Automated detection of physical contact events in youth ice hockey: a player-centric deep learning approach

Researchers developed an AI system that automatically analyzes youth ice hockey game footage to detect and track physical collisions and potential head impacts. While framed as a safety tool, this represents automated surveillance technology that monitors children's bodies and movements during sports, raising questions about privacy, consent, and the normalization of AI-powered behavioral monitoring in youth activities.