Pain Assessment in Animals: human experts, make way for AI!

Abstract

This study explores the question whether Artificial Intelligence (AI) can outperform human experts in animal pain recognition using sheep as a case study. It uses a dataset of N=48 sheep undergoing surgery with video recordings taken before (no pain) and after (pain) surgery. Four veterinary experts used two types of pain scoring scales: the sheep facial expression scale (SFPES) and the Unesp-Botucatu composite behavioral scale (USAPS), which is the `golden standard' in sheep pain assessment. The developed AI pipeline based on CLIP encoder significantly outperformed human facial scoring (AUC difference = 0.115, p<0.001) when having access to the same visual information (front and lateral face images). It further effectively equaled human USAPS behavioral scoring (AUC difference= 0.027, p=0.163), but the small improvement was not statistically significant.