When a grizzly bear attacked a group of fourth- and fifth-graders in western Canada in late November 2025, it sparked more than a rescue effort for the 11 people injured – four with severe injuries. Local authorities began trying to find the specific bear that was involved in order to relocate or euthanize it, depending on the results of their assessment.

The attack, in Bella Coola, British Columbia, was very unusual bear behavior and sparked an effort to figure out exactly what had happened and why. That meant finding the bear involved – which, based on witness statements, was a mother grizzly with two cubs.

Searchers combed the area on foot and by helicopter and trapped four bears. DNA comparisons to evidence from the attack cleared each of the trapped bears, and they were released back to the wild. After more than three weeks without finding the bear responsible for the attack, officials called off the search.

The case highlights the difficulty of identifying individual bears, which becomes important when one is exhibiting unusual behavior. Bears tend to look a lot alike to people, and untrained observers can have a very hard time telling them apart. DNA testing is excellent for telling individuals apart, but it is expensive and requires physical samples from bears. Being trapped and having other contact with humans is also stressful for them, and wildlife managers often seek to minimize trapping.

Recent advances in computer vision and other types of artificial intelligence offer a possible alternative: facial recognition for bears.

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