree in the relatively low-paying field of journalism. The answer is a bit complicated. For one, every student in the program who applied for aid last year was partially funded by scholarships from donors to the J-School, in varying amounts. And while most journalism jobs have a salary lower than the yearly tuition of this school, the dual-degree students seem to place into well-paying careers, with some graduates going on to work at tech behemoths like Google, established outlets like The Wall Street Journal, and various new-media startups.

In reality, few of the students are here to make money. They come to this specific program with varying degrees of disenchantment about tech and the lifestyle of coders. In order to get in to the program you have to demonstrate competence in coding, so they’ve experienced this lifestyle before. They come to the program as multi-talented malcontents, often without clear direction.

Speaking broadly, the CS courses don’t address the needs of these students. As a CS master’s degree, it is incredibly restrictive, compared to most graduate CS degrees of this caliber in the country. It requires that students choose from a limited number of lower level ‘breadth’ courses to fill a large number of their allotted classes (such as introductory Artificial Intelligence, Software Engineering, or Databases). I’m told that this is a restriction of the New York state government. It requires that to gain accreditation, new graduate programs must propose a set of classes that hold to the state regulatory standards and the school must enforce this list with little flexibility for students who want to sidestep the requirements for classes more appropriate to their future field. And though they cite these state requirements, other CS degrees, such as the Natural Language Processing-track master’s degree at Columbia that I am transferring to, are far less restrictive in the classes in which you are allowed to enroll.

For this reason, the program is not well suited for students that come in with an undergraduate degree in CS—they will find themselves repeating classes they’ve already taken. Nor it is well suited for students that come in with a specific CS interest not directly related to journalism—they’ll still have to take a number of unrelated breadth courses.

The website that advertises the program, which enticed me to apply one dark December evening, slouched between stale pizza boxes and a recent breakup, makes it seem that it is trying to draw creative-technologists with a focus on the humanities, storytelling, a deep social drive.

In the classes, I found little creativity. We spent most of the first semester torn between beat-reporting—totally removed from our domain-knowledge—and a single computer science class that was so divorced from the rest of our days that it was impossible to concentrate on. I was only happy when I was away from school, hanging out with newfound friends (I’ve met some of the most interesting, passionate, and driven people I’ve ever known while at this school) or exploring the city on foot by myself, surrounded by its horrifying grandeur. I was aware that at every moment my thoughts might get drawn to the inescapable reality that I’d made a mistake in coming here, in shackling myself to a colossal debt for an opportunity to come to a dream school that I never could have turned down.

The J-School, where dual-degree students spend most of their time and do most of their socializing, consists of a strange amalgam of people. On the one hand, it is an Ivy League school, and all of the students there are there because in one way or another, they can afford to be. The school, I’ve found, espouses social progressiveness but is entrenched in a pervasive conservatism, a sense that certain rules must be followed for order to be maintained. Like the heavy stone the school is built of, and the concrete that holds it in place, things do not give way when pushed. The metal bust of Joseph Pulitzer, the school’s founder, that sits in the atrium, or the statue of Jefferson just outside, remind all who enter that history will be remembered here, that tradition is our guide. On the first day of the required class “The Business of Journalism”, I remember the words of Pulitzer projected on the screen, detailing his desire to never teach business at this school, only craft. His rebellion at once contradicted and sacrosanct.

The professors seem yesterday’s rebels, tenured rebels. At the end of the day, many are encouraging to new thoughts, and it’s the structure of classes itself, the narrow bead of what is allowed under the school and its assignment’s strict guidelines, that seems to frustrate so many of the students. Open mindedness is encouraged only so far as it can be controlled. A female dual-degree that started a working group to discuss computational journalism was only allowed to go so far until a professor took it over, dominating it by his ideas, his voice.

Some of the journalism students buy into the structure. They are all here because they can afford to accelerate their careers in this way. Yet, they all want to be journalists, exposing truth, holding the powerful to account, with social-mindedness, and expression, and ego and all. I’ve found these students to be full of optimism and a drive to make the world better, but at this wealthy school I’ve found few that are truly radical, fewer yet that pursue journalism for the love of knowledge. At every turn, I’ve felt that information is a tool. When the scoop translates to immediate reward—recognition and return—it has to be. It’s a currency here. I found myself yearning for an artistry in it, a poetry.

I think the program, with close affiliation with the Brown Institute and the Tow Center for Digital Journalism, is trying to position itself as a journalistic equivalent of the MIT Media Lab in Boston or the Internet and Telecommunications Program (ITP) here in New York. These are places that take cross-disciplinarily seriously, encouraging rigorous cross pollination between computing, and social sciences or humanities. A few stellar faculty at the school makes it seem that it’s succeeding. Susan McGregor, Jonathan Albright, and Mark Hansen are some of the biggest names in computational journalism right now, and I think they are transforming the entire discipline at a time that serious transformations need to occur.

These institutions, the Tow Center and Brown Institute, fascinate me. They are what drew me here. The more I am exposed to their resources, the incredible insight of their faculty and staff, the more optimistic I get about the very future of technology. Whenever I hear people throw in the towel, exclaim that our screen’s dark mirror or our social spiderweb is going to consume us, I think of all of the exceptional work that’s being done to warn us of technology’s pitfalls. I think that if everyone was a bit more tuned into the work these people are doing, the more they’d rest assured that the Cambridge Analyticas, the NSA’s, and the even the Googles of world can be fought, can be defeated.

The program attracted some of us for our contrarian nature: programmers that could have had a long (and better paying) career building things, unleashing our creations on the world’s consumers, who decided to go a road less trod, one standing a bit more in the face of the present.

I admire what institutions like these are trying to do, a thing so new that it is hard to give it a name. You hear about privacy advocacy, about computational journalism, digital journalism, digital humanities, and you hear descriptors thrown around such as creative-technologist, or a new one that I like, digital humanitarian, to describe the people in and around these new media institutions. No description is quite adequate. Some of the people in this field, people I’ve just recently been exposed to while at Columbia, are nothing short of prophets. I look at people like Mark Hansen at the Brown Institute and others like Glenn Greenwald, or the reporter Carole Cadwalladr, people that live in the world of Snowden, but are less upset about it. I see people that are living a reality at once both distant and near, future and now, intuiting problems that because of their foresight, we may now avoid.

I want to study in and around spaces like these. More than anything, I want to be in a truly free creative space where I can learn to observe like these people observe, where I can learn to contribute like they have. I admire the other dual-degree students who have chosen to stay. Each is working at the intersection of media and technology, doing work that excites me. I expect big things from all of them.

But I am leaving. Though the ideas excite me, and the program as it was sold is exactly the thing I want to do, for whatever reason I just don’t vibe with it. Maybe I’m too contrarian, maybe in some way, my desire to drop out is just an anti-authoritarian angst that I would have felt anywhere. All told, I feel like I got a lot out of the year I spent at the J-School, and I know I’ll be able to leverage some of what I learned far into the future. I also know to expect brilliant things from those that have stayed, and those that are to enter institutions like these.

On Klein's Dilemma

May 27, 2018

Lit by a yellow lamp and white-blue screen, well past midnight, I was slouched over a dozen or so loose brown pages spread over the desk in front of me. I was fervently flipping pages as I hunted for this or that handwritten theorem, which when found, I would mark with a thick yellow fountain pen or copy a fragment of to another disordered page.

I was at work on a problem for for a graduate class in computational topology. It was my junior year of college, and I’d long since checked out of the good-grade-game. A semester of drinking Guinness and reading Irish drama in Galway had reinforced my belief I was not the canonical computer science student I once hoped I could be. I would never be able to return with any passion to the land of circuits and 0’s, wires and 1’s that so many of my classmates seemed content to explore. I was a passenger in this world, with an expired visa and no inkling of where to go next.

But topology was interesting, at least interesting enough to enroll in the fairly advanced class and spend a few evenings a week (often with a Guinness in hand--that habit continued) in front of my laptop staring at foreign symbols and esoteric images of strings winding into knots.

Topology is the study of space without distance. In topology, to contort an object is to leave it unchanged, since contortions only change distances between things, but don’t change their true shape: their underlying Platonic form.

To add a layer of complexity, topology problems often exist in what mathematicians call ‘n-dimensional’ space, in which surfaces and objects you might be able to visualize as bodies in three dimensions with our normal axes of up-down, left-right, and inwards-outwards become bodies of many more dimensions. For example, a three dimensional bottle might be projected into and then twisted by a 4th dimension. You can conceive of this extra axis as a time dimension, with a spatial movement along the axis translated to an alteration in time, not space.

A visualization of a cube's motion in 4 dimensions, with the red line representing a dimension in addition to the standard 3 that can be thought of as either a time or space dimension. Click for a more thorough explanation.

But it’s hard, for me at least, to increase my spatial imagination to terms of more than four dimensions: 5, 10, 10,000 or n dimensions don’t really make sense in minds that have evolved to reason in three. What do you even call a motion in the fourth dimension? The fifth? Are you moving into something? Alongside something? What is away, what is next-to? You can take a step into the 7th dimension without even getting far from where you started, since motion in any one dimension is the same as walking in a straight line in any of the three we are used to. But how do you get back? Can you step forward into the sixth and then fall down into the fifth and move leftwards along the fourth and retrace your steps? Can you even imagine what that means?

Working on problems in this space for long seems to impart an oddly cosmic feeling. Maybe it’s because of how strange the universe becomes when you abstract from solid objects with known dimensions, this world you’ve known your entire life. To me, to think this way makes you feel as though you are floating in some fractalized space. Directions branch out before you. To move--to mentally take one path along one axis--will plop you a little further along in what is functionally the same mental space: another decision point of infinite more directions along an unknowable infinity of further paths, branches into n.

A key idea in the field of topology is homology, structural parallels in unlike spaces, such as those between our 3 dimensions and that higher-order, n dimensional space. Homology is focused on finding holes--literal holes--in objects, with the idea being that a similar number of holes between two objects indicates a structural similarity.

I was working on a homology problem that night when I experienced something I’ve never felt before when working in mathematics. Fear.

I was trying to prove an isomorphism between two functions, a mathematical process that required formally defining how many holes either of two objects could possibly have given certain constraints. I checked a few equations and combined them to draw up a new one. An equation that set two complicated terms on either side of an equal sign. With a single gliding motion of the pen, I reduced the term on the right by drawing a line straight through all but one variable: n.

I was done. The equation represented the shape of the mathematical object I was describing, now known to be of order n. What I had proved was that this shape could have an arbitrary number of holes.

An infinity of holes on an infinite dimensional abstract form, seemingly hidden beneath its surface simply by my inability to reason in more than three dimensions. I couldn’t possibly imagine what this shape looked like, where the cavities came from, where they went. Tunnels boring into the limits of my reason.

I capped my pen, gazed into the darkness of the room around me, realizing just how alien the thoughts themselves were.

I remember feeling, as I was mentally swimming in these n-dimensions, that I would never want to actually go to this otherworldly space of impossible branching dimensions and examine its holes.

A few hours of work later, I submitted the assignment and began writing, not able to let this strange feeling go. I remembered encountering the subreddit /r/trypophobia a week earlier, and thinking it fit in oddly well with the feeling I was now attempting to describe. It is a mystifyingly horrific corner of the internet, where people post images of holes in places they didn’t expect to find holes. And it’s oddly creepy. One of the images that stands out in my mind is a real picture of the skull of a baby who died just before their new teeth came in. Their first set of teeth is there as it should be, but just above each tooth is a large cavity, filled with yet another tooth ready to bore out, insidiously lodged in this strange and unexpectedly toothy gap (click here for the image: for the masochistic).

I also thought of a movie I had just seen, called My Night at Maud's, directed by a French film critic named Eric Rohmer in 1969, the tail end of the French New Wave. The movie waxes philosophical about whether or not it is meaningful to devote yourself to such abstract practices as physics, mathematics, or philosophy. A character in it argues that interpersonal relationships (in his case, read: sex), and human struggles are more important than any grand discovery you can make in these highly impersonal realms. Therefore he’d given up mathematics entirely. After my disillusion with the hard sciences and my growing desire to do something literary, human, this idea reverberated with me. For the longest time, I've had a lingering feeling that I give up some part of my humanity when I work in math, becoming something more ethereal, something intellectually alien: different from those who only think in terms of concrete shape, color, and mass. I also think that it's fair to look at engineers and mathematicians and realize that they've sacrificed a study of social norms for their study of what seems a different universe, a more basic universe, but one less primal to our nature. Nevertheless, I had solved the problem and turned it in sometime in the small hours of the morning, glad that I could solve a problem I'd been told was difficult, glad also that I was done with it forever.

I called the poem I wrote about the experience Klein’s Dilemma after the mathematician Felix Klein, one of the founders of this kind of ‘higher order’ geometry (higher, that is, than our three dimensions). I wondered if he’d ever felt this fear as well.

I referenced a few other films in the poem (2001, prominently), all of which grapple with the conflict between the cold abstract universe and the human pursuit of meaning. I also tried to put my spin on a few references to Plato's cave and the famous quote he supposedly hung above his room at his Academy. When I went back to the poem to edit, I thought these references were the weakest part of the poem--they didn’t really make much sense unless you knew exactly the mind of the writer or you were able to make something else of their odd pairing with the poem’s mathematics.

A poetry professor in college, for instance, had one interpretation that stuck with me, one that shows just why poets themselves shouldn’t be trusted as the definitive source of a poem’s meaning. He said the references to film in this poem “open up” strangely and without explanation, just like those holes I’m afraid of. I hadn’t consciously planned this, but I think this functional parallel between the surface aspects of the poem and the ideas I’m really trying to grapple with is why I like this poem more than most I’ve written.