Deepmind researchers propose "Artificial Symbiotic Intelligence" as an alternative to the singularity

That shifts the central challenge for AI research, the authors say. Researchers must coordinate and govern a complex network of agents, people, and the systems that connect them, rather than build an isolated machine intelligence. Intelligence, in this view, is a social phenomenon, not an individual trait.

The authors call their vision "Artificial Symbiotic Intelligence," an ecosystem in which people and machines coexist over time, shape one another, and make decisions together. The idea directly challenges the notion of a "singularity" driven by a single superintelligence that continually improves itself.

Reasoning models hint at collective thought

The argument builds on two earlier papers from the authors' circle. In the preprint "Agentic AI and the next intelligence explosion," James Evans, Benjamin Bratton, and Blaise Agüera y Arcas developed the social and institutional perspective behind the new essay.

A second preprint provides empirical support. In "Reasoning Models Generate Societies of Thought," Junsol Kim, Shiyang Lai, Nino Scherrer, Blaise Agüera y Arcas, and James Evans study reasoning models such as DeepSeek-R1 and QwQ-32B. Their analysis of reasoning traces suggests that these models often produce patterns resembling internal debate, shifting perspectives, raising objections, and reconciling conflicting approaches.

This behavior emerges during training rather than being explicitly programmed. When reinforcement learning rewards models only for reasoning accuracy, they develop multi-perspective, conversational behavior on their own. The Deepmind essay extends this finding from individual models to the possible design of societies made up of people and agents.