A FOIA request by the Electronic Privacy Information Center revealed how excited the National Security Commission on Artificial Intelligence (NSCAI) is about using CCTV cameras to create a national surveillance network.
An NSCAI presentation titled “Chinese Tech Landscape Overview” discusses China’s facial recognition CCTV camera network in glowing terms.
“When we talk about data resources, really the largest data source is the government.'”
The presentation discusses how the Chinese government profits from encouraging companies to use facial recognition on visitors and employees.
“Now that these companies are operating at scale they are building a host of other services (e.g. facial recognition for office buildings, augmented reality)”
In America things are not all that different.
In the United States, the Feds encourage private companies like Clearview AI, Amazon Ring and Flock Safety to use facial recognition and automatic license plate readers to identify everyone.
Under the section “State Datasets: Surveillance = Smart Cities” the presentation extol’s China’s smart city surveillance saying, “it turns out that having streets carpeted with cameras is good infrastructure for smart cities as well.”
Americans do not need more government surveillance and we certainly do not need our smart cities carpeted with government surveillance devices.
The NSCAI says, “mass surveillance is a killer application for deep learning.
As our government applies AI deep learning to things like CCTV cameras, cellphone locations, and license plate readers, a person’s entire life can be predicted.
AI’s will use deep learning to accurately guess where you work, eat, shop, sleep, worship and vacation. Basically, mass surveillance is a killer application for knowing all there is to know about everyone.
Last week MLlive, revealed that a startup AI company co-founded by the University of Michigan is helping governments use CCTV cameras to monitor people for social distancing as indicated by a professor of electrical and computer engineering at the University of Michigan (UM):
…click on the above link to read the rest of the article…