How Swiss AI Recognises Wild Animals And Helps Biologists Worldwide

2026-04-08 04:05:11

(MENAFN- Swissinfo) From identifying bears in Alaska to tracking deer in the Alps, Swiss-built AI is opening new frontiers in wildlife conservation. But machines are no miracle workers: they rely on researchers who have spent a lifetime in nature. This content was published on April 8, 2026 - 09:00 7 minutes

I analyse the risks, opportunities and concrete impacts of artificial intelligence on society and everyday life. Since joining SWI swissinfo in 2020, I translate the complexity of science and technology into stories that speak to a global audience. Born in Milan to an Italian-Egyptian family, I have been passionate about knowledge and writing since childhood. I worked between Milan and Paris as a multilingual editor for technology magazines before transitioning to international journalism with SWI swissinfo.

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Beth Rosenberg has spent the past 20 years observing bears in remote areas of Alaska, without electricity or running water. The biologist and ecologist, who works at the Alaska Pacific University, can now recognise individual animals by the shape of their heads and muzzles, as well as by small scars or distinctive behaviours.

“Some bears always fish in a certain way, or like to play with each other. If you spend enough time observing them, individual differences quickly become obvious,” she says.

Now, Rosenberg is sharing her experience with an artificial intelligence (AI) model. In collaboration with researchers at the Swiss Federal Institute of Technology Lausanne (EPFL), Rosenberg helped to train an AI system on how to recognise individual bears. The training relies on Rosenberg's long experience and thousands of photos she collected over six years along the McNeil River in Alaska, where hundreds of brown bears converge every year to catch salmon migrating upstream.

Studying these predators is vital for understanding the health of their ecosystem and how species respond to climate change. But doing so non-invasively in remote environments is challenging. This is where AI can make a difference. Potentially, it could open up“enormous opportunities to better understand wildlife and ecosystems, supporting conservation and management,” Rosenberg says.

Recognisable snouts

The AI model developed with EPFL can reliably identify bears along the McNeil River based on physical features such as head shape or profile. It can track their movements over time and across space by linking images of the same individual animal taken at different times and locations and can even flag new bears it has never seen before – a result Rosenberg describes as unprecedented.

By analysing a large number of images, AI also helps researchers to identify recurring patterns – such as where bears feed, rest or move – and to study their behaviour.

“This helps us better understand bears, their population dynamics, and answer many important ecological questions,” the researcher explains.

Reaching this point, however, was far from easy.

Unlike zebras or leopards, bears do not have easily distinguishable patterns. This makes them particularly difficult to identify for computer vision systems – AI technologies which analyse and interpret images and videos in a way which mimics human vision. Bears also look dramatically different at various times of the year: before hibernation, they can gain over 100 kilograms, and their fur changes completely between summer and winter.

“That's enough to confuse even the most trained eyes,” Rosenberg says.

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