AI RESEARCH
The Novelty Bottleneck: A Framework for Understanding Human Effort Scaling in AI-Assisted Work
arXiv CS.AI
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ArXi:2603.27438v1 Announce Type: new We propose a stylized model of human-AI collaboration that isolates a mechanism we call the novelty bottleneck: the fraction of a task requiring human judgment creates an irreducible serial component analogous to Amdahl's Law in parallel computing. The model assumes that tasks decompose into atomic decisions, a fraction $\nu$ of which are "novel" (not covered by the agent's prior), and that specification, verification, and error correction each scale with task size.