The diversity of human expression is the raw material of discovery. Generative artificial intelligence threatens this resource even as it promises to accelerate innovation, a paradox now visible across science, culture, and professional work. We propose a framework to explain this tension. AI systems compress informational variance through statistical optimization, and users amplify this effect through epistemic deference. We call this process the AI Prism. Yet this same compression can enable novelty. Standardized forms travel across domain boundaries, lowering translation costs and creating opportunities for recombination that we term the Paradoxical Bridge. The interaction produces a U-shaped temporal dynamic, an initial decline in diversity followed by recombinant innovation, but only when humans actively curate rather than passively defer. The framework generates testable predictions about when compression constrains versus amplifies creativity. As AI becomes infrastructure for knowledge work, managing this dynamic is essential. Without intervention, the conditions for recovery may not arrive.

翻译：人类表达的多样性是发现的原材料。生成式人工智能在承诺加速创新的同时却威胁着这一资源，这一悖论如今在科学、文化和专业工作中已清晰可见。我们提出一个解释这种张力的理论框架。人工智能系统通过统计优化压缩信息方差，而用户则通过认知顺从放大这种效应。我们将此过程称为"AI棱镜"。然而，这种压缩本身也能催生新颖性。标准化的形式跨越领域边界传播，降低了转化成本，并创造了我们称之为"悖论之桥"的重组机遇。这种相互作用产生了U型时间动态——多样性初始下降随后出现重组式创新，但仅当人类主动策划而非被动顺从时才会发生。该框架产生了关于压缩何时抑制或放大创造力的可检验预测。随着人工智能成为知识工作的基础设施，管理这种动态至关重要。若不加干预，复苏的条件可能永远不会到来。