After 2022, scientists became more interdisciplinary and exploratory, collaborated across more fields, and reported more differentiated team roles, with the largest shifts among high-AI-writing, established, and non-English LMIC authors.
The Longevity of Innovation
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Modern science is organized around specialization in training and teamwork. Scientists develop deep expertise within a field and combine complementary knowledge through collaboration to solve complex problems. Yet whether specialization is the most effective path to sustained innovation remains unclear. Here we introduce a quantitative framework that distinguishes generalists from specialists based on scaling patterns of disciplinary mobility while remaining independent of career age and productivity. Applying this framework to 49 million publications produced by 3 million scientists between 1900 and 2020, we examine how research style relates to innovation, learning, collaboration, and productivity. We find that scientists who move across fields are more likely to sustain innovative contributions throughout their careers, whereas those who remain within narrow fields exhibit the age-related decline in innovation. Generalists are less anchored to the literature of their training. They are more likely to pursue research independently, and, when they collaborate, they preferentially partner with other generalists. Teams with a greater share of generalists produce more innovative research, even after accounting for differences in knowledge diversity. Despite these advantages, generalists publish fewer papers on average and have become less common over time. These findings reveal a tension between the longevity of scientific careers and the longevity of scientific innovation.
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Scientific exploration, collaboration and labor division in the large language model era
After 2022, scientists became more interdisciplinary and exploratory, collaborated across more fields, and reported more differentiated team roles, with the largest shifts among high-AI-writing, established, and non-English LMIC authors.