13-17th December 2016 hosted jointly by Interface Cultures and Fashion and Technology departments at the Art University Linz, Austria
This workshop is only open to university students.
Fashionable Technology I
Textiles are one of the oldest forms of technology, we’ve been wrapping our bodies in material for 100,000 years. As our environment changes, we develop new mechanisms to functionally and fashionably interface between ourselves and our surroundings. The technologies we develop in turn influence our surroundings, prompting us to continuously adapt.
This course aims to situate recent developments in “smart textiles” within the historical framework of clothing technology and fashion. We want to give students a historical background and a good understanding of the technologies involved, as well as the skills to prototype and build their own designs.
Through a series of short lectures and introductory activities, students will be introduced to smart textiles, wearable technology, soft circuits and electronic textiles. We encourage a learning-by-doing approach to making technology. Lectures will be brief, and the majority of course time will be spent in hands-on introductory exercises and prototyping and producing a final project.
For the final project we will provide students with a conceptual framework, in which they should conceive, design and realise a working prototype. The framework will be announced at the start of the course.
– 1 hour lecture that situates recent developments in “smart textiles” within the historical framework of clothing technology and fashion and introduces “Wearable Technology”
– Read text >> http://dataprevention.net/
– Intro activity
– Project development
– Project development
Further Reading and References
The Data Prevention Manifesto
…by the Plumbing Birds
Wearable Tech History
Wearable Computing Blogs
Open Sourcing Wearables: the Impact of Open Technologies and User Engagement in the Design of Body-Borne Interactive Products.
Data scientist Cathy O’Neil on the cold destructiveness of big data
Big data promises fairness. With enough information about individuals and populations, we can design algorithms that will identify the best possible answer to a given question, free of human bias. Algorithms, after all, are not racist, sexist, or elitist. Or are they?
Ich habe nur gezeigt, dass es die Bombe gibt
UK governments Data Prevention Act
Sense Your City
“In just a few decades, we’ve turned into a data-producing species. According to some estimates, there is now more data produced every two days than in all of history prior to 2003. The promise is this: If we could just unlock and understand this data, our cities would be more efficient, our economy more vibrant, our lives better.
But data is not an easy thing to grab onto. It can be misinterpreted, skewed or plain wrong. It can contain noise that obscures the signal.”
“To empower citizens to sense and make sense of their environment, we created a DIY sensor network to measure pollution, dust, light, sound, temperature, and humidity. We created an interactive map, opened the data, and asked you to use it to narrate a story about your city.”
Big Picture Group Google Brain
“We explore how information visualization can make complex data accessible, useful, and even fun. Our focus is on ways to illuminate the data and algorithms used in machine intelligence.”
Ebru Kurbak and Mahir M. Yavuz – News Knitter
“News Knitter converts information gathered from the daily political news into clothing. Live news feed from the Internet that is broadcasted within 24 hours or a particular period is analyzed, filtered and converted into a unique visual pattern for a knitted sweater.”
Dense captioning of Boston Dynamics Atlas Robot from Gene Kogan
“This video demonstrates both the impressive capabilities of neural captioning systems, as well as the humorous (and maybe unsettling) limitations of such systems when their training data lack the vocabulary to fully describe the scene.”
Memo Akten’s Keeper of our collective consciousness
“I wrote a poem. It’s a collaboration with Google. Not people working at Google, but actual Google, the search engine.”
Jill Magid: Trust
“Treating the cameras as elements in a personal relationship with the municipal authorities, and letter-writing as a diaristic confessional abetting her own surveillance, the result is a captivating, mysterious exercise in oversharing, a performative self-portrait facilitated by using the technology of our oft-vilified constabulary panopticon.”
Addie Wagenknecht, “Anonymity,”
Lauren McCarthy’s Follower
“Follower. Don’t go unnoticed. Follower is a service that grants you a real life Follower for a day. A no-hassle unseen companion. Someone that watches, someone that sees you, someone who cares.”
Kyle McDonnald’s Exhausting a Crowd
Kyle McDonnald’s and Lauren McCarthy’s People Keeper (pplkpr)
“An app that tracks, analyzes, and auto-manages your relationships. It uses GPS and subtle changes in heart rhythm to keep track of when you’re coming and going and determine your emotional state. The data is connected to people you interact with to determine who should be auto-scheduled into or out of your life.”