Panic Breeder

Samir Bhowmik, Jukka Hautamäki

Research output: Artistic and non-textual formExhibitionArt in coproduction

Abstract

PANIC BREEDER is an installation consisting of a GAN-hallucinated video and Machina Baltica (the Beautiful Mind of), a sculpture.

With more than 85 million people living in its catchment area, the Baltic Sea has been exposed to an extensive environmental degradation since the beginning of the industrialization of the region in the late 19th century. It is often regarded as the most polluted sea in the world. This condition has negatively affected its biodiversity by directly endangering animals and plants or by damaging their habitats. 

Building on a HELCOM (Helsinki Commission [Baltic Marine Environmental Protection Commission]) Red List of endangered (threatened and declining) species, Panic Breeder presents a quasi-nature documentary of imaginary fantastical species as the future inhabitants of the Baltic Sea. It takes inspiration from An Evolution of Species, theorized by Charles Darwin, and comments on the iterative and adversarial capabilities of AI to probe the surreal and terrifying future of “survival of the fittest”. 
By quantifying the energy consumption of machine learning that goes into such suspect desires, from among the machine-generated breeding, a singular creature is manifested in physical form. In this fictional scenario, the loss of species is counter-balanced by the possibilities of AI-generated creatures to act as a temporary, if not futile, antidote to climate change panic and anxiety.

 The artwork uses GAN (Generative Adversarial Network), a class of machine learning systems, where two neural networks (Generative and Discriminative) compete with each other for several training sessions. The trainings utilize a custom dataset of extinct and endangered birds to generate new images. The animation created from the new images presents the transformation and evolution of the species. The artwork is subtitled with a running commentary, with other numerical metrics such as energy consumption and carbon emissions displayed on the side.
Original languageEnglish
PublisherAalto University
Publication statusPublished - 26 Dec 2019
MoE publication typeF2 Public partial realisation of a work of art
EventConnecting the Dots - Espoo, Finland
Duration: 27 Nov 201915 Jan 2020
https://www.aalto.fi/fi/tapahtumat/connecting-the-dots-tekoalynayttely

Keywords

  • artificial intelligence
  • environmental aestehtics
  • Machine Learning

Field of art

  • Contemporary art

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