The potentially fractal nature of intelligence

This article examines the hypothesis that intelligence may exhibit fractal properties. The concept of Nth order intelligence is introduced, emphasizing its implications for problem-solving scalability and contrasting the limitations of centralized systems with the potential of decentralized collective intelligence. The analysis explores the limitations of first-order AI systems in addressing non-linear problem scaling, particularly in the context of AI safety, and critiques the inherent risks of centralization in accelerating control-oriented trajectories. In contrast, decentralized collective intelligence is proposed as a scalable framework capable of optimizing problem-solving across diverse participants. The stakes of these competing trajectories are profound: one path leads to escalating centralization, potentially culminating in irreversible and misaligned control, while the other fosters collaboration through decentralized structures that ensure alignment. This work emphasizes the necessity of prioritizing decentralized, semantic-level approaches to intelligence to address existential challenges and ensure alignment with collective human interests.