London AnitaB.org offers this unique workshop to Explore Machine Learning for Creative Data Interaction with Dr. Rebecca Fiebrink, Dr. Helen Pritchard and Dr. Joanne Armitage – avant-garde Human-Computer Interaction researchers and digital artists as part of the Coding in Gender Equality project with IKLECTIK.
In this workshop, we will engage in hands-on activities that challenge many prevalent narratives around machine learning— for instance, that it is impersonal, objective, inexpressive, and usable only by experts. We will explore different sources of data that reflect algorithmic visions of participants (for instance, data scraped from social media profiles), as well as participants’ own visions of the world, including queer and feminist possibilities (through data participants create on the spot with text, images, or sound).
We will experiment with novice-friendly tools for applying machine learning to this data, creating new works of art, designing new interactions with data, and constructing new perspectives on what machine learning is “good for” and how to use (and misuse) it.
- What is machine learning?
- Building interactions with machine learning and Wekinator (no coding required!)
- Obfuscating machine learning and anti-surveillance art
- Exploring personal identity in data – what does the Internet know about us?
- Exploring generative methods: AI that creates literature, knitting patterns, and other curiosities
- Group zine writing: machine learning science fictions
- ReflectionsParticipants should bring a laptop and power supply (if you have one; if you don’t, you can share with someone else). We will send an email to participants a few days before the workshop with some links to download free, cross-platform software.
Dr. Rebecca Fiebrink is a Senior Lecturer at Goldsmiths, University of London. Her research focuses on designing new ways for humans to interact with computers in creative practice, including the use of machine learning as a creative tool. Fiebrink is the developer of the Wekinator, open-source software for real-time interactive machine learning whose current version has been downloaded over 15,000 times. She is the creator of a MOOC titled “Machine Learning for Artists and Musicians,” which launched in 2016 on the Kadenze platform. She was previously an Assistant Professor at Princeton University, where she co-directed the Princeton Laptop Orchestra. She has worked with companies including Microsoft Research, Sun Microsystems Research Labs, Imagine Research, and Smule, where she helped to build the #1 iTunes app “I am T-Pain.” She holds a PhD in Computer Science from Princeton University.
Dr. Helen Pritchardis an artist and lecturer at Goldsmiths, University of London where she is the head of Digital Arts Computing. Central to Helen’s work is the consideration of co-research, participation, and queer environmental practice. Helen’s practice often emerges as workshops, collaborative events and computational art. Since 2013 Helen has been a member of the environmental collective Citizen Sense. As an artist Helen has shown work internationally including Tate Exchange (UK), transmediale (Germany), DAFest International festival of Digital Art, (Bulgaria), Spacex (UK), Microwave Festival (Hong Kong), ACA Florida, (USA)
Dr Joanne Armitage lectures in digital media at the University of Leeds and her practice-research encompasses areas including physical computing, science and technology studies and computer music. She is also notable for her practice in live coded music, as one half of the live coding duo ALGOBABEZ with Shelly Knotts, associated with the Algorave movement and as a member of the laptop collective OFFAL. She recently won the British Science Association’s Daphne Oram Award for Digital Innovation and is part of the Sound and Music’s Composer-Curator programme for 2018.
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