Self As Dataset: Animating the Body with Machine Learning
Self As Dataset: Animating the Body with Machine Learning
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Self As Dataset: Animating the Body with Machine Learning is for artists interested in AI and animation who want more authorship and control over their data than browser-based tools allow, without needing high-performance GPU systems or advanced technical background.
Over the span of the workshop, participants will:
- Unpack the gap between ethical intention and practical access in AI art, why meaningful engagement with machine learning can feel either oversimplified or out of reach, and how participant-authored datasets bridge that.
- Build simple datasets grounded in their own movement and original visual material, drawing on approaches from computer engineering and dance-theatre.
- Translate movement into animated outputs using accessible machine learning workflows adaptable to lower-spec devices.
- Reflect on authorship, consent, and embodiment in contemporary AI systems through live demonstration, collaborative experimentation, and discussion.
Participants leave with a short AI-animated clip and a clear, repeatable process. No prior experience is required. Participants may engage hands-on or follow along through guided demonstration.
Through these initiatives, we aim to give participants further opportunities to build their new media arts practice and engage with Toronto's creative communities.
ABOUT THE FACILITATOR
Punit is an Indo-Canadian dance-theatre artist based in Vancouver, working across contemporary and street dance, performance, and emerging media. His practice explores themes of identity and contemporary society, often through dystopian and speculative lenses. Alongside his performance work, Punit brings a background in computer science and a growing focus on AI-driven creative processes. He is interested in how embodied experience intersects with computational systems, particularly in rethinking authorship, data ownership, and representation within machine learning. Punit has presented original works with organizations including NewWorks, Dance West Network, and the Dance Centre, and has performed across Canada. His projects have been supported by the Canada Council for the Arts and the Chrystal Dance Prize through Dance Victoria. His current work is a dance film exploring the translation of human movement into digital and AI-generated forms, reframing AI as a collaborator that can expand creative access across technical and social barriers.
ADDITIONAL INFORMATION
MEMBER PRICING
InterAccess Studio Members receive a 40% discount on all workshops. To
activate Studio Member pricing, click "Use ticket access code" at
checkout and enter your Member discount code.
EQUITY ACCESS PRICING
To reduce financial barriers, a pay-what-you-can (PWYC) discount is available for any community members that self-identify as part of an equity-seeking group, which includes (but is not limited to) disabled, Black, Indigenous, students, and newcomers. This discount is also available to those earning less than a living wage. To request an Equity Access code, please email education@interaccess.org.
ACCESSIBILITY INFORMATION
We are located on the second floor of the building, which is accessible by two flights of stairs or an elevator. The front entrance has an automatic push door and is accessible by ramp or a short flight of stairs. Inside, all InterAccess facilities are on the same level, including a single-user accessible washroom.
CANCELLATION AND RESCHEDULING POLICY
Please email
education@interaccess.org to request a refund. We are unable to
guarantee attendee cancellations or refunds less than 1 week prior to a
workshop or event. InterAccess reserves the right to cancel or
reschedule this workshop if necessary.
Location
InterAccess, 32 Lisgar Street, Toronto, ON, M6J 0C7