Over 25 years since 9/11, mass surveillance has expanded from targeted counterterrorism to routine use by law enforcement, immigration agencies, and private companies, creating an interconnected system where governments obtain surveillance data through private corporations and data brokers. The essay argues there has been no comprehensive analysis demonstrating these programs actually prevent attacks or improve safety, while the risks grow with advancing AI technologies.
For 25 years since 9/11, the U.S. government has shifted from targeted surveillance to mass surveillance techniques, initially justified as counterterrorism but now routinely used by law enforcement, ICE, and private security systems. Mass surveillance data flows through a pipeline from private companies—which collect it for commercial purposes—to government agencies, including the FBI purchasing data from brokers, with little evidence that these programs actually prevent attacks or improve public safety.
U.S. intelligence agencies reported Tuesday that top Chinese AI companies have systematically copied advanced American AI models like Claude, ChatGPT, Gemini, and Grok since 2024 through a practice called distillation. The FBI, NSA, and CISA identified six Chinese developers—DeepSeek, Moonshot AI, Alibaba, MiniMax, StepFun, and Z.AI—as conducting large-scale distillation campaigns likely with Chinese government awareness. China's Foreign Ministry rejected the accusations, stating its AI development reflects technological self-reliance and called for cooperation rather than confrontation.
A 2015 article advocating for a decentralized web architecture that preserves openness while addressing critical flaws in the current web: fragility, lack of privacy, and censorship vulnerability. The author proposes building a distributed web with properties similar to existing platforms but offering reliability, privacy, and accessibility without requiring permission to create.