Machine-learning applications are proving to be especially useful to the scientific community studying the planet’s largest bodies of water.

This article is part of our latest Artificial Intelligence special report, which focuses on how technology continues to evolve and affect our lives.

If you had about 180,000 hours of underwater recordings from the Pacific Ocean, and you needed to know when and where, in all those different hours, humpback whales were singing, would you Google it?

That is what Ann Allen, a research ecologist at the National Oceanic and Atmospheric Administration, did. Sort of.

In January 2018, she approached Google and asked if they might be able to help her find the signal of humpback whale songs amid all the other ocean noise, like dolphin calls or ship engines. Using 10 hours of annotated data, in which the whale songs and other noises were identified, Google engineers trained a neural network to detect the songs, based on a model for recognizing sounds in YouTube videos, said Julie Cattiau, a product manager at Google.

About nine months later, Dr. Allen had a model for identifying humpback whale songs, which she is using in her research on the occurrence of the species in islands in the Pacific and how it may have changed over the last decade. Google used similar algorithms to help Canada’s Department of Fisheries and Oceans monitor in real-time the population of the endangered Southern Resident Orca, which is down to around 70 animals.

Machine learning and artificial intelligence applications are proving to be especially useful in the ocean, where there is both so much data — big surfaces, deep depths — and not enough data — it is too expensive and not necessarily useful to collect samples of any kind from all over.

Climate change makes machine learning that much more valuable, too: So much of the data available to scientists is not necessarily accurate anymore, as animals move their habitats, temperatures rise and currents shift. As species move, managing populations becomes even more critical.