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Environmental Machine Learning

research thread:

groworld_hpi > Boskoi 2010 > Augmented Ecology 2014 > Machine Wilderness 2015 > Environmental Machine Learning (2018?)

potential starting questions:

  • if/how the concept of the 'umwelt' in biological creatures relates to the 'world view' that forms in artificial neural networks during training.
  • how do animals, plants or machines learn through experience and exposure? (+cognitive biases)
  • (how) could an AI become environmentally literate? (+ implications)
  • what does a 'synthetic worldview' mean for the understanding/appreciation of environmental complexity?
  • how do strategies of environmental observation compare/relate (in AI, choreography, ecology, art, landscaping, traditional cultures,..)
  • thalience: how much of the human is present in the 'robotic eye'?
  • who is the observer in these experiments? what kind of power-relations come out? (+symbiogenesis)

methods:

  • fieldwork: exploration through interactions between man-machine-environment in-situ
  • prototyping: like in Boskoi & Machine Wilderness with experiments as vehicles for materializing questions
  • critical reflection
  • multimodal and transdisciplinary approach: could the project also give room to explore observation strategies from various domains of human inquiry and probe them in-situ?

program:

  • fieldwork session Kilpisjarvi Biological Research Station, Finland?
  • fieldwork session GBSanctuary, Kerala, India?
  • critical reflection / writing, web or print?
  • exhibition (Artis Zoo?)

reading:

framing:

see also:

  • environmental_machine_learning.1501186117.txt.gz
  • Last modified: 2017-07-27 20:08
  • by theunkarelse