For scientists who have long tried to untangle animal signals, this discovery of emotional traits across species is a leap forward in a field that is being transformed by AI
AI can detect positive or negative emotions. Representation pic/iStock
Humans have long recognised certain well-known behaviour like a cat hissing as a warning, but in many cases we’ve had little clue of what’s going on inside an animal’s head. Now we have a better idea, thanks to a Milan-based researcher who has developed an AI model that he claims can detect whether their calls express positive or negative emotions.
Stavros Ntalampiras’s deep-learning model, which was published in Scientific Reports, can recognise emotional tones across seven species of hoofed animals, including pigs, goats and cows. The model picks up on shared features of their calls, such as pitch, frequency range and tonal quality.
The analysis showed that negative calls tended to be more mid to high frequency, while positive calls were spread more evenly across the spectrum. In pigs, high-pitched calls were especially informative, whereas in sheep and horses the mid-range carried more weight, a sign that animals share some common markers of emotion but also express them in ways that vary by species.
For scientists who have long tried to untangle animal signals, this discovery of emotional traits across species is a leap forward in a field that is being transformed by AI.
The implications are far-reaching. Farmers could receive earlier warnings of livestock stress, conservationists might monitor the emotional health of wild populations remotely, and zookeepers could respond more quickly to subtle welfare changes.
This potential for a new layer of insight into the animal world also raises ethical questions. If an algorithm can reliably detect when an animal is in distress, what responsibility do humans have to act? And how do we guard against over-generalisation, where we assume that all signs of arousal mean the same thing in every species?
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