US Edition
Study Exposes Computer Vision's Role in Pervasive Surveillance
- On 25 June 2025, researchers published a study in Nature revealing that computer vision research extensively enables surveillance of people worldwide.
- The study analyzed over 40,000 papers and patents from the 1990s to 2010s, showing a five-fold rise in surveillance-related patents tied to computer vision research.
- Researchers found that ambiguous language in documents, often calling humans 'objects', masks the true extent of surveillance linked to computer vision technologies.
- In a manual review, 90% of sampled papers and 86% of patents dealt with data on humans, with 78% of 2010s patents linked to surveillance, described as “pervasive and normalised.”
- The findings imply urgent threats to privacy and rights, prompting calls for computer vision researchers to adopt critical inquiry, conscientious objection, and ethical advocacy.
15 Articles
15 Articles
Insufficient Press Coverage of Big Data Surveillance
As the second Trump administration is dispatching its minions to stalk US streets, smashing citizens’ First Amendment rights, in partnership with unregulated Big Tech, it also surveils online, helping itself to citizens’ personal identifiable information (PII). In the age of surveillance capitalism, information is a hot commodity for corporations and governments, precipitating a multi-billion-dollar industry that not only profits from the collec…
Despite numerous advantages, computer vision and its presence threaten fundamental rights such as privacy, freedom of expression and movement, the study indicates.
Analysis of 42,000 studies and patents shows that the development of machine vision is primarily aimed at tracking humans
Pervasive surveillance of people is being used to access, monetize, coerce and control, study suggests
New research has underlined the surprising extent to which pervasive surveillance of people and their habits is powered by computer vision research—and shone a spotlight on how vulnerable individuals and communities are ...
Coverage Details
Bias Distribution
- 43% of the sources lean Left, 43% of the sources are Center
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