Artificial Intelligence and the New Science of Culture

Abstract

Cognition and culture have long been treated as parallel objects of study, joined more by metaphorthan by mechanism. We argue they are co-constituted in a manner now empirically tractable:subjectivities can be measured as local trajectories through a high-dimensional cultural field, andthe field is itself the aggregate of those trajectories. Recent advances in machine learning, includingembedding methods and large generative models, provide the first general framework formeasuring this co-constitution from micro-cognition to macro-social structure. Vector geometryrecovers individual conceptual structure, organizational communication, and large-scaleideologies; captures multimodal cultural content beyond text; and generates testable predictionsabout cultural emergence, including the simultaneous arrival of independent discoveries acrossdistant minds. We treat this predictability of simultaneous innovation as evidence for the co-constitutive view: when the geometry of the cultural field is measurable, trajectories of cognitivesearch through it become predictable. We then examine generative AI agents as simulators ofhuman subjectivity and as a qualitatively new coordinating substrate whose insertion into sociallife introduces evolutionary dynamics unprecedented in human cultural history. We formalize thisreflexive condition as a Heisenberg-like Uncertainty Principle for generative AI: as instruments forfixing a culture’s position grow more precise, our capacity to predict its trajectory degrades,because the machinery of cultural description and cultural action have merged. We close withethical questions raised by AI-mediated cultural drift, recursive synthetic culture, and the limits ofhuman cultural agency, offering guidelines for safe, equitable, and privacy-preserving research onAI and culture.