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environmental_machine_learning [2017-07-21 06:24] – theunkarelse | environmental_machine_learning [2017-08-18 20:54] – theunkarelse | ||
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=== research thread: === | === research thread: === | ||
- | [[http:// | + | [[groworld_hpi]] > [[http:// |
=== potential starting questions: === | === potential starting questions: === | ||
- | * if/how the concept of the ' | + | * if/how the concept of the ' |
- | * how do animals, plants or machines learn through experience and exposure? | + | * how do animals, plants or machines learn through experience and exposure? |
- | * how much of us humans permeates into the robotic eye of the beholder? (Or more broadly: Do we hold on to us being the human?) | + | * (how) could an AI become environmentally literate? (+ implications) |
- | * can these ' | + | * what does a ' |
- | * how do strategies of environmental observation compare/ | + | * how do strategies of environmental observation compare/ |
- | * can machine learning | + | * thalience: how much of the human is present in the ' |
+ | * who is the observer in these experiments? | ||
+ | |||
+ | === blurb: === | ||
+ | Complex machines have been part of our environment for many centuries. Pioneers like al Jazari already made programmable automata around 1200AD. Machines came to dominate the land, sea and air dramatically since the Industrial Revolution. Until very recently the ability to relate to the environment was limited to plants and animals, but now machines are starting to blur those lines. What does it mean if machines join animals and plants there on more equal levels of awareness? Environmental Machine Learning is a program of fieldwork sessions with experiments as vehicles for materialising questions. | ||
+ | |||
+ | === context: === | ||
+ | All mayor tech companies have made AI their top priority in a race to file patent applications. These are not just reaching into the depths of human society, but permeate into the remotest mangroves, deserts or reefs. Some first experiments with machine learning | ||
=== methods: === | === methods: === | ||
* fieldwork: exploration through interactions between man-machine-environment in-situ | * fieldwork: exploration through interactions between man-machine-environment in-situ | ||
- | * prototyping | + | * prototyping: like in Boskoi & Machine Wilderness with experiments as vehicles for materializing questions |
* critical reflection | * 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? | + | * 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: (under construction)=== | ||
+ | * **dec 2017 / nov 2018** > EML Meetup series at MidWest Experimental Station Amsterdam > //theme: Synthetic Environmental Literacy// | ||
+ | * **may 2018** > fieldwork session Finland > //theme: Rules of Engagement: Machine and Animal interactions// | ||
+ | * **sep 2018** > fieldwork session Terschelling > //theme: Random Forests: Environmental observation and perception into algorithm// > 10 ppl / 2 or 3 days | ||
+ | * **nov 2018** > critical reflection / writing, web or print > // | ||
+ | * exhibition (Artis Zoo?) | ||
+ | * //Plain Air Nouveau// EU program | ||
=== reading: === | === reading: === | ||
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* " | * " | ||
* " | * " | ||
+ | * " | ||
* [[https:// | * [[https:// | ||
* [[https:// | * [[https:// | ||
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* [[https:// | * [[https:// | ||
* [[https:// | * [[https:// | ||
+ | * [[https:// | ||
* [[https:// | * [[https:// | ||
=== framing: === | === framing: === | ||
* [[http:// | * [[http:// | ||
+ | * [[https:// | ||
+ | * [[thalience]] | ||
+ | * Panpsychism | ||
=== see also: === | === see also: === | ||
- | * [[machine_learning]] | + | * [[machine learning]] |
- | * [[machine_ecology]] | + | * [[machine ecology]] |
+ | * [[Robust Physical Perturbations]] | ||
* http:// | * http:// |