| Developers: | Hefei Comprehensive National Science Center |
| Date of the premiere of the system: | July 2022 |
Content |
History
2022: Launch of a neural network to test the loyalty of Communist Party members
On July 4, 2022, Chinese researchers reported that they had developed an artificial intelligence-based system capable of assessing the loyalty of members of the Chinese Communist Party.
According to Didi Tang, a journalist for the Times newspaper in Beijing, the technology's work was detailed in an article that was posted online on July 1, 2022, but was removed shortly afterwards.
The Hefei Comprehensive National Science Center argued in the article that the developed neural network is capable of reading facial expressions and brainwaves, analyzing how attentive a party member is to "thinking and political education" in order to "further strengthen their confidence and determination to be grateful to the party, listen to the party and follow the party."
Hefei Science Center reportedly invited 43 Communist Party members who are part of the research team to test the technology.
The video, which was published in the article and has also been deleted, shows the study participant walking into a special kiosk, sitting opposite the screen and reading articles promoting the party's policies and achievements.
Tang said the kiosk can see the researcher's facial expression using possibly surveillance cameras.
The article said that "on the one hand, AI can judge how party members perceived thought and political propaganda, and on the other hand, it will provide reliable analytical data on thought activity and political education in order to improve and enrich them."
It is not known whether this technology is built into the kiosk, or how the technology will be implemented to monitor 96.77 million CCP members domestically.
Brainwave reading is nothing new for China - in 2018, the South China Morning Post published an article that brainwave reading technology was used on workers at one of the factories in Hangzhou.
Helmets were used to read workers' emotions, and artificial intelligence algorithms determined emotional outbursts such as depression, anxiety or rage.[1]
Notes
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