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This paper introduces a zero-assumption method for detecting occupational emergence based on the co-attractor concept, where shared vocabulary and practitioner cohesion reinforce each other. The method independently tests vocabulary and population cohesion using resume data, with ablation to confirm vocabulary as the binding mechanism. Applying this to 8.2 million US resumes from 2022-2026, the study finds that while a cohesive AI vocabulary formed rapidly, the AI practitioner population did not cohere, suggesting AI is diffusing rather than forming a distinct occupation.
Despite a rapidly forming professional vocabulary, the AI field isn't coalescing into a distinct occupation, challenging assumptions about how new technologies translate into new job categories.
Occupations form and evolve faster than classification systems can track. We propose that a genuine occupation is a self-reinforcing structure (a bipartite co-attractor) in which a shared professional vocabulary makes practitioners cohesive as a group, and the cohesive group sustains the vocabulary. This co-attractor concept enables a zero-assumption method for detecting occupational emergence from resume data, requiring no predefined taxonomy or job titles: we test vocabulary cohesion and population cohesion independently, with ablation to test whether the vocabulary is the mechanism binding the population. Applied to 8.2 million US resumes (2022-2026), the method correctly identifies established occupations and reveals a striking asymmetry for AI: a cohesive professional vocabulary formed rapidly in early 2024, but the practitioner population never cohered. The pre-existing AI community dissolved as the tools went mainstream, and the new vocabulary was absorbed into existing careers rather than binding a new occupation. AI appears to be a diffusing technology, not an emerging occupation. We discuss whether introducing an"AI Engineer"occupational category could catalyze population cohesion around the already-formed vocabulary, completing the co-attractor.
