"From Watching People to Understanding Situations: Balancing Public Safety, Privacy and Social Acceptance in AI Video Surveillance"
Year: 2026
Type: article
Abstract: Artificial intelligence enabled video surveillance can improve public safety by detecting crowd gatherings, abnormal behaviour and emerging hazards, but it also intensifies concerns about privacy and social acceptance.This Opinion argues that the central design question should not be how much information can be extracted from video, but how little personal information is actually required to achieve a legitimate safety objective.Situation-oriented systems based on counting, density, flow and temporal anomaly detection may preserve useful security capabilities while reducing unnecessary identification, retention and profiling.Privacy by design can therefore be treated not as a barrier to intelligent surveillance, but as an engineering requirement.
Author: Rafael Rodrigo-Guillen
Institution: University of Alicante
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7225157796