Practical Implementations of AI & ML in Conservation Contexts
Authors: Francesco Tonini, Geospatial Data Scientist, The Nature Conservancy; Fei Fang, Assistant Professor, Carnegie Mellon University
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Learn about Artificial Intelligence (AI) and Machine Learning and how to incorporate AI into your programs and projects. This session will provide an introduction to two practical implementations of AI in the conservation context, highlight lessons learned from some of the early implementations of AI in our sector, and inspire new ideas and partnerships.
- Protection Assistant for Wildlife Security (PAWS) helps park rangers design effective patrol routes to prevent poaching of wildlife in large national parks. Developed by Carnegie Mellon University in partners with WCS, WWF, and other partners.
- Mapping Ocean Wealth (MOW) is a global initiative to map coastal and ocean ecosystem services and the benefits nature provides to people. AI techniques in image recognition, such as Deep Learning, were used to classify geo-tagged photos from Flickr combined with global data provided by the tourism industry to map tourism benefits provided by coral reefs in the Caribbean region. Developed by The Nature Conservancy in partners with UCSC and Critigen.
Each presentation will answer several questions from the framework that was developed by NetHope and NetHope members in collaboration with the University of California in Irvine, USAID, MIT, and several other partners.