AI Breakthrough: Decoding Animal Emotions Across Species

AI unlocks the emotional language of animals

Can artificial intelligence help us understand what animals feel? A pioneering study suggests the answer is yes. Researchers from the Department of Biology at the University of Copenhagen have successfully trained a machine-learning model to distinguish between positive and negative emotions in seven different ungulate species, including cows, pigs, and wild boars. By analysing the acoustic patterns of their vocalisations, the model achieved an impressive accuracy of 89.49%, marking the first cross-species study to detect emotional valence using AI. "This breakthrough provides solid evidence that AI can decode emotions across multiple species based on vocal patterns. It has the potential to revolutionise animal welfare, livestock management, and conservation, allowing us to monitor animals' emotions in real time," says Élodie F. Briefer, Associate Professor at the Department of Biology and last author of the study. AI as a Universal Animal Emotion Translator By analysing thousands of vocalisations from ungulates in different emotional states, the researchers identified key acoustic indicators of emotional valence. The most important predictors of whether an emotion was positive or negative included changes in duration, energy distribution, fundamental frequency, and amplitude modulation. Remarkably, these patterns were somewhat consistent across species, suggesting that fundamental vocal expressions of emotions are evolutionarily conserved. A Game-Changer for Animal Welfare and Conservation The study's findings have far-reaching implications. The AI-powered classification model could be used to develop automated tools for real-time monitoring of animal emotions, transforming the way we approach livestock management, veterinary care, and conservation efforts. Èlodie F. Briefer explains: "Understanding how animals express emotions can help us improve their well-being. If we can detect stress or discomfort early, we can intervene before it escalates. Equally important, we could also promote positive emotions. This would be a game-changer for animal welfare." Key Scientific Findings Next Steps: Expanding Research and Sharing the Data To support further studies, the researchers have made their database of labelled emotional calls from the seven ungulate species publicly available. "We want this to be a resource for other scientists. By making the data open access, we hope to accelerate research into how AI can help us better understand animals and improve their welfare," Briefer concludes. This study brings us one step closer to a future where technology allows us to understand and respond to animal emotions -- offering exciting new possibilities for science, animal welfare, and conservation.

AI Might Be Able to Help Decipher Signs of Pain and Emotions in Animals

They have also been taught how to interpret various expressions Researchers are now reportedly experimenting with artificial intelligence (AI) to decipher the facial expressions of animals to understand their emotions. As per the report, several research groups are now using AI models with computer vision to analyse emotions and signs of pain and distress in farm animals. This is one of the niche use cases of the technology, but provided enough high-quality data, a large language model can figure out in real time whether an animal is in need of assistance. According to a Science.org report, several research groups are studying whether AI can be reliably used to monitor the well-being of farm animals. One such example is the Intellipig system, developed by researchers at the University of the West of England Bristol (UWE) and Scotland's Rural College (SRUC). The project, which is detailed on a web page of the university's website, is currently in its beta testing phase. Researchers have now reportedly implemented the Intellipig system in farms and are using AI to monitor hundreds of pigs. The report claims that every morning, a picture of every pig is taken before they are given food, and based on the AI-based identification, each pig is given specific food. Additionally, the AI also runs a separate inference to analyse the facial data and understand if there are any signs of pain or distress. In case there are, the AI alerts the farmer, who can then take a closer look and determine if the situation requires any intervention. Notably, the researchers have also claimed that the system can eventually analyse the emotions of these animals as well. Notably, deciphering health issues in animals from facial expressions and other behavioural patterns is not a new science. A lot of literature exists on this, and humans trained in the subject matter have been using the knowledge to understand when an animal might be suffering from an ailment or is emotionally not well. However, as per the report, relying on humans is not a sustainable method, as they need an average of 100 seconds to identify the various facial muscles. On the other hand, AI can do the same in near real-time at a large scale. Researchers are not planning to establish an autonomous system with AI in charge, as the technology is currently in a nascent stage.

Researchers are training AI to interpret animal emotions | TechCrunch

Artificial intelligence could eventually help us understand when animals are in pain or showing other emotions -- at least according to researchers recently profiled in Science. For example, there's the Intellipig system being developed by scientists at the University of the West of England Bristol and Scotland's Rural College, which examines photos of pigs' faces and notifies the farmer if there are signs of pain, sickness, or emotional distress. And a team at the University of Haifa behind facial recognition software that's already been used to help people find lost dogs is now training AI to identify signs of discomfort on animals' faces. These systems rely on human beings to do the initial work of identifying the meanings of different animal behaviors (usually based on long observation of animals in various situations), so they can train the AI on what to look for. However, a researcher at the University of São Paulo has experimented with using photos of horses' faces before and after surgery, as well as before and after taking painkillers, allowing an AI system to use deep learning to decide on its own what signs might indicate pain, with an 88% success rate in a recent study.