Advances in using AI to assess animal behaviour and welfare

Organiser: Mona Giersberg and Bas Rodenburg (University of Utrecht, The Netherlands)

We keep animals in various contexts: cats as companions, cows on a farm, sport horses or service dogs. As a society, we attach increasing importance to the welfare of these animals. In recent years, there has also been a paradigm shift within animal welfare science: from an emphasis on preventing welfare problems, such as pain and injury to promoting positive experiences and states in animals. Animal behaviour is a valuable indicator to assess animal welfare. In practice, however, it is often not feasible to monitor animal behaviour on a large scale and over a long period of time by human observers. This is where the added value of AI lies. With technologies such as computer vision, we can expand human capacities and monitor animal behaviour continuously and more accurately. This allows us to detect and respond earlier to behaviours that indicate a negative or positive state in animals. For this, it is important to bring together knowledge from different disciplines (e.g. veterinary science, biology, computer science), combine it and implement it in practical applications to improve the lives of animals.

This symposium brings together experts from different areas of animal behaviour science, AI and data science. We will discuss presentations on various applications of AI for measuring animal behaviour and monitoring animal welfare. These applications should put the animal at the centre and focus on how it feels and perceives its environment. The aim is to learn from each other and to explore possible collaborations to adapt successful AI tools from one field to other fields of animal behaviour science. Together, we will work to make full use of the potential of AI to improve the lives of animals in practice.

chickens with qr codes