AI-enhanced collective intelligence.

IF 6.7 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Patterns Pub Date : 2024-10-10 eCollection Date: 2024-11-08 DOI:10.1016/j.patter.2024.101074

Hao Cui, Taha Yasseri

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Abstract

Current societal challenges exceed the capacity of humans operating either alone or collectively. As AI evolves, its role within human collectives will vary from an assistive tool to a participatory member. Humans and AI possess complementary capabilities that, together, can surpass the collective intelligence of either humans or AI in isolation. However, the interactions in human-AI systems are inherently complex, involving intricate processes and interdependencies. This review incorporates perspectives from complex network science to conceptualize a multilayer representation of human-AI collective intelligence, comprising cognition, physical, and information layers. Within this multilayer network, humans and AI agents exhibit varying characteristics; humans differ in diversity from surface-level to deep-level attributes, while AI agents range in degrees of functionality and anthropomorphism. We explore how agents' diversity and interactions influence the system's collective intelligence and analyze real-world instances of AI-enhanced collective intelligence. We conclude by considering potential challenges and future developments in this field.

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人工智能增强的集体智慧。

当前的社会挑战超出了人类单独或集体行动的能力。随着人工智能的发展，它在人类集体中的角色将从辅助工具变为参与成员。人类和人工智能具有互补能力，两者结合在一起，可以超越人类或人工智能单独发挥的集体智慧。然而，人类与人工智能系统的互动本身就很复杂，涉及错综复杂的过程和相互依存关系。本综述从复杂网络科学的角度出发，构思了人类-人工智能集体智能的多层表征，包括认知层、物理层和信息层。在这个多层网络中，人类和人工智能代理表现出不同的特征；人类从表层到深层属性的多样性各不相同，而人工智能代理的功能和拟人化程度也各不相同。我们探讨了代理的多样性和互动如何影响系统的集体智能，并分析了现实世界中人工智能增强集体智能的实例。最后，我们探讨了这一领域的潜在挑战和未来发展。

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