cyber/fiber
cyber/fiber (2021-) is a project exploring the links between computation and knitting. The work involves a modded or hacked KH-930e knitting machine connected to a computer running open source software from All Yarns Are Beautiful (AYAB).
Both knitting and coding are fundamentally procedural: The process of creating a pattern based on a finite set of specifications has resonances with writing lines of code. Picking up a dropped stitch on the machine is something like debugging code. Writing a ‘for loop’ that cycles through an array of elements is like repeatedly running the knitting carriage over a bed of needles. Repetition and discipline results in something like a piece of handmade hardware.
Pat Treusch describes the process of knitting with machines as a ”methodological tool and analytical frame for contemporary technofeminism” (Treusch 10). Technofeminism enables new forms of inquiry that push us towards a more just world. Robotic knitting, Treusch says, is an “interventionist practice” and “generative, playful engagement” with an open situation, resulting in diverse forms of knowledge. “Playing with yarn can be considered a practice of producing new stories,” she writes.
In my work, I attempt to create meaning through a process of unwinding, untangling, pulling and stretching, knitting and unraveling, with surprising outcomes. Yarn is both metaphor and material.
Pat Treusch describes the process of knitting with machines as a ”methodological tool and analytical frame for contemporary technofeminism” (Treusch 10). Technofeminism enables new forms of inquiry that push us towards a more just world. Robotic knitting, Treusch says, is an “interventionist practice” and “generative, playful engagement” with an open situation, resulting in diverse forms of knowledge. “Playing with yarn can be considered a practice of producing new stories,” she writes.
In my work, I attempt to create meaning through a process of unwinding, untangling, pulling and stretching, knitting and unraveling, with surprising outcomes. Yarn is both metaphor and material.
Works
the air moves in to fill the spaces where my body's been (2024)
A sweater containing a detachable “patch,” knitted using hand manipulated stitches that produce a 3D ruching effect. The patch contains a proximity sensor and battery pack wired up to a FLORA, an Arduino-compatible microcontroller that was designed specifically for soft circuitry. The sweater is a prototype for a live performance exploring my proximity to other bodies, the spaces that exist between bodies.
Knit on a knitting machine with wool yarn.
the air moves in to fill the spaces where my body's been (2024)
A sweater containing a detachable “patch,” knitted using hand manipulated stitches that produce a 3D ruching effect. The patch contains a proximity sensor and battery pack wired up to a FLORA, an Arduino-compatible microcontroller that was designed specifically for soft circuitry. The sweater is a prototype for a live performance exploring my proximity to other bodies, the spaces that exist between bodies.
Knit on a knitting machine with wool yarn.
Seeing (Pears) Like a Computer (2024)
A sweater highlighting errors made by the image classification model Ultralytics YOLOv8, a state-of-the-art machine learning (ML) model that’s used for classifying images.
When I ran an image of a pear harvest from my pear tree through the ML model, it incorrectly identified one of the pairs as a “person” with a 0.26 confidence threshold.
The title is referencing the work of James C. Scott, Seeing Like a State, which emphasizes the unversalizing gaze of large systems that are designed to identify, sort, and categorize people and bodies for the purpose of exercising control and enforcing normative values. Why is this model seeking to identify people rather than fruits?
Knit on a knitting machine with wool yarn, naturally dyed with the bark from the pear tree in my backyard.
A sweater highlighting errors made by the image classification model Ultralytics YOLOv8, a state-of-the-art machine learning (ML) model that’s used for classifying images.
When I ran an image of a pear harvest from my pear tree through the ML model, it incorrectly identified one of the pairs as a “person” with a 0.26 confidence threshold.
The title is referencing the work of James C. Scott, Seeing Like a State, which emphasizes the unversalizing gaze of large systems that are designed to identify, sort, and categorize people and bodies for the purpose of exercising control and enforcing normative values. Why is this model seeking to identify people rather than fruits?
Knit on a knitting machine with wool yarn, naturally dyed with the bark from the pear tree in my backyard.
connect one computer to another computer and to the network (2022)
The internet dial-up modem sound, translated into a spectrogram visualization.
Knit on a knitting machine with cotton yarn.
The internet dial-up modem sound, translated into a spectrogram visualization.
Knit on a knitting machine with cotton yarn.
You can watch a 2024 artist talk I gave on the topic titled Knitting with machines: Imagining softer futures through ‘string figures.’