Scientists tackling conservation problems turn to artificial intelligence

New technologies are generating far more information than ever before to help scientists assess and predict the health and behavior of species and ecosystems, as well as the threats they face. These include cryptic cameras, acoustic sensors, satellite imagery and citizen science apps. Now, researchers and conservation practitioners analyzing large data sets are exploring artificial intelligence, or AI--the ability of a machine or a computer program to think and learn--to help them process, analyze and interpret data to monitor ecosystems and predict results. Computer systems already exist that can host huge amounts of data, use AI with increasingly "smart" algorithms to classify data from the various types of sensors used by scientists, apply modeling results to create reproducible code, and create user interfaces to allow people to monitor natural systems and make predictions with high accuracy. By training computer algorithms with a subset of available data, machines can now learn what they should do for a given challenge--such as classify photos by the species found in them, identify areas of a satellite image containing water or intact forest, or translate speech from one language to another --based on human feedback and data collected from previous experience.