Limits to the Problem-Solving Ability of Human Groups Related to Strong Collective Intelligence

This paper explores the concept of strong collective intelligence (strong CI) and its necessity for solving complex problems that surpass the capabilities of human groups working without such advanced collaborative frameworks. Drawing parallels between the evolution of multicellularity and the potential of strong CI, it argues that certain complex issues cannot be effectively addressed through traditional problem-solving strategies due to inherent limitations in human cognitive and organizational capacities. The study introduces five hypotheses that outline the theoretical boundaries limiting group problem-solving abilities: the classification of problem-solving domains, the establishment of universal metrics of fitness, the distribution and decentralization of problem-solving efforts, the development of a semantic model for system behavior, and the decomposition of collective behavior into reusable functional components. Through generative AI demonstrations, the paper illustrates examples of these limits in action, emphasizing the need for a General Collective Intelligence (GCI) platform to achieve optimal collective outcomes. The discussion section suggests collaborative strategies for overcoming these barriers, advocating for cooperation, convergence, and the design of systems that encourage collective problem-solving. The paper concludes by highlighting the potential of strong CI, particularly in the context of global challenges such as the Sustainable Development Goals (SDGs), to significantly enhance the problem-solving capabilities of human groups by leveraging technology and collective intelligence. Future research directions include a large-scale "Change the World University Challenge" to empirically validate the proposed hypotheses and further explore the application of strong CI in addressing complex global issues.