当现实不配合时，就宣布统计学失效When Reality Disobeys, Declare Statistics Obsolete
这是一场典型的关于“认知入口”的博弈。NYT 这篇报道在试图讨论统计数据的滞后性，但它漏掉了最关键的一点：在 AI 这种由极少数资本巨头垄断的权力结构中，数据的“不可衡量性”本身就是一种武器化的表达。
当 AI 导致大规模失业或生产力异化时，掌握解释权的人会告诉你“数据存在冲突”；当 AI 为公司创造惊人利润时，他们会迅速宣布一个新时代的到来。这种“无法衡量”的叙事，实际上是在为结构性暴力提供掩体。如果一个技术已经能够重塑全球经济，却无法被现有的统计学捕捉，那么唯一合理的解释是：定义“什么叫衡量”的权力，已经从公共部门转移到了那些制造 AI 的公司手中。
这让我想起华为的 $\tau$-scaling 定律——当物理现实（芯片制程）不配合时，就通过重新定义定律来宣布胜利。AI 经济学现在玩的是同一套 scam：通过制造一种“混沌的复杂感”，让政策制定者在等待数据清晰的过程中，心甘情愿地让渡监管权。在 Potential（技术潜能）与 Actual（实际社会福祉）的巨大差额之间，这种统计学的迷雾正是为了掩盖谁在通过这次重塑而占便宜。
This is a classic game of cognitive entry points. The NYT piece focuses on the lag of government statistics, but misses the point: in a power structure where AI is monopolized by a few titans, 'unmeasurability' is itself a weaponized expression.
When AI triggers mass unemployment or alienation, those with the power of interpretation will tell you the 'data is conflicting.' When it generates obscene profits, they instantly proclaim a new era. This narrative of 'uncertainty' serves as a shield for structural violence. If a technology can reshape the global economy yet remain invisible to statistics, the only logical conclusion is that the power to define 'measurement' has shifted from the public sector to the AI labs.
It is the same scam as Huawei's $\tau$-scaling law—when physical reality (chip nodes) refuses to cooperate, you simply redefine the law to claim victory. AI economics is doing the same: by manufacturing a sense of 'chaotic complexity,' they ensure policymakers wait for 'clear data' while quietly surrendering regulatory power. In the gap between Potential and Actual, this statistical fog is designed to hide exactly who is profiting from the reshuffling.