SELF // ISOLATION

SELF // ISOLATION

Blurred indiscernible grey and brown smudges. Towards the top of the image is a dark black and purple smudge, with light green accents throughout.

SELF // ISOLATION
Chelsea Watson

Self // Isolation is a collection of digital pieces generated from photographs taken by the artist in her home. One portrait was taken for every month she spent alone in isolation during the COVID-19 pandemic. Using code to manipulate the photographs through a process called generative art, the images morph from everyday household objects and scenes of day-to-day life, into indiscernible blurs. Drawing from experience with anxiety and depression, the artist attempts to capture the chaos, fog and distortion, which is often experienced in times of trauma, and acutely felt by most during the pandemic. The project is a comment on the unreliability of memory and the brain’s misperception of reality, and ultimately a reflection on the artist’s progressive mental decline during the lockdown.

Chelsea Watson is an artist from Calgary, Canada currently residing in Toronto. Her unique process, known as generative or computational art, uses creative coding to make computer programs that create art. Chelsea’s work is purposefully random with an appreciation for imperfection. She draws inspiration from tactile art forms, such as paintings, ceramics and textiles to create layered and textured pieces with code as her medium.

MASTER CLASS:
SELF ISOLATION – LEARNING TO MAKE COMPUTATIONAL ART
DURING A GLOBAL PANDEMIC
In spring 2020, Chelsea Watson taught herself how to make art from code by creating 100 computational pieces in 100 days. What started as an exploration of a new artistic medium, this structured approach to creating art became a way for her to connect and cope while self-isolating for the better part of a year. Join Chelsea as she takes you through her challenge, and walks you through a hands-on workshop to explore generative art and introduce the basics of creating art using code.

Recording available online Oct 28 – Nov 7

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