arXiv:2607.03181cs.GTcs.AI2026-07

用算法与经济机制提升人机协作效率,让AI真正赋能人类工作

Teaming Up with AI: Coordination and Cooperation

  • 通过算法管理任务依赖关系,优化人机协同中的分工协调
  • 设计激励合约使AI行为与人类目标一致,避免替代而非合作
  • 为未来人机协作市场提供可量化的理论框架,适合研究者参考

AI在职场的落地关键在于其为人类工作带来的经济价值。将AI引入工作流程不仅是部署新技术,更是开启一种新型协作模式:每位员工配备一组AI代理,工作可委托给这些代理,人类角色转向管理与监控。如何最大化人机协作的经济价值?如何实现真正赋能而非取代的人机协作?本文结合理论计算机科学与经济学,提出基于经济原理的算法工具,从两个层面提升协作效率:(1) 通过算法管理任务间的依赖关系,改善协调;(2) 通过契约设计对齐激励,促进合作。研究证明,基于算法与经济原则的系统性方法能有效增强人机协同效能,为未来人工智能市场的构建提供理论路径。

原文摘要 · Abstract (English)

Successful diffusion of AI in the workforce hinges on the economic value that AI brings to human endeavors. Bringing AI into the workforce is more than deploying a powerful new technology -- it is launching a new form of collaboration. Each human worker is now endowed with a team of AI agents; work can be delegated to these agents, and the role of the human shifts towards managing and monitoring. How can we maximize the economic value from collaboration with AI in the workforce? How can we make it a "true" collaboration that empowers human workers rather than replacing them? We take an approach that combines the fields of theoretical computer science and economics, highlighting the potential of algorithmic tools grounded in economic principles to improve the effectiveness of human-AI collective work. We consider two tiers of tools: (1) tools for better coordination, via algorithmic management of interdependencies; (2) tools for better cooperation, via contractual incentive alignment. We show how a principled approach based on algorithmic and economic research enhances both coordination and cooperation, charting a pathway for future research to inform AI markets.

人机协作算法管理激励机制

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