Published • loading... • Updated
China Intensifies Battle Against Cyberbullying with New Draft Law
Platforms would need real-name checks and AI monitoring, with violators facing fines of up to 10 million yuan, the draft says.
- On Wednesday, The Cyberspace Administration of China released a draft law targeting cyberbullying, including AI-enabled abuse, applying to activities within China and overseas entities targeting the country.
- Beijing is tightening internet oversight following a surge in digital harassment and AI-enabled abuse, as the draft law covers online spread of harassing, defamatory, or false information alongside AI misuse.
- Under the proposed rules, platforms must verify user identities and offer users a "one-click protection" feature that blocks incoming messages and comments; schools are required to incorporate anti-cyberbullying material into their curricula.
- Service providers violating these regulations face fines of up to 10 million yuan, website shutdowns, or license revocation, while individuals using "troll armies" or AI-generated manipulation face severe legal repercussions including criminal prosecution.
- The regulator is canvassing public opinion on the draft law until August 28, as regulators from Europe to the United States are also writing rules for AI-generated cruelty, placing China's proposal among the more prescriptive attempts globally.
Insights by Ground AI
15 Articles
15 Articles
China drafts cyberbullying rules that reach AI-generated abuse
China’s internet regulator has published draft rules to combat cyberbullying, and, according to Reuters, the measures are written to reach abuse generated with artificial intelligence. The Cyberspace Administration of China released the draft for public comment on 29 July, part of a widening effort to police what happens on the country’s platforms. The draft targets […] This story continues at The Next Web
·Amsterdam, Netherlands (Kingdom of the)
Read Full Article
Coverage Details
Total News Sources15
Leaning Left4Leaning Right3Center3Last UpdatedBias Distribution40% Left
Bias Distribution
- 40% of the sources lean Left
40% Left
L 40%
C 30%
R 30%
Factuality
To view factuality data please Upgrade to Premium
