让人类与AI协作生成更优解决方案，突破单一智能局限。
Amplifying Human Creativity and Problem Solving with AI Through Generative Collective Intelligence
- AI同时扮演交互伙伴与知识枢纽，构建人机认知桥梁。
- 基于比较判断与最小后悔原则，实现高效协同决策。
- 适用于气候适应、医疗改革等复杂社会问题，适合跨领域团队使用。
我们提出一种通用的人机协作框架，旨在放大人类与人工智能各自的优势，称为生成式集体智能（Generative Collective Intelligence, GCI）。GCI 中的 AI 扮演双重角色：作为交互代理，以及作为知识积累、组织与利用的技术载体。在此角色中，AI 构建了人类推理与模型之间的认知桥梁。它作为一种社会文化技术，使群体能通过结构化协作解决复杂问题，突破传统沟通障碍。我们认为，GCI 能够克服纯算法方法在问题求解与决策中的局限性。本文阐述了 GCI 的数学基础，基于比较判断定律与最小后悔原则，并简要展示了其在气候适应、医疗变革和公民参与等领域的应用。通过融合人类创造力与AI的计算能力，GCI 为应对单靠人类或机器无法解决的复杂社会挑战提供了新路径。
原文摘要 · Abstract (English)
We propose a general framework for human-AI collaboration that amplifies the distinct capabilities of both types of intelligence. We refer to this as Generative Collective Intelligence (GCI). GCI employs AI in dual roles: as interactive agents and as technology that accumulates, organizes, and leverages knowledge. In this second role, AI creates a cognitive bridge between human reasoning and AI models. The AI functions as a social and cultural technology that enables groups to solve complex problems through structured collaboration that transcends traditional communication barriers. We argue that GCI can overcome limitations of purely algorithmic approaches to problem-solving and decision-making. We describe the mathematical foundations of GCI, based on the law of comparative judgment and minimum regret principles, and briefly illustrate its applications across various domains, including climate adaptation, healthcare transformation, and civic participation. By combining human creativity with AI's computational capabilities, GCI offers a promising approach to addressing complex societal challenges that neither humans nor machines can solve alone.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。