How will artificial intelligence impact animals?

A fascinating question!

While Exploring the National Geographic official website, I found an article entitled "How artificial intelligence is changing wildlife research". In short it says that traditional methods of studying and counting, for example, giraffes are no longer valid, because they require time and money, which are not enough in the world of giraffes. To solve this problem, the Wildbook program was developed (developed by the nonprofit company Wild Me), which automatically identifies individual animals by their unique fur patterns or other distinctive features, such as accidents or outlines of the ears.

"Before, a population assessment wasn't something you could do on a weekend. It's incredible," Stacy-Dawes says. "It's been really helpful in allowing us to work faster and understand the population better than we ever really could have before."

All information received is uploaded to the GiraffeSpotter database, which is publicly available, and allows everyone, from park rangers to safari tourists, to upload giraffe photos and location information to an online database. "We can increase our learning efforts by 10 times, giving tourists and civilian scientists the opportunity to contribute to our research. This gives us a huge data set that would not be available before."

AI is on track to accomplish the tasks typically performed by researchers manually, from identifying individual animals from photographs for population studies to classifying millions of camera images collected by field scientists. Thanks to advances in computing power and machine learning, computers can now learn on their own using data banks.

"There's a perfect storm of AI and camera trap technology in terms of understanding animals from images," says Robert Long, who has been collaborating with Microsoft to develop AI tools to help monitor rare carnivores in the Pacific Northwest using camera traps. "I think it's literally a revolution underway in terms of auto-identification of animals, whether it's from still cameras or video."

Machine learning will not only usher in the automation of monitoring endangered species from camera trap data but also the automation of spotting poachers, something Morris describes as being right on the cusp of practicality: "You can't put people everywhere but you can put cameras in a lot of places." The potential for computer vision to help the planet encompasses everything from analyzing aerial imagery in arctic and savannah landscapes to monitor large animals to tracking forest recovery and loss from satellite imagery, to even monitoring plastic pollution using AI drones. "Computer vision can offer a lot not just for wildlife conservation applications but also sustainability more broadly," says Morris. "Fundamentally it's really about leveraging AI to save the planet."

Thanks for the scrolls!