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Seeding Things No.1

Research output: Exhibits, objects and web-based outputs › Exhibition

Published

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Seeding Things No.1. Southern, Jen (Artist). 2021. Online: Mozfest.

Research output: Exhibits, objects and web-based outputs › Exhibition

Harvard

Southern, J, Seeding Things No.1, 2021, Exhibition, Mozfest, Online.

APA

Southern, J. (2021). Seeding Things No.1. Exhibition, Mozfest.

Vancouver

Southern J. Seeding Things No.1 Online: Mozfest. 2021.

Author

Southern, Jen (Artist). / Seeding Things No.1. [Exhibition].

Bibtex

@misc{5a49a8cfb0234182aba441509bc5df1b,
title = "Seeding Things No.1",
abstract = "A video made through incremental collaborations in a greenhouse and machine learning software. A landscape emerges from a glacier and grass begins to grow, only to recede back under the ice. Through freeze and thaw, it slowly gives way to a densely matted greenness that is grass-like, but also not. The work continues to grow in a generative conversation between plants, AI, and the artist. It draws a parallel between the actions of biological growth and machine learning, both seeded and tended by human input. The work is quietly influenced by ideas of environmental and human justice from fiction (Jemisin 2015-17, VanderMeer 2014), an entangled understanding of more-than-human relationships from social sciences (Tsing 2015, Haraway 1991 & 2016, Barad 2007), and of environmental and microbial care (Puig de la Bellacasa 2017). This complex ecology of {\textquoteleft}contaminated diversity{\textquoteright} (Tsing 2015) produces sublime encounters that threaten and enthral. ",
keywords = "Machine Learning, video art, Care",
author = "Jen Southern",
year = "2021",
month = mar,
day = "8",
language = "English",
publisher = "Mozfest",
edition = "2021",

}

RIS

TY - ADVS

T1 - Seeding Things No.1

A2 - Southern, Jen

PY - 2021/3/8

Y1 - 2021/3/8

N2 - A video made through incremental collaborations in a greenhouse and machine learning software. A landscape emerges from a glacier and grass begins to grow, only to recede back under the ice. Through freeze and thaw, it slowly gives way to a densely matted greenness that is grass-like, but also not. The work continues to grow in a generative conversation between plants, AI, and the artist. It draws a parallel between the actions of biological growth and machine learning, both seeded and tended by human input. The work is quietly influenced by ideas of environmental and human justice from fiction (Jemisin 2015-17, VanderMeer 2014), an entangled understanding of more-than-human relationships from social sciences (Tsing 2015, Haraway 1991 & 2016, Barad 2007), and of environmental and microbial care (Puig de la Bellacasa 2017). This complex ecology of ‘contaminated diversity’ (Tsing 2015) produces sublime encounters that threaten and enthral.

AB - A video made through incremental collaborations in a greenhouse and machine learning software. A landscape emerges from a glacier and grass begins to grow, only to recede back under the ice. Through freeze and thaw, it slowly gives way to a densely matted greenness that is grass-like, but also not. The work continues to grow in a generative conversation between plants, AI, and the artist. It draws a parallel between the actions of biological growth and machine learning, both seeded and tended by human input. The work is quietly influenced by ideas of environmental and human justice from fiction (Jemisin 2015-17, VanderMeer 2014), an entangled understanding of more-than-human relationships from social sciences (Tsing 2015, Haraway 1991 & 2016, Barad 2007), and of environmental and microbial care (Puig de la Bellacasa 2017). This complex ecology of ‘contaminated diversity’ (Tsing 2015) produces sublime encounters that threaten and enthral.

KW - Machine Learning

KW - video art

KW - Care

UR - https://vimeo.com/520653028

M3 - Exhibition

PB - Mozfest

CY - Online

ER -