AI Tech screens loyalty of Communist Party Members
Chinese researchers recently developed artificial intelligence technology (AI tech) that can gauge Chinese officials’ loyalty to the ruling Communist Party. The technology could be a tool for Beijing’s anti-corruption campaign to monitor further and purge “corrupt” Party members, indicating the regime’s growing fear of losing its legitimacy and power.
More than 4.7 million officials at all levels were investigated, subjected to various forms of disciplinary punishment, or prosecuted in the past 10 years, according to data released by China’s top watchdog, the Central Commission for Discipline Inspection (CCDI), on June 20.
Beijing’s anti-corruption campaign was initialed in November 2012, when Chinese Communist Party (CCP) leader Xi Jinping first came to power.
“Political corruption is the biggest corruption. Some corrupt elements have formed interest groups in the hope of ‘stealing power from the party and the state,” according to state-run media Xinhua.
State-Sponsored AI Tech, Digital Authoritarianism
The Institute of Artificial Intelligence at Hefei Comprehensive National Science Center in eastern China’s Anhui Province published a post, claiming that it developed technology that could directly support the CCP. A “wonderful connection between AI and construction of the CCP,” it touted on its official WeChat account on July 1, the 101st anniversary of the founding of the CCP.
The post included a video showing a man walking into an equipment room labeled “Smart Political Thinking Bar,” then sitting in front of a computer with a touch screen to take a test. After completing the test, his test score and analysis chart appeared on the screen.
The test, catered to Communist Party members, covers content taught in Party schools, including political indoctrination such as Xi Jinping Thought, communism, socialism, CCP history, and current policies and regulations.
The video introduced a device that could use AI technology to extract the biometric features of CCP members, including facial expressions, electroencephalography, and dermatological features, among others.
After integrating and analyzing personal data, it would evaluate how a person was able to understand the content he/she studied, such as gauging the level of concentration, recognition, and mastery of the various subjects.
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