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Computer Science > Machine Learning
Title:Remote Labor Index: Measuring AI Automation of Remote Work
Abstract:AIs have made rapid progress on research-oriented benchmarks of knowledge and reasoning, but it remains unclear how these gains translate into economic value and automation. To measure this, we introduce the Remote Labor Index (RLI), a broadly multi-sector benchmark comprising real-world, economically valuable projects designed to evaluate end-to-end agent performance in practical settings. AI agents perform near the floor on RLI, with the highest-performing agent achieving an automation rate of 2.5%. These results help ground discussions of AI automation in empirical evidence, setting a common basis for tracking AI impacts and enabling stakeholders to proactively navigate AI-driven labor automation.
| Comments: | Website: this https URL |
|---|---|
| Subjects: | Machine Learning (cs.LG) ; Artificial Intelligence (cs.AI); Computation and Language (cs.CL) |
| Cite as: | arXiv:2510.26787 [cs.LG] |
| (or arXiv:2510.26787v1 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2510.26787 arXiv-issued DOI via DataCite |
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