Towards a theory of human creativity sustained by embodied collective intelligence.

Creativity in human societies may be sustained not by isolated minds but by embodied, collective intelligence. Using music as a model, this review argues that creativity depends on the dynamic tuning of uncertainty: moderate, time-varying surprise, often accompanied by interoceptive bodily sensations, can promote exploration, while interpersonal synchrony and social evaluation stabilize and transmit what is new. Because creativity is value-neutral, its social consequences depend on ethics, morality, and empathy.

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Abstract

Creativity in human societies may be sustained not by isolated minds but by embodied, collective intelligence. Using music as a tractable model system, this paper reviews evidence that creativity depends on the dynamic tuning of uncertainty: moderate, time-varying surprise-often accompanied by interoceptive bodily sensations-can promote exploration, while interpersonal synchrony and social evaluation can stabilize and transmit what is new. Because creativity itself is value-neutral, its social consequences depend on the co-occurrence of ethics, morality, and empathy. This paper argues that ethical norms bound admissible deviation, and empathic perspective-taking-supported by bodily and physiological coupling-acts as a social form of precision weighting that increases (or decreases) the likelihood that novelty is admitted, reshaped, or rejected by a community. From these ingredients emerges field-level intelligence (FLI): a process in which groups preserve diversity, selectively integrate deviations, and maintain "just-right" uncertainty under partially connected social structures. Although music provides a high-resolution measurement sandbox, this paper articulates boundary conditions and testable predictions for other domains (e.g., scientific discovery, design, and everyday collaboration) and for human-AI co-creativity. This paper outlines an empirical agenda: operationalize FLI and social precision weighting, quantify uncertainty dynamics in embodied interaction, and identify network conditions that sustain socially shared creativity without overgeneralizing across domains.