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24 February 2023 2 min read

This blog is an excerpt from episode four of our Everyday AI podcast. 

When most people think about birds, they don’t think about artificial intelligence (AI).  

Dr Jessie Barry, Program Manager at the Cornell Lab of Ornithology, is not most people. 

Jessie leads a project called Merlin Bird ID. If you spot a bird you don’t recognise, you can upload a photo of it to the app. An in-built AI system then helps you figure out what this bird might be based at your current location. 

But it’s not only bird photos the team at Cornell University have been collecting over the years. The project is now also home to the world’s oldest and largest collection of animal and bird sounds.

“We have more than a million recordings. That's enough to start training this computer how to identify bird sounds," Jessie said. 

“In the last few years, phones have become so good that it’s become easier for more people to participate. Merlin can then help provide answers for what those birds are.” 

Not only is AI helping everyday people figure out which bird has been waking them up at 5am each morning, it’s also helping marine biologists with a thorny problem.

Using AI in conservation

Crown-of-thorns starfish are not cute, little starfish. They are covered in poisonous spines and eat coral. And on the Great Barrier Reef, their populations have been growing out of control. 

Traditionally, marine biologists will monitor population numbers by getting dragged through the water behind a boat and counting all the spiny species as they go. You can only tow divers at a certain speed, stopping every two minutes to record what they see. They’ll do this until they’ve surveyed the whole reef, which can take all day, or longer. 

We knew AI could help improve this process. So, we teamed up with Megha Malpani and her team at Google to build a machine learning model that could detect the plethora of poisonous problems.  

“It's operating in real time on the boat and processing video in real time to figure out where there are crown-of-thorns starfish," Megha explained.

"We can use it to map out the crown-of-thorns starfish and then help control teams figure out where the outbreaks are and prioritise them.”

The new system has been extremely effective. 

“In a test, the human expert found one crown-of-thorns starfish, while our machine learning model picked up 20!" Megha said.  

We made sure this technology can scale beyond the Great Barrier Reef. The model has been made open source so that students, researchers and data scientists can build on it for reef and environmental conservation projects across the world.

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