Drawing Music Part I: Building the Circuit

Tangible Interactions

Assignment: Make a musical instrument using the MIDI control protocol.

Concept: An interface where the user draws on a piece of paper to make music.


Layout: I knew that I was going to make homemade force sense resistors, but I wasn’t sure about the layout. At first I thought I would have three or four sensors of equal size side by side, but then the assignment of notes would feel too arbitrary. I liked the idea of concentric circles, but those don’t lend themselves to paper’s rectangularity. I finally decided on nested rectangles. The outermost FSR would produce the lowest notes, and the innermost FSR would produce the highest notes.

Ground Layer: Three pieces of conductive fabric and three wires leading to ground.

Complete Circuit: Sandwiched between the two layers of conductive fabric is a layer of Velostat, a material that is conductive and pressure sensitive. I think I must have made an error somewhere because when I press down on the FSRs the resistance goes *up* instead of down…but each FSR is giving me a fairly consistent baseline, so I think I can work with it!

Screening Information Response

Canvas for Public Discourse

“Writing always involves this screening of this spectral interplay of parasites and hosts”

Mark C. Taylor

The first thing that jumped out to me in the reading was Taylor’s description of the writing process–an interplay of parasites and hosts. He uses familiar imagery to refer to his literary influences, both conscious and subconscious. He refers to these influences as ghosts that haunt him as he writes. He also refers to them as parasites; their continued existence and relevance depends on contemporary writers like Taylor, so in that sense Taylor’s writing is like a “host”. At the same time, Taylor thinks of himself as a parasite. He lifts passages and ideas for his own gain. His writing would be anemic without the blood of his predecessors.

I am immediately skeptical of this line of thinking. Certainly there is some truth to it, but I am frustrated by the trend of using scientific concepts as metaphor for concepts in art or the humanities. In science, parasitism implies that one organism is actively harmed by the actions of another. Taylor doesn’t really make the case that he is harmed by his literary influences, nor that his influences are harmed by him. In my opinion, the relationship is closer to comensalism–Taylor’s writing is improved by references to Augustine, but Augustine is neither hurt nor helped by this interaction.

In a similar vein, I am somewhat troubled by Taylor’s references to “survival of the fittest” outside of its scientific meaning. So-called “Social Darwinists” co-opted these same concepts to imply that people of color were less “fit” than Whites. I don’t think that Taylor is being insidious; only that he is using the caché of hard sciences to uplift his own work (now that’s parasitism!) In science, fitness has a very specific meaning–it refers to the ability of an organism to succcessfully reproduce. The problem that I have in Taylor’s essay is that he has not completed his metaphor. He states that in a conversation, ideas that are not “fit” do not survive…but he does not explain what it takes for an idea to be “fit”. What is “fitness” in the context of thought? Is it thought that persists in one’s own mind? Or a thought that gets passed to many individuals, like a meme? Must the thought be insightful? Or can it just be the thought of an adorable cross-eyed cat? Is a cross-eyed cat an insightful thing?

3 Minute Presentation: The Melissa Calculus

Canvas for Public Discourse

Once I was sitting in a coffee shop and a woman wanted something from me. What she wanted was slightly unusual. She turned to me and said that she felt she was receiving a calling. She asked, “Would you mind if I prayed for you?”

I’m a godless woman, and so I said, “sure.”

She asked me to describe the troubles in my life so her prayers could be more specific, and she held my hands as she said a prayer to god, out loud, in a coffee shop.

I later told my godless boyfriend Max about the encounter, intending it to be an amusing anecdote. I was surprised how Max’s face immediately turned sour.

“You let her pray for you??”

“Well, yeah, I mean, why not?”

“This woman is such an asshole! She could have prayed silently to herself, but she had to interrupt your whole day to prove how pious she is!”

“But I mean, it clearly meant so much to her to let her pray for me, and I feel completely neutrally about it.”

Max continued, “It really bothers me that she thinks she did a favor for you, but really you did a favor for her.”

I said, “It doesn’t bother me. If I wind up feeling neutrally and she feels really good about herself, then that means I did the right thing.”

Max responded, “Sometimes your Melissa Calculus makes me really mad.”

The Melissa Calculus is a term that my boyfriend coined. It’s a cost-benefit analysis that I do when someone wants me to do something for them. I think of what I have to lose from the interaction, and what the other person has to gain. The Melissa Calculus states that if you can reasonably assume that the other person will gain more than you will lose, then you should participate in the interaction.

Sometimes the losses and gains can be quantified. If you live or work in an apartment building with a terrible elevator system, you may want to hold the door when you see a person running for it, rather than frantically hit the “door close” button. You’ll only lose about 10 or 20 seconds, but the other person would have lost 1 to 3 minutes waiting for the next elevator.

This is not to cast judgment on anyone who lets an elevator door close. I have have often used the door close button, sometimes with vigor, sometimes with spite. But if you are ever unsure of what you should do, I find that it is often helpful to let the Melissa Calculus decide.

It works even when people aren’t specifically asking for something. You might take 5 minutes to write to your 3rd grade teacher on Facebook about how you found her really inspiring. Whatever it costs you to set 5 minutes aside and compose a post, it may be a dozen times more meaningful to the teacher who receives that post.

There is a flaw with the Melissa Calculus. It requires you to make assumptions about people, often times people you don’t know very well. Maybe your 3rd grade teacher came to hate the public school system and is now anarchist. Maybe she’ll comment on your post by telling you that you were a lousy third grader and you should go fuck yourself. It’s a matter of weighing probability.

Then there’s the matter of figuring out how much your time and energy are “objectively” worth. I’m a person who has depression, and a symptom of depression can be assuming that you are worthless. Therefore, it doesn’t matter how much psychic pain I endure, if it makes someone else happy. The Melissa Calculus only works if you have self-worth. The Melissa Calculus asks that you take care of yourself first.

Really what the Melissa Calculus wants to remind you is that it is often the case that small inconveniences for you can make other people feel really good. It’s like using a lever, or a pulley. You don’t have to tug the rope that hard to move what seemed like a mountain.

The Medium is the Message: Response

Canvas for Public Discourse

Leonard Doob, in his report Communication in Africa, tells of one African who took great pains to listen each evening to the BBC news, even though he could understand nothing of it. Just to be in the presence of those sounds at 7 P.M. each day was important for him. His attitude to speech was like ours to melody— the resonant intonation was meaning enough.

Marshall McLuhan

There are many ideas in McLuhan’s essay that I sympathize with. He excoriates a general who argued that the “products of modern science” are not inherently good or bad; their value is only revealed in their use. I agree with McLuhan here–the General is peddling a more eloquent version of “guns don’t kill people, people kill people”. We should be critical of firearms regardless of whom they are fired on. McLuhan responds to the General with sarcasm: “Apple pie is in itself neither good nor bad; it is the way it is used that determines its value.” His point being that apple pie is a form of technology, and a person can certainly come to a conclusion about some of its qualities before taking a bite, or throwing the pie in someone’s face. Though there are many possible “uses” for an apple pie, but it does not sit in an objective neutral state until it gets used.

I also think about McLuhan’s essay with regards to an artist I know. Though she trained as a visual artist for many years, a few years ago she decided she wanted to pursue poetry instead. I am a writer (but not a poet), and I found myself very frustrated by her pivot. She had spent years studying visual art, and is really good at it! It seemed so presumptuous to simply decide to become a poet.

I recall her finding a dead moth on a windowsill, squealing with joy at the providence of finding such a beautiful dead thing, and sitting down to write a poem. I read the poem–and I thought it was terrible. I thought to myself, shouldn’t she have just drawn the fucking moth? The girl can draw, she can’t write!

I felt like she was doing the world a disservice by creating a dumb poem, rather than a good drawing. But it’s also fair to say that the world doesn’t need a drawing of a dead moth either, even if it’s quite a good drawing. It makes me wonder, what does a poem do that a painting simply can’t? Why did she find herself so enchanted with poetry, and so disenchanted with drawing? I’m trying to ask, are there merits of writing a bad poem because of the nature of the medium?

When I return to McLuhan’s quote above, I find myself irritated–a similar kind of irritation I had towards the bad poem. What is the man really gaining from listening to a radio broadcast he can’t understand? He is well within his rights to do so, but wouldn’t his time be better served elsewhere? McLuhan argues that radio can communicate something outside of its content, such that it may well be worthwhile to listen to a radio show in a language you can’t understand. But what is that thing being communicated? Intonation? I would argue that intonation becomes much more important when it is partnered with content, language. McLuhan says that it doesn’t matter if a train carries gunpowder or grain. It matters to a militia if there is no gunpowder. It matters to a starving town if there is no grain.

Painful Objects Proposal

Data Art


A few weeks ago I walked around my apartment and recorded all the objects that at one or multiple points had caused me physical harm. I was interested at seeing how many hazardous objects there were, where these things were located, and ranking the the amount of pain they caused. Most of all, I wanted to write about the experience of getting betrayed by stuff that was supposed to be on my side (though I should probably resist the urge to anthropomorphize, I never seem to be able to).

For me, there was something cathartic about recording these painful experiences. So my proposal is to create an online space where anyone can contribute their objects, and view all the objects that have been submitted.

Visual Representation: 

The basic concept is to depict red droplets within a frame. The frame represents the home, and the droplets represent the objects/experience of pain. Here are the variables I want to use:

Size of droplet = # of painful incidences
Saturation of droplet = amount of pain from 1 to 10
Bluish hue = if there was emotional pain and how much (from 1 to 10)
Droplet position = clustered based on location of object in home
Mouse position = Hover over droplet to reveal information about the object

I’m most conflicted about how to represent the “home” and where to place the droplets within the home. This is because everyone’s home looks different! Should I draw lines to demarcate rooms, or is that too literal? Should I make it look like a blueprint, or is that way too literal? For the time being, I’m modeling the home based off of my own apartment (since that’s the only data set I have so far).


I created a few drawings in Illustrator to brainstorm what the web page might look like:

I also made a quick p5 sketch of a potential droplet:

I decided to make a physical representation as well. I used a mug of water and a plastic chopstick to collect water droplets.  I put droplets of water on a piece of paper (1 droplet = 1 incident, 2 droplets = 2 incidents, and so on) and then I dipped a red pen into those droplets (1 dip = 1 on pain scale, 2 dips = 2 on pain scale, etc.) Unfortunately the first couple of droplets sapped nearly all the ink out of the pen, so the saturation is too weak overall. I thought I was very clever with my chopstick method but I should’ve just picked up some cheap watercolors and brushes from a drug store. Here’s the result:


If you’d like to add to my dataset, here’s the form!

Zora’s Astonishing Circus Acts: A Storybook Game

Designing Games for Kids, Featured Posts

Assignment: Make a game for little kids (ages 4-6)

Concept: Write a children’s book that has a game embedded into the story.

Research: The first thing that I did was look up other children’s books that had a similar concept. I found a lot of books that had clever lift-the-flap mechanisms:

Dear Zoo by Rod Campbell

Paper ZOO by Marya Dzianová’s

I found other books that had different kinds of animation, like Emily Cedar’s “What Makes the World go ‘Round”:

I also found out about the incredible Hervé Tullet, who is known in France as “The Prince of Pre-school books”. Two examples seen below are The Finger Circus Game and The Game of Shadows:

Because I’m not a visual artist, I didn’t want the game to be based on a clever visual or tactile effect. Instead, I wanted to think of a way to get the children playacting and have some agency over the story.

Refined Concept: I realized that kids love pretending to be animals. So I decided that the main game mechanic would be having kids act out animals doing silly things. I made a long list of animals that I thought young children would recognize and also enjoy mimicking–like jellyfish, shark, grizzly bear, dog and chicken. Then I made a list of actions that included surfing, playing guitar and practicing karate. I used a variety of verbs (instead of just “doing”) in order to make it more educational.

The next step was figuring out what kind of story would facilitate that kind of playacting. Perhaps with Herve Tullet’s Finger Circus fresh in my mind, I realized that a circus would be the perfect place for these animals to perform.

Fabrication: The story has gone through three drafts and two physical prototypes. I created two decks of cards for the animals and the actions that the children would draw at random on their turn. Because I used 20 animals and 20 actions, that means there are 400 possible combinations!

The first prototype used velcro, which made it really easy for the kids to stick their cards directly onto the page of the book. Unfortunately, it made it impossible to stack the cards in decks, and also made the book bulkier. For my second prototype I decided to use plastic sleeves that the kids could slide the cards into, but that made it much harder for the kids to place the cards. I think the plastic sleeve is more elegant than velcro but the design needs some refinement.

Playtesting: So far I have playtested the book twice. Once with my professors kids (who are ages 4 and 8) and with a whole classroom of preschoolers. My professor’s kids really enjoyed it (and they loved goading their dad into acting out animals as well), and it was a huge hit in the classroom! The kids were rapt the entire time, even though my book doesn’t really have illustrations yet (the only illustrations I have are of the different animals). A few of the kids who didn’t get a turn wouldn’t let me leave the classroom until I promised that they would have a turn next time!

Mushroom Death Remediation

Fungus Among Us

A few weeks ago I watched this TedTalk given by Jae Rhim Lee:

Her message really resonated with me. I understand the temptation of family members to try to preserve the bodies of loved ones after death, but for my part, I don’t want anyone looking at me after I’m dead, making comments how good I look (considering the circumstances), and admiring what a good job the mortician did. I don’t want my body tossed into the Earth like a leaky formaldehyde bag wearing lipstick. My grandmother’s wake was horrible for me. She didn’t look like herself at all. It was like we were burying a stranger.

Jae Rhim Lee created a mushroom burial suit. It costs much less than the average casket, and it’s far better for the environment. Lee has trained fungus to get good at eating what will be her remains by feeding it her skin cells, hair, nails, sweat, and blood. Even though it might seem morbid to teach an organism to eat your body, I thought there was something poetic about it, and it inspired me to write this short science fiction piece:

A way in which I might extend this project is to have a podcast that features a science fiction story and a non fiction piece that discusses some of the real science referenced in the story.

In the meantime, I’ll continue thinking about how we can use fungus to normalize death and decomposition.

Gramma Bot: Twitter Bot Final

Featured Posts, Twitter Bot Workshop

An anti-harassment twitter bot that questions the offender about their decision to use inflammatory language.

I was inspired by a teacher friend of mine who uses a socratic technique when his students call each other names. “Why did you call her that? What does that mean?” I wanted to use a bot to initiate conversation (with the bot saying something like, “Why did you feel like using this word?”) in order to make people reflect on the language they use and how it affects others.

One of the bots that inspired this project was Kevin Munger’s anti-harassment bot geared towards racists. The constraints placed on the bot were smart. It was only looking for the n-word, only when combined with an @ reply, and it checked the user’s timeline for prior offenses. Other important measures were taken that wouldn’t be feasible for my project–manually inspecting the profiles, and manually checking to make sure the two users in the interaction aren’t friends. Furthermore, in order for Munger to run his experiment, he had to hide that fact that he was using bots. I had decided that I was going to be transparent about my bot’s bot status.

I also read studies that had already done textual analysis of slurs used on twitter, like this one. Reading studies like this were important, because I realized that there was no magical Markov chain that was going to help me identify harassment on twitter without false negatives/positives. Even human experts can’t agree on what constitutes harassment. Here’s a quote from the study I linked to: “In manually coding, analysts had considerable difficulty achieving inter-annotator agreement (the extent to which both annotators agreed on the meaning of the same tweet).”

Finally, I wanted to see what other sorts of anti-harassment bots are out there. Even though there are quite a few, I had to restrict myself to bots whose code is written in javascript. This source code really jump-started my project. This is a simple bot created for a hackathon. It takes a whole slew of offensive terms and gives them different weights (for example, both “cunt” and the n-word are given weights of 3, while “fat” and “shit” are given weights of 1). If a user tweets something with a weight greater than 3, then the bot tweets out the user name and says “this comment has been marked as offensive and has been recorded.”

There are some glaring problems with this bot. If I tweet out, “I’m so fucking mad, someone just called me a cunt,” then I would get flagged for using a combination of the words “fucking” and “cunt”. That’s what you get with contextless word counters. They can’t tell the difference between a complaint about getting harassed and actual harassment (like, “You’re a fucking cunt.”) Further more, I didn’t want to call out users on a tweet-by-tweet basis. I wanted to track their behavior over time. A person could have a hundred reasons for using the word “bitch” in a tweet. But it’s definitely fair to call them out if they’ve tweeted the word “bitch” a hundred different times, no matter the reason.

The Ideal Bot:
I’m calling my bot “GrammaBot” because I want it to be satirical, rather than preachy. GrammaBot will track the words “bitch” and “cunt” only, because I want it to be relatively limited in scope. It will also only look at users in the United States because people in the UK seem to have a very different relationship with the word “cunt”. If a single user says either of these words more than 4 times, the bot will mention them in a tweet and say some variation of, “You’ve said the word ‘cunt’ 5 times since [date]. GrammaBot is wondering why you keep saying that word!”

Here is the source code for my bot:

So far I’ve only tested my bot in the console log (so I don’t get immediately blocked by Twitter). This is a video of what it looks like when I run my code. Because I’m using a personal account I’m tweeting the term “blahblahblahblah” instead of “cunt” to test that everything works:

Right now I’m only tracking “cunt” instead of “bitch” and “cunt”, which I actually think is good because it’s limiting the amount of data that’s coming in. Unfortunately I haven’t been able to figure out how to simultaneously filter by keyword and location (the twitter api doesn’t allow you to use both parameters at once). The good news is that by not limiting by location, I’m not missing the offenders who don’t have locations associated with their accounts. I’m also limiting the search to non-retweets. I only want the bot to identify OC (Original Content (or, for the more puerile among us, Original “Cuntent”)). You can follow @Gramma_Bot to see the offenders’ messages and Gramma’s reponses!

UPDATE: On the same day Gramma Bot launched (March 25, 2017), the application’s writing privileges were revoked. 

Before Gramma got shut down, a few funny things happened:

  1. The bot flagged itself as an offender so kept calling itself out for using the word cunt. This was a silly thing for me to forget to account for in the code, but it does play into the narrative of “LOOK AT WHAT GRAMMA BOT HAS BECOME”

2. An offender was amused/baited by the bot, responding with, “I work on those numbers, you cunt”

3. A crazy lady (whose account has just been suspended) who has devoted her twitter career to harassing the doctors and nurses who supposedly botched her breast augmentation surgery assumed that it was the nurses who created Gramma Bot to “bully” her.

4. Gramma Bot retweeted quite a few butt photos from “titty.me” so I manually got rid of those.

I’m now deciding whether to appeal twitter’s restriction and then neuter my bot so it follows twitter’s automation rules, create Gramma_Bot2 and inevitably get that account suspended, or simply let things be.

RIP Gramma Bot.

Hanging Desk: Week 1

Piecing It Together

For my midterm assignment, I’ve decided to build a hanging desk I saw in a CB2 catalog. Here are images of what their desk looks like:

I really like their design so for the moment I’m going to try and replicate it. Here are my own sketches:

At the bottom of my sketch page I’ve included a “challenge section”–I’m thinking about including gears on the sides of the structure that turn as the desk drawer is opened.

I also made a cardboard prototype:

Forever Giphy Chat Bot

Twitter Bot Workshop

Assignment: Make a bot that responds to @-replies or direct messages. Use Digital Ocean to run this bot “forever” on a remote server.

My chat bot concept was to use the giphy api and tweet out a random gif using the content of the tweet as a tag. Here’s what I mean:

random_user: @GiphyChatBot chill
GiphyChatBot: @random_user [random gif that is tagged “chill”]

I think this qualifies as a chatbot because it simulates/automates a human interaction that might go like this:

Person 1: Hey bro, send me a Little Shop of Horrors gif
Person 2: Okay bro, here is your Little Shop of Horrors gif

The thing that I don’t love about the bot is that it only produces single-exchange interactions. It doesn’t create an extended conversation between user and bot. At any rate, here is an example tweet: