Will Neural Scaling Laws Activate Jevons' Paradox in AI Labor Markets? A Time-Varying Elasticity of Substitution (VES) Analysis

• Tác giả: Rajesh P Narayanan, R. Kelley Pace
• Ngôn ngữ: eng
• Ký hiệu phân loại: 331.1 Labor force and market
• Thông tin xuất bản: 2025
• Bộ sưu tập: Metadata
• ID: 224256

Tóm tắt

 AI industry leaders often use the term ``Jevons' Paradox.'' We explore the significance of this term for artificial intelligence adoption through a time-varying elasticity of substitution framework. We develop a model connecting AI development to labor substitution through four key mechanisms: (1) increased effective computational capacity from both hardware and algorithmic improvements
  (2) AI capabilities that rise logarithmically with computation following established neural scaling laws
  (3) declining marginal computational costs leading to lower AI prices through competitive pressure
  and (4) a resulting increase in the elasticity of substitution between AI and human labor over time. Our time-varying elasticity of substitution (VES) framework, incorporating the G\o rtz identity, yields analytical conditions for market transformation dynamics. This work provides a simple framework to help assess the economic reasoning behind industry claims that AI will increasingly substitute for human labor across diverse economic sectors.