I’ve been thinking more about what I am going to be titling this body of work as well as an upcoming workshop I will be hosting at the MAL next week. I’ve titled the work Knitting with machines: Imagining softer futures through ‘string figures.’ 

The term “string figures” is one of the SF practices (science fiction, speculative fabulation, speculative feminism, etc) introduced by feminist STS scholar Donna Haraway in her book Staying with the Trouble. These practices enable us to fabricate futures that connect us to our shared communities in the face of a challenging present. Like knitting, string figures are loops, but they are also ways of weaving stories together. In my work, I am approaching knitting as both metaphor and material for exploring futures that promote connection, community, and embodied knowledge(s). 

This past week, I’ve been reading Pat Treusch’s book Robotic Knitting: Re-Crafting Human-Robot Collaboration Through Careful Coboting, in which she details her attempts to teach a robot how to knit. I have been soaking up some of the language she uses to describe her approach to robotic knitting. She describes the process of robotic knitting as a ”methodological tool and analytical frame for contemporary technofeminism” (Treusch 10). Technofeminism, according to Judy Wajcman, enables new forms of inquiry that push us towards a more just and equitable world. 

Robotic knitting, Treusch says, is an “interventionist practice” and “generative, playful engagement” (10) with an open situation, resulting in diverse forms of knowledge. I have been thinking about my own experimentation with knitting and yarn as a playful approach to untangling meaning and materiality. I’ve written before on this blog about how my approach to art-making is sometimes scattered or emergent, but also intensely relational. 

“Playing with yarn can be considered a practice of producing new stories.”

Pat Treusch

Like Donna Haraway untangling a ball of yarn during an interview, I think that in my work I attempt to create meaning through a process of unwinding, untangling, pulling and stretching, knitting and unraveling, with often surprising outcomes. Yarn is both metaphor and material (referencing a line from Sadie Plant’s book Zeros + Ones).

Donna Haraway describes this kind of knowledge-production as “situated knowledge”: the idea that specific assemblages of bodies, time, space, material, and power relations produce different, site-specific forms of knowledge. We get only a partial view of that system, but the partial/local view tells us more than a universal view.

“It matters what matters we use to think other matters with; it matters what stories we tell to tell other stories with; it matters what knots knot knots, what thoughts think thoughts, what ties tie ties. It matters what stories make worlds, what worlds make stories.” 

Donna Haraway, Staying with the Trouble

I will continue pulling these intellectual threads (ha!) through my work, especially as I look towards designing a workshop that invites new modes of inquiry and research.

On Friday, I had the opportunity to visit the Unstable Design Lab at ATLAS, led by Laura Devendorf. It was really inspiring to see how the group is exploring cutting-edge weaving techniques, including building new software tools for sketching 3D parametric surfaces and experimenting with thermochromic materials that change color when heat is applied. When I talked about my project, Laura mentioned that the old patents for domestic knitting machines are quite revealing as artifacts of the past: Apparently, they use gendered language that reflects how the patent writer anticipated such machines might be used by women in the home. I am really interested in digging more into those patents this week.

Over the past few days, I’ve been pushing myself to experiment more with 3D knitted structures, using a technique called hand-manipulated stitches on the knitting machine. I knit a few different versions of a zig zag stitch, as shown in the previous post. Next, I experimented with combining weaving with the zig zag stitch, weaving a spool of wire into the knit. 

I also learned how to do a tuck stitch, which produces a thicker, more durable fabric to work with overall. I love how the two yarns look next to each other in the tuck stitch.

I also learned how to use the hold setting of the knitting machine to knit short rows. I learned how to knit a rounded ladder, and then knit a few different pouches using this technique. As I have been experimenting with different kinds of sensors, I am thinking about how to weave, hide, or store various electronic components within the garment so that they are hidden from view. This technique was really helpful for thinking about how to create small pockets.

Next, I want to experiment with a few more sensors and feedback, including the touch sensor and haptic motors.

References (in the order referenced)

Donna Haraway, Staying with the Trouble: Making Kin in the Chthulucene

Pat Treusch, Robotic Knitting: Re-Crafting Human-Robot Collaboration Through Careful Coboting

Judy Wajcman, TechnoFeminism

Sadie Plant, Zeros + Ones

Donna Haraway, “Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective”

Over the past few days at MAL I’ve been setting up my workspace and getting the knitting machine up and running, as well as doing an inventory of all the sensors I have available. 

I’ve been reading/re-reading a few of the books that are informing the development of my work during this residency. Daniela K Rosner’s book Critical Fabulations: Reworking the Methods and Margins of Design has informed my practice with soft circuitry and knitting over the past few years. The book aims to examine the ways in which craftwork, often performed by feminized labor, has been central to the history of engineering. (I’ve written about this before in my blog post about weaving core memory). Engineering is craftwork, craftwork is engineering. 

The title of Rosner’s book is inspired by the term “critical fabulations,” coined by feminist scholar Saidiya Hartman: “By playing with and rearranging the basic elements of the story […] I have attempted to […] imagine what might have happened or might have been said or might have been done.” This has resonances with Donna Haraway’s concept of “re-figuring,” which she explores in her book Staying With the Trouble. Rosner defines critical fabulations this way:

Critical fabulations are ways of storytelling that rework how things that we design come into being and what they do in the world. They deconstruct design methods to open different understandings of the past that reconfigure the present, creating new opportunities for a just future […] By making stories and catalyzing new embodied ways of knowing, fabulations draw attention to the contested nature of knowledge productions.

Daniela K Rosner

The goal of the book isn’t just to draw attention to these forgotten, commodified forms of labor. Rosner states that her goal is to use these stories and histories “to envision our relationships to design anew” by exploring their “ongoing knots, troubles, and possibilities” (7). By revisiting these stories and interrogating/disrupting the most commonly accepted histories of computing and engineering, she aims to open up new possibilities for imagining different design futures.

I’ve been thinking a lot about these ideas as I’ve been experimenting with electronics and textiles in my own work. I’ve been struck recently by how much of today’s conversations about tech are driven by a hype cycle that relies on a total ignorance to  – or intentional erasure of – the past. This is why I was excited specifically to explore ideas around knitting, stringing, ‘fabulating’ alternative futures at the MAL. Walking around the lab, I’m surrounded by dozens of vintage computers, operating systems, games, and hundreds of software manuals and books that aimed to tell the story of what our technological future would look like. 

This week, I have been exploring different ways in which knits can serve as interfaces. I want to make my knitting interactive through different techniques of weaving/knitting/sewing some of the hardware into my knits. I’ve also been trying out new techniques for knitting 3D structures and shapes on the knitting machine, as it will make the work overall more tactile and dimensional.

On Wednesday, I started by wiring up a flex sensor with my Arduino. Flex sensors are typically used in garments like gloves for detecting a finger bending, for instance. As the sensor is flexed, the resistance across the sensor increases, which allows for variable values. I knit a simple swatch with some folded pleats. I slid the flex sensor into the pleat, and ran a simple test for adjusting the brightness of an LED.

Code below (pulled from this tutorial) that demonstrates how I mapped resistance values being received from the sensor (0-1023) to the LED’s Pulse Width Modulation (0-255).

void loop(){

  value = analogRead(flexPin);         //Read and save analog value from potentiometer

 Serial.println(value);               //Print value

 value = map(value, 700, 900, 0, 255);//Map value 0-1023 to 0-255 (PWM)

 analogWrite(ledPin, value);          //Send PWM value to led

 delay(100);                          //Small delay


I ran this experiment with a simple Arduino, but one of my goals this week is to set up some swatches with the FLORA. FLORA is an Arduino-compatible microcontroller that was designed specifically for designing wearables and soft circuitry. Because it’s round and has eyelets, the microcontroller can be easily sewn with conductive thread into a garment.

On Thursday, I knitted a 3D zig zag pattern inspired by this blog post on ruched or manual pull-up effects in knits. I was so excited with how this experiment turned out, and I want to explore more of these 3D surfaces in my work, especially because I think their tactility lends themselves to interactivity: You just want to touch them.

That night I had a minor heart attack when the knitting machine carriage inexplicably jammed. I spent two hours troubleshooting (and accidentally stabbing myself with needles) before calling it a night. The next day I did a more thorough cleaning of the carriage and discovered a tiny metal gear that had gotten stuck. I unstuck it and all was well.

Today was my first day in the Media Archaeology Lab, where I will be spending the month as an artist/researcher in residence. As part of this experience, I’ll try to publish semi-daily lab notes to document my experiments and reflections on this blog. Forgive any typos 🙏

Today, I started by flipping through a few books about software. Some of the books I remembered and documented: Cybernetics, Art and Ideas (Jasia Reichartdt), Computer Power and Human Reason: From Judgement to Calculation (Joseph Weizenbaum), Apple Machine Language + Apple ad insert (Don & Kurt Inman), Artificial Intelligence: Making machines “think” (Neill Graham), Bob Neill’s Book of Typewriter Art, Future Stuff (Malcolm Abrams and Harriet Bernstein).

I was particularly struck by seeing Weizenbaum’s 1976 book Computer Power and Human Reason: From Judgement to Calculation, a book I read years ago that aims to push back on technodeterminist narratives, side-by-side with a book from 1989 titled Future Stuff: More than 250 useful, time-saving, delicious, fun, stimulating, and energy-saving products that will be available by the year 2000. 

Future Stuff attempts to predict – with a shocking amount of confidence! – which tech products will be available in 11 years, alongside stats like Odds (e.g. 100% confident), ETA (e.g. 1990), and Price (e.g. $18,000). This includes products that actually are in the market now, like on-demand film streaming, a desk treadmill, and interactive gaming, but also wacky products like the walking TV and the self-improvement chamber. Reading through these listings, I’m struck by how confident the tone of the book is: Of course these products will be on the market. There is a pervasive feeling that these technologies are not only things that people really need, but their development is ultimately inevitable. The future is already planned.

Conversely, Joseph Weizenbaum’s pivotal book Computer Power says that nothing about the future is inevitable. In the book, he pushes back on the idea of technodeterminism:

“The myth of technological and political and social inevitability is a powerful tranquilizer of the conscience. Its service is to remove responsibility from the shoulders of everyone who truly believes in it. But, in fact, there are actors!” 

Joseph Weizenbaum

Writing during the Vietnam War, Weizenbaum was keenly aware of how engineers and technologists had contributed to the development of war machines. By treating technological development as inevitable, he argues, we may be setting up the conditions under which oppression, violence, and other harms can occur. I really enjoyed this blog post by Librarian Shipwreck that explores some of the ways Weizenbaum’s words continue to prove relevant in the current time, as we navigate conversations about AI products like ChatGPT, for instance, without interrogating their limits, their impact on society, or the ways they could reify existing power relations.

That blog post introduced me to several other essays by Weizenbaum on ethics in computing. In a 1983 piece in the New York Review of Books, “The Computer in Your Future”, he writes:

“The computer has long been a solution looking for problems—the ultimate technological fix which insulates us from having to look at problems.”

Joseph Weizenbaum

By removing any discussion of power and incentives from narratives around technological innovation, we submit ourselves to someone else’s fantasy of what the future will look like.

This month, I will be thinking a lot about knitting as a feminist technoscience, and what it can teach us about imagining or re-figuring (to use Donna Haraway’s language) different technological futures through string figures. How can we take these visions of the future from the past, and re-figure them into new, material forms? How can we imagine futures that are relational, connective, and that center care? Knitting is both material and metaphor in my project.

Tomorrow I’ll be setting up my knitting machine and all my electronic components in the lab, so I’ll have more time to do some physical experiments with knits and sensors.


Computer Power and Human Reason: From Judgement to Calculation, Joseph Weizenbaum

Computers enable fantasies – On the continued relevance of Weizenbaum’s warnings, Librarian Shipwreck

The Computer in Your Future, Joseph Weizenbaum, The New York Review of Books

Staying with the Trouble: Making Kin in the Chthulucene, Donna Haraway

Logo design by Katrina Ricks Peterson

algogossip is an exploratory project I’m currently developing, which was recently tested out at the 2022 Internet Yami-Ichi.

Last month I called up my friend, a full-time content creator. I’ve been reading a lot about the tactics people use to increase the chances of their posts being seen on social media, so I asked: Where did she go to get advice and tips for how she posts? 

When you consider how many people rely on algorithmic visibility on social media for financial stability, questions around how social media algorithms work become absolutely critical. According to a recent SignalFire report, roughly 2 million people work as full-time, professional content creators on platforms like YouTube, Instagram, and Twitch. These platforms do not provide detailed information about how their algorithms work, at the risk of being gamed. But at the same time, when changes to the algorithm are rolled out without warning, content creators are left scrambling trying to make sense of the changes. 


Over the past few years, I’ve been thinking about the stories people tell each other about their everyday interactions with social media algorithms. As part of my grad school thesis research in 2016, I asked people to share their stories about Facebook’s ad targeting: What kinds of strange experiences did they have with targeted ads? During my time as a Ford-Mozilla fellow in 2017, I collaborated with Coding Rights to explore this question further: What experiences were women having on the platform? What constitutes algorithmic harm? We talked to women who had had unsettling or confusing experiences with Facebook’s targeted ads. Most recently at Mozilla, I’m leading qualitative research that aims to get at the heart of people’s experiences with YouTube’s user control mechanisms: Do they feel like they have meaningful control over the system? How do they change their behavior in an attempt to exert control?

My research has been informed by scholars writing about how people engage with social media algorithms. Taina Bucher has written extensively about the “algorithmic imaginary” (Bucher 2017), the animating force of social media algorithms, ways of thinking about what algorithms are, what they should be, and how they function. She argues that the stories people offer up about algorithms are important because they have real social impact. Michael Ann DeVito and others argue that the folk theories people hold about social media algorithms serve as frames through which we can understand their reactions to change (DeVito et al. 2017). They say that by looking seriously at the complaints people make about algorithms, we can better understand the nature of “expectation violations.”

A paper about how users exercise control over social media algorithms (Burrell et al. 2019), says that the complaints people make about social media algorithms are important feedback signals. Citing Sara Ahmed’s writing on complaint as a feminist tactic, they write that “the act of complaint itself can be a way for people to record their grievances and build solidarity in the face of limited recognition by those with organizational power.” (Ahmed has since published a book titled Complaint! that looks at how complaints are made and what they can do, specifically through a Black feminist and feminist of color lens.)

My thinking on this project has been most shaped and inspired by Sophie Bishop’s excellent scholarship on the concept of “algorithmic gossip,” a term she defines as “communally and socially informed theories and strategies” about social media algorithms that people share with one another in order to boost financial stability and visibility on social media platforms (Bishop 2019). She says that “gossip is productive” and that it is an “important and under-studied form of knowledge production.”

Gossip, especially in its association with women, has historically been looked down upon and treated as trivial, intimate, and dangerous. It’s also a tactic that’s wielded in situations where a power asymmetry exists, and most often it’s wielded by marginalized groups. I think about the whisper networks at universities or at companies that have warned newcomers about problematic individuals, or have allowed people to quickly share important knowledge. Most importantly, gossip serves to subvert power: In the absence of good, accurate information about how a system works, people rely on one another to make sense collectively. 

The project

Back to the question I asked my friend: Where did she go to get advice and tips for how she posts? She told me that she was part of a group text with other friends who were content creators, where they shared tips and offered support. Many of them subscribe to industry newsletters or work with agencies who give them advice about how and what to post. Others seek out internet forums for answers to their questions. 

I started looking into some internet forums where these conversations take place. There are a number of subreddits dedicated to answering people’s questions about how the TikTok algorithm works, advice for boosting visibility on Instagram’s algorithm, avoiding/appealing shadowbans, and similar topics. The posts in these forums range from the didactic (“Post at least 6 times a day. Upload history like 2 of those. HASHTAGS VERY important.”) to the supportive (“Why don’t you try some challenges ? Like challenge people to do ex: 5 pushups everyday and have your own hashtag.”). There is a real sense of camaraderie, with posts expressing frustration  (“I have been banned for more than a month now and they are not reviewing my appeal”) and affirmation (“Yeah this has been happening to my videos as well.” I decided to use these posts as a starting point from which I could explore further. 

Coding the project

After setting up Reddit API credentials, I scraped posts and their comments from these subreddits using Reddit’s PRAW, filtered by specific flairs (e.g. “Algorithm Question / Shadowbanned”). I imported a Python module written by Prakhar Rathi, and then wrote a script that would scrape the posts and comments and save the dataset as a CSV. I combined the data and converted it into a JSON file.

I thought about what I wanted to do with this dataset of ‘algorithmic gossip’, especially in an art gallery setting. I considered curating a selection of the data in a book or zine. I also considered building an ML model to generate new advice from this dataset.

I thought about some of the previous exploration of voice technology I had done with my collective tendernet, and considered the ways we think about gossip as spoken: it has an aural quality. I got really excited about the creative potential for a voice interaction – could you call a phone number and get a voice message? Pick up an object, put it to your ear, and a message plays? With one tendernet collaborator Zoe Bachman, we brainstormed some ideas and agreed on an aesthetic: y2k tech girlie. Another collaborator Katrina Peterson took the aesthetic concept and iterated some cute logo designs.

Ahead of the 2022 Internet Yami-Ichi, I decided to build a web-based piece (see the prototype here) that employs text-to-speech. I built the website using JavaScript, making use of the p5.js and p5.speech.js libraries. Each time you click the page, a new piece of ‘algorithmic gossip’ appears and is read out loud in an unnatural-sounding robotic voice. I tested out different qualities of the voice, including testing out a “whisper” (it sounded terrifying).

Testing it out

Testing out the piece at the Internet Yami-Ichi was a lot of fun. The energy of the event was very much a cross between an art book fair, a bazaar, and an art gallery. I talked to lots of people who came through about the concept behind the project and got some great ideas. I was also inspired by hearing more about Angie Waller’s work with Unknown Unknowns; she is also working with comments and pictures scraped from the internet.

I want to continue refining and exploring this dataset through different creative explorations. 


Sara Ahmed. 2021. Complaint! Duke University Press, Durham.

Sara Ahmed. 2018. Refusal, Resignation and Complaint. feministkilljoys. Retrieved May 7, 2022 from https://feministkilljoys.com/2018/06/28/refusal-resignation-and-complaint/

Sophie Bishop. 2019. Managing visibility on YouTube through algorithmic gossip. New Media & Society 21, 11–12 (November 2019), 2589–2606. DOI:https://doi.org/10.1177/1461444819854731

Sophie Bishop. 2020. Algorithmic Experts: Selling Algorithmic Lore on YouTube. Social Media + Society 6, 1 (January 2020), 205630511989732. DOI:https://doi.org/10.1177/2056305119897323

Taina Bucher. 2017. The algorithmic imaginary: exploring the ordinary affects of Facebook algorithms. Information, Communication & Society 20, 1 (January 2017), 30–44. DOI:https://doi.org/10.1080/1369118X.2016.1154086

Michael A. DeVito, Darren Gergle, and Jeremy Birnholtz. 2017. “Algorithms ruin everything”: #RIPTwitter, Folk Theories, and Resistance to Algorithmic Change in Social Media. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI ’17), Association for Computing Machinery, New York, NY, USA, 3163–3174. DOI:https://doi.org/10.1145/3025453.3025659

Michael Ann DeVito. 2021. Adaptive Folk Theorization as a Path to Algorithmic Literacy on Changing Platforms. Proc. ACM Hum.-Comput. Interact. 5, CSCW2 (October 2021), 1–38. DOI:https://doi.org/10.1145/3476080

A few months ago I bought a beautiful hand-woven object off the internet. The object measures 5.5 inches by 5.5 inches and consists dozens of thin threads tightly woven through small beads, strewn across a square resin frame.

When it first arrived, I enjoyed challenging friends by showing them the object without any context and asking them to identify what it is. One group of friends thought that it was some kind of weaving device. “Do you weave with it?” one friend asked. “Small loom for patching clothes,” guessed another. At first another friend thought it was a loom, but upon closer examination he noticed that the tiny threads woven throughout it are, in fact, thin wire filaments. Does it carry an electric charge, he asked?

Dimensions: 14 cm x 14 cm. Memory capacity: 4096 bits. Ferrite field: 64×64.

He was right. The object is what is known as a “ferromagnetic core memory,” an antiquated form of computer memory. As I started researching the origin of the object, I learned more about how the histories of computation, memory, textile production, and labor are intertwined.

Core memory was first developed in the 1950s and was the most common type of random-access computer memory until 1975. Random-access memory (RAM) is a type of computer memory that can be accessed at any time, regardless of when it was saved. Core memory works as follows: Wires are tightly laced through small ferrite rings (known as cores). Ferrite is used because it becomes magnetized when exposed to magnetic fields. Electric currents are sent through the wire, which creates magnetic fields. The core can be polarized negatively or positively based on magnetic fields operating in opposite directions (i.e. switching the polarity). Those opposing polarities correspond to 1 or 0, the components that make up bits and bytes.

Weaving core memory

In the United States, the lightweight quality of hand-woven core rope memory, “a technique of physically weaving software into high-density storage,” powered the early Apollo Guidance Computer that put the Apollo on the moon. The history of core rope memory has been well-documented: highly skilled weavers and craft workers, most of whom were women, worked in a Raytheon factory in Waltham, Massachusetts to weave the core rope memory. There was a gendered aspect to this labor: The core rope was referred to as LOL memory (“Little Old Lady” memory). Journalists, engineers, and even a manager at Raytheon allegedly described this work as requiring no thinking and no skill.

The software for flights was managed by a “rope mother” (who was usually male), although Margaret Hamilton, who is best remembered for overseeing the development of the Apollo software, was rope mother on the Luminary.

Unnamed woman described as a “space age needleworker” in a Raytheon press kit. Source: Science News
Source: Raytheon CN-4-20C / Smithsonian Institution WEB15435-2016.

In their paper “Making Core Memory: Design Inquiry into Gendered Legacies of Engineering and Craftwork,” Daniela Rosner and others explore how the high-status, male labor of building computers was powered by low-status craftwork largely carried out largely by women (specifically, women of color). According to Rosner, the work performed at Raytheon was described as “tender loving care” by the man who oversaw the Apollo Guidance Computer’s hardware.

Lisa Nakamura interrogates these ideas in her paper “Indigenous Circuits: Navajo Women and the Racialization of Early Electronic Manufacture”, which looks at the indigenous women who built integrated circuits for the Apollo Guidance Computer. From 1965-1975, the Silicon Valley company Fairchild Semiconductor ran a circuit manufacturing plant in New Mexico on Navajo land where Navajo women were employed. Nakamura demonstrates how racialized notions of labor shaped how value was conferred on the engineering/craftmanship work those Navajo women carried out. According to Nakamura, the work the Navajo women did was described as “affective labor, or a ‘labor of love.’”

The critical contributions of these craftworkers – both the women weaving core memory in MA and the women building integrated circuits in NM – were systematically undervalued and largely erased from computing history until recently. Gendered and racialized notions about what is considered “real” tech work persist today.

The Saratov-2 computer

The ferrite core memory plate I own is a relic of Soviet computing history. The Saratov-2 microcomputer from which my core memory plate is from appears to have been uncovered in the ruins of a fire. Russian urban explorer Ralph Mirebs describes his discovery in a 2020 blog post “Cemetery of Soviet Computers.” Apparently no photos remained of this “legendary machine,” the Saratov-2, until the author came across the ruins. (He declined to share the location). The Saratov-2 is apparently rare enough that no examples were believed to have survived until this discovery.

Source: Ralph Mirebs
Source: Ralph Mirebs

The Saratov-2 was a clone of the US minicomputer PDP-8/M. Cloning US computers was common practice at the time: In the 1970s, the USSR began getting its hands on PDP minicomputers with the intent of copying them. The PDP-8 was allegedly acquired by the USSR from a sunken US submarine, and then reverse engineered by the Central Research Institute of Measuring Equipment (ЦНИИИА) in the city of Saratov. At least that’s what the Etsy posting says – a blog post written by another computer hobbyist investigates this claim further and can’t confirm it.

What made the Saratov-2 unique was that it didn’t have a microprocessor. Instead, it was broken down into its individual components, which sat in drawers. The ferrite core memory cube, the microcomputer’s RAM, was located in one such drawer.

What about the Saratov-2 core memory plate I own? What handiwork and labor did it require? It’s difficult to say who hand wove the core memory that powered these early microcomputers, since information about them is scant.

Source: Ralph Mirebs

According to Ralph Mirebs (site in Russian), the decimal number on the core memory plate I own begins with KhSHM, which suggests the plate was manufactured at the Central Institute of Measuring Equipment in Saratov, Russia during the 1970s. The Central Institute of Measuring Equipment (TsNIIIA for short) was founded in 1958 and specialized in the manufacturing of electronic devices, including magnetic materials and integrated circuits. This is where the Saratov-2 minicomputer was developed.

I was able to track down the location of the Central Institute of Measuring Equipment. The cluster of TsNIIIA buildings are located at the intersection of Moskovskaya and Radishcheva streets in Saratov, Saratov Oblast, Russia.

Photo taken 1965. Source
Currently on Google Maps

The TsNIIIA closed in 1991, and a joint stock company TsNIIIA took its place. In 2017, the owners tried to sell the 32 buildings but failed. In 2021, it was announced the buildings would be turned into a “technocenter.” It’s unclear what the buildings are currently used for.

So, who were the artisans who worked in a TsNIIIA building to weave core memory for the Saratov-2 microcomputers? I’m really not sure. If anyone has more information, I’d love to learn more.


Nakamura, Lisa. “Indigenous Circuits: Navajo Women and the Racialization of Early Electronic Manufacture.” American Quarterly, vol. 66, no. 4, 2014, pp. 919–41. DOI.org (Crossref), https://doi.org/10.1353/aq.2014.0070.

Rankin, Joy Lisi. “Core memory weavers and Navajo women made the Apollo missions possible.” Science News. https://www.sciencenews.org/article/core-memory-weavers-navajo-apollo-raytheon-computer-nasa. Accessed 21 Apr. 2022.

Rosner, Daniela. Critical Fabulations: Reworking the Methods and Margins of Design. The MIT Press, 2018.

Rosner, Daniela K., et al. “Making Core Memory: Design Inquiry into Gendered Legacies of Engineering and Craftwork.” Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, ACM, 2018, pp. 1–13. DOI.org (Crossref), https://doi.org/10.1145/3173574.3174105.

Shorey, Samantha, and Daniela Rosner. “A Voice of Process: Re-Presencing the Gendered Labor of Apollo Innovation.” Communication  1, vol. 7, no. 2, Mar. 2019, https://doi.org/10.7275/yen8-qn18.

“Software Woven into Wire: Core Rope and the Apollo Guidance Computer.” http://www.righto.com/2019/07/software-woven-into-wire-core-rope-and.html. Accessed 14 Jan. 2022.

Currently, I’m in a class on Algorithmic Poetry, in which we’ll experiment with integrating machine learning algorithms into our writing and creative practice.

Last week, we were prompted to think about how we would describe our own creative practice, especially when it comes to our coding or writing. Over the past few years, I’ve been reflecting on my “style” of making, which has always been scattered and emergent but also intensely relational. I’m driven by my curiosity for a question or an idea and often the art objects or code I produce are a byproduct of the research process. I create through mapping and learning and studying, with various experimental outputs.

I recently read Natalie Loveless’ manifesto-book, A Manifesto for Research-Creation: How to Make Art at the End of the World, which I felt not only validates this practice-centered type of investigation, but also positions it as a fundamentally feminist mode of research that is focused on experimentation.

Of Donna Haraway’s book The Companion Species Manifesto, Loveless writes that it “implicitly argues that it is in allowing ourselves to be drawn by our loves, our intensive and extensive curiosities, attentive to what and whom we are driven to explore, and examining the complex web of relations that we inherit thereby, that we might inhabit research questions ethically” (27). In other words, the questions are never answered. They are always in the process of unfolding.

“A research-creational approach insists that it is to our deepest, doggiest, most curious loves that we are beholden, and that is is love – eros – that must drive our research questions as well as our methodological toolkits….A multiplicity of responsive practices structured by situated (emergent, erotic, driven) accountability” (28).

In addition, Loveless reminds us that we must cultivate the erotic as our guide in our knowledge-making practices, a reference to Audre Lorde’s essay “The Uses of the Erotic: The Erotic as Power”. When we are attuned and attentive to those things that bring us pleasure and joy, we are positioned to do our best research and work.

I’ve been reflecting on this “style” of curiosity-driven research and experimentation as I’ve revisited some of my past work in which I wrote code that generated text. A couple of examples of text generators I built:

I’m still not quite sure what the output of some of my experimentation over the next month will look like, but I have had a renewed interest in textile design – specifically, producing objects on my knitting machine. Using punch cards, I’d love to translate some of the text generation from this class into physical, knitted textiles. You can see more of my ideas & references in this are.na channel.

Brian Eno, Oblique Strategies, 1974
  1. What kinds of forms and practices emerge when we turn away from the new and attend to the persistent, unsettled, and non-digital?
  2. What tensions might these forms and practices create with our typical practices of attribution and impact?
  3. How does sidelining the technological new allow us to pay attention to things in a different manner?

These three questions are at the heart of a 2018 paper “From HCI to HCI-Amusement: Strategies for Engaging what New Technology Makes Old,” in which two HCI practitioners resist the formal logic and structure of design workshops and instead take inspiration from the Fluxus movement to develop a set of “HCI-amusements.”

In the 1960s and 1970s, Fluxus emerged as an interdisciplinary creative practice in which artists, composers, designers, and poets engaged in experimental art that emphasized the process (research, archive, iterative “critical making”) rather than a finished output. Fluxus was characterized as a shared posture and language towards making, rather than an art movement. It was also decidedly “anti-art” in that artists strove to eliminate boundaries between “art” and the “non-art” spaces by integrating an iterative creative practice into everyday life, using everyday objects. The result was a set of art objects that were radically accessible.

In a parallel effort towards “critical making,” UC Berkeley offers a class aimed at getting students to think about the role of discomfort in design (see the paper “Uncomfortable Interactions” for a theoretical overview). Similarly, the project “Disobedient Objects” is a cookbook of sorts for subverting the utility of various objects, and serves as a conceptual starting point for thinking about “making the familiar unfamiliar.”

I’m thinking about these three questions now:

  1. How do we attend to the non-digital in order to sensitize ourselves to new forms and processes?
  2. Given that human-centered and “persuasive” design are tools that have been co-opted by capitalism, what tactics can we use to subvert HCI? How do we inject friction, noise, slowness, and discomfort into design interactions?
  3. How do we design interfaces that are uncomfortable and subversive?
  4. What new design patterns might emerge?

Yesterday I had the opportunity to user test my thesis project as it exists in its current state at the Quick & Dirty show. Since I’ve been doing some disparate experiments, I decided to show two of the pieces in an attempt to get feedback on what works, what feels compelling, and how the projects might be better synthesized.

First, I showed a web application I built that uses IBM Watson’s Personality Insights API (i.e. psychometrics) to make assumptions about who you are as a person. The user logs into Facebook in the application and then a dashboard appears that shows them their predicted psychological makeup and purchasing habits. I tried to take a satirical/speculative approach, suggesting what psychometrics could look like in the future.

Second, I showed the work I had done on generating 3D facial models from 2D images. The idea is that after a user logs into Facebook, the application will automatically produce a 3D model of their face just from their Facebook photos. Earlier in the day, I had 3D printed a face, so for the show I projected the isomap facial image on top of the 3D model to lend the 3D experiment more tactility.

People responded really well to the visual aspect of the project and expressed a desire to see more of a connection between this visual and the psychometric web app.

Overall the feedback was so useful. I felt as if the common theme was a desire for a stronger framing of the project. How do I want the audience to feel as an end result? What kind of approach or tone should I be taking?

My Facebook metadata as landscape.

This semester, I’ve focused my attention on creative ways of interpreting and visualizing my personal Facebook data.

I’m interested in exploring the concept of “digital dualism” – the habit of viewing the online and offline as largely distinct (source). We are actively constructing our identities whether behind a screen or in person. As Nathan Jurgenson writes, “Any zero-sum “on” and “offline” digital dualism betrays the reality of devices and bodies working together, always intersecting and overlapping, to construct, maintain, and destroy intimacy, pleasure, and other social bonds.”

The exact location where I made a Facebook update.

With this project, I wanted to try re-inserting the digital world into the physical world. I decided to locate specific actions I took on Facebook within a physical geography and landscape.

It’s very easy to download your Facebook metadata from the website – all you have to do is follow these directions. In my data archive, I found information about every major administrative change I’ve made to my Facebook account since I created the account in 2006, including changes to my password, deactivating my account, changing my profile picture, etc. This information was interesting to me because from Facebook’s perspective, these activities were in all likelihood the most important decisions I had ever made as a Facebook user.

I rearranged that data into a simple JSON file:

I decided to explore the IP Address metadata associated with each action. I wanted to know more about the physical location where I had made these decisions concerning my Facebook account, since I obviously didn’t remember where I was or what I was doing when I had made these changes.

I wrote a Python script (see code here) that performs several different actions for each item in the JSON file:

(1) Takes the IP address and finds the corresponding geolocation, including latitude & longitude & city/state;

(2) Feeds the latitude/longitude into Google Maps’ Street View and downloads 10 images that each rotate 5 degrees;

(3) Adds a caption to each image specifying the Facebook activity, the exact date/time, and the city/state; and

(4) Merges the 10 images into a gif.

The result was two dozen weird undulating gifs of Google Street View locations, which you can check out on the project website.

After doing all that work, however, I didn’t feel satisfied with the output. If the goal was to find a way to re-insert my digital data trail into a physical space, I felt that the goal hadn’t yet been realized in this form. I decided to take the project into a different, more spatially-minded direction.

I wrote another Python script that programmatically takes the IP address and searches for the latitude/longitude on Google Maps, clicks the 3D setting, records a short video of the three-dimensional landscape, and then exports the frames of that video into images.

Programmatically screen recording Google Maps’ 3D landscape.

Using the photogrammetry software Photoscan, I created a 3D mesh and texture from the video frames. Then, I made a quick design of the Facebook app on an iPhone with the specific Facebook activity associated with that location & IP address. Finally, I pulled the landscape .obj into Unity with the iPhone image and produced some strange, fantastical 3D landscapes:

Pulling the 3D mesh into Unity and inserting the Facebook metadata into the landscape.

darknet markets

In Australia, 224 people were detained, including members of Asian criminal groups and biker gangs, three tons of drugs and 45 million Australian (35 million American) dollars were confiscated. The expressions “deep web” and “darknet” are periodically utilized conversely. Nonetheless, this isn’t right. The darknet is essential for the more noteworthy deep web. The deep web incorporates all unindexed destinations that don’t spring up when you do an Internet search. Australians use Darket Market in 2021 asap market link. In the course of the joint operation of the United States and Australia, ANOM app was developed and distributed in a criminal environment. Thanks to this, the police received the opportunity to monitor closed chats,The darknet is important for the deep web, yet it alludes to sites that are explicitly utilized for detestable reasons. Dark net sites are intentionally stowed away from the surface net by extra methods. in which drug smuggling was discussed, money laundering and even planning murders.