This is an old revision of the document!


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' (as Memo Akten called it) that forms in artificial neural networks during training.
  • how do animals, plants or machines learn through experience and exposure?
  • (how) could an AI become environmentally literate?
  • could such a 'synthetic' worldview deepen the understanding/appreciation of environmental complexity? (bypass human cognitive biases)
  • could machine learning expand environmental literacy in technology/society?
  • how do strategies of environmental observation compare/relate in AI, choreography, ecology, art, landscaping, traditional practices, etc..
  • thalience: how much of us humans is present in the 'robotic eye'? (Or more broadly: In an age of AI do we hold on to us being the humans?)

methods:

  • fieldwork: exploration through interactions between man-machine-environment in-situ
  • prototyping
  • 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?

reading:

framing:

see also:

  • environmental_machine_learning.1500790737.txt.gz
  • Last modified: 2017-07-23 06:18
  • by theunkarelse