U.S. AI Race With China: Trust Matters More Than Performance — SkimNews
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- Sam Altman admitted the AI revolution is going slower than expected, blaming "human habits and institutional inertia," while a majority of Americans now express more concern than excitement about AI and only 23% trust it compared to 87% of Chinese citizens.
- China has built a more extensive regulatory framework for AI deployment than the U.S., including mandatory labeling of AI-generated content, protections against algorithmic price discrimination, and rules shielding children and the elderly from anthropomorphic manipulation.
- U.S. midterm elections are emerging as an AI flashpoint, with conservative voters angry about data centers' water, electricity, and land demands saying they are preparing to "break rank" over the issue.
- OpenAI lost a $1-billion licensing deal with Disney following the Sora deepfake debacle, and Airbnb CEO Brian Chesky said his company uses Alibaba's Qwen model because it is "very good" and "fast and cheap" — evidence that adoption decisions are cost-driven, not performance-driven.
- Anthropic's latest Fable model has had its slowest adoption yet as companies gravitate toward cheaper or free open-source alternatives, reinforcing the argument that AI consumption costs now outweigh benchmark superiority.
- The 81st UN General Assembly convenes in New York this week with Xi Jinping scheduled to hold talks with Trump but opting to skip the general debate, opening space for other nations to shape AI governance norms.
- The European Union's long-standing consumer protection tradition could prove to be the key to sustainable AI innovation, even as Europe is dismissed as unable to match U.S. or Chinese model performance.
Why it matters: If AI adoption is being decided at the deployment and trust layer rather than at model performance — as Disney's rejection of Sora, Airbnb's choice of Alibaba's Qwen, and the 64-point U.S.-China trust gap all suggest — then U.S. policymakers laser-focused on winning the performance race are optimizing for the wrong finish line while consumer and voter backlash builds at home.
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