Amplifying Human Creativity and Problem Solving with AI Through Generative Collective Intelligence

TL;DR

This paper introduces Generative Collective Intelligence (GCI), a framework that enhances human-AI collaboration by leveraging AI as both an interactive agent and a knowledge-organizing technology to solve complex problems.

Contribution

It presents a novel framework for human-AI collaboration that combines mathematical foundations with practical applications across diverse societal domains.

Findings

GCI can improve problem-solving effectiveness in complex domains.

AI as a social technology bridges human and machine reasoning.

Applications include climate, healthcare, and civic engagement.

Abstract

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.