远程劳动指数：测量AI对远程工作的自动化
机器学习
2025-10-31 v1 人工智能
计算与语言
摘要
AI在知识和推理基准测试方面取得了快速进展，但这些收益如何转化为经济价值和自动化仍不清楚。为了衡量这一点，我们引入了远程劳动指数（Remote Labor Index, RLI），这是一个涵盖多个行业的基准测试，包含实际的、具有经济价值的项目，用于评估在实际场景中端到端 agent performance（agent性能）。AI代理在RLI上的表现接近下限，最佳-performing agent（最佳表现的agent）实现了2.5%的自动化率。这些结果有助于以经验性证据为AI自动化讨论提供基础，为跟踪AI影响设定 common basis（共同基础），并使利益相关者能够主动应对AI驱动的劳动自动化。
引用
@article{arxiv.2510.26787,
title = {Remote Labor Index: Measuring AI Automation of Remote Work},
author = {Mantas Mazeika and Alice Gatti and Cristina Menghini and Udari Madhushani Sehwag and Shivam Singhal and Yury Orlovskiy and Steven Basart and Manasi Sharma and Denis Peskoff and Elaine Lau and Jaehyuk Lim and Lachlan Carroll and Alice Blair and Vinaya Sivakumar and Sumana Basu and Brad Kenstler and Yuntao Ma and Julian Michael and Xiaoke Li and Oliver Ingebretsen and Aditya Mehta and Jean Mottola and John Teichmann and Kevin Yu and Zaina Shaik and Adam Khoja and Richard Ren and Jason Hausenloy and Long Phan and Ye Htet and Ankit Aich and Tahseen Rabbani and Vivswan Shah and Andriy Novykov and Felix Binder and Kirill Chugunov and Luis Ramirez and Matias Geralnik and Hernán Mesura and Dean Lee and Ed-Yeremai Hernandez Cardona and Annette Diamond and Summer Yue and Alexandr Wang and Bing Liu and Ernesto Hernandez and Dan Hendrycks},
journal= {arXiv preprint arXiv:2510.26787},
year = {2025}
}
备注
Website: https://www.remotelabor.ai