A Comparison of Artificial Intelligence and Human Observation in the Assessment of Cattle Handling and Slaughter

Slaughter facilities use a variety of tools to evaluate animal handling, including but not limited to live audits, the use of remote video auditing, and some AI technologies. The objective of this study was to determine the similarity between AI and human evaluator assessments of critical cattle handling outcomes in a slaughter plant. One hundred twelve video clips of cattle handling and stunning from a slaughter plant in the United Kingdom were collected. The AI identified the presence or absence of: Stunning, Electric Prod Usage, Falling, Pen Crowding, and Questionable Handling Events. Three human evaluators scored the videos for these outcomes. Four different datasets were generated, and Jaccard similarity indices were generated. There was high similarity (JI > 0.90) for Stunning, Electric Prod Usage, and Falls between the evaluators and the AI. There was high consistency (JI > 0.80) for Pen Crowding. There were differences (JI ≥ 0.50) between the humans and the AI when identifying Questionable Animal Handling Events but the AI was adept at identifying events for further review. The implementation of AI to assist with cattle handling in a slaughter facility environment could be an added tool to enhance animal welfare programs.