Economics of Human and AI Collaboration: When is Partial Automation More Attractive than Full Automation?

ArXi:2603.29121v1 Announce Type: cross This paper develops a unified framework for evaluating the optimal degree of task automation. Moving beyond binary automate-or-not assessments, we model automation intensity as a continuous choice in which firms minimize costs by selecting an AI accuracy level, from no automation through partial human-AI collaboration to full automation. On the supply side, we estimate an AI production function via scaling-law experiments linking performance to data, compute, and model size.