AI Deciphers Wolf Howls: Yellowstone's Cry Wolf Project Unveils Secrets of Wolf Communication

Jeffrey T. Reed, a linguist and AI expert with the Cry Wolf Project, is employing artificial intelligence to decode wolf communication within the Greater Yellowstone ecosystem. This initiative analyzes wolf howls to understand their structure, intention, and context. Wolves use collective howls, often initiated by the alpha female, to mark territory, protect pups, or regroup. They can recognize each other's voices without visual contact. According to Reed, a specific 'bark-howl' vocalization can translate to 'danger, I need help.' AI algorithms can now estimate pack size based on audio analysis of these howls. Autonomous recording units capture extensive audio in remote areas, which helps in detecting poaching and revealing the complexity of wolf communication. In one instance, a wild wolf, recorded with a body microphone, vocalized as much as an average human in a day. Reed presented his work at TED 2025 in Vancouver. He emphasizes that understanding wildlife communication is crucial for recognizing our place within the ecosystem. The Cry Wolf Project records 24-hour audio of wolves year-round from up to 60 recorders at a time. Reed also uses spectrograms to teach his AI what wolf sounds look like so it can disentangle them from other sounds through image recognition.