AI Patents in the United States and China: Measurement, Organization, and Knowledge Flows
We develop a high-precision classifier to measure artificial intelligence (AI) patents by fine-tuning PatentSBERTa on manually labeled data from the USPTO's AI Patent Dataset. Our classifier substantially improves the existing USPTO approach, achieving 97.0% precision, 91.3% recall, and a 94.0% F1 score, and it generalizes well to Chinese patents based on citation and lexical validation. Applying it to granted U.S. patents (1976-2023) and Chinese patents (2010-2023), we document rapid growth in AI patenting in both countries and broad convergence in AI patenting intensity and subfield composition, even as China surpasses the United States in recent annual patent counts. The organization o...
| Authors | Hanming Fang, Xian Gu, Hanyin Yan et al. |
|---|---|
| Primary category | econ.GN |
| Published | 12 April 2026 |
| Last updated at source | 12 April 2026 |
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