For millions of years making sense of the environment was the domain of biological organisms, but now machines are starting to join in. This research programme looks at what the arrival of AI could mean for landscapes and non-human inhabitants. What are fundamental ingredients for environmental literacy and how could these be made accessible to an AI?
All the mayor tech companies have made artificial intelligence one of their main objectives and some first experiments with machine learning have been undertaken by ecologists as a way to address heterogeneity issues in their data. (Dealing with anything from genetic data, to climate, or species abundance.) EML aims to take a less task oriented view; what the appearance of machine learning in biodiverse environments could mean. What does it mean if machines join animals and plants there on more equal levels of awareness? Some artists, designers, environmentalists and conservationists have started probing those questions. Random Forests aims to bring those people together to map the territory, draw the first outlines of environmental machine learning and dig out the more fundamental questions it raises.
Project website: RandomForests.nl
Research notes: Environmental Machine Learning