AI Tools in Scientific Research: Boosting Individuals at the Expense of Collective Progress

Artificial intelligence (AI) tools have revolutionized scientific research by dramatically enhancing individual productivity, enabling researchers to produce more publications and achieve greater career acceleration. Empirical evidence from millions of papers shows AI adopters publish 3.02 times more and receive 4.84 times more citations, with junior scientists advancing 1.37 years faster. However, this individual empowerment comes with systemic costs: AI narrows research topic diversity by 4.63%, reduces interdisciplinary collaboration by 22%, and concentrates efforts in data-rich domains, potentially stunting the broader scientific enterprise. Drawing on large-scale analyses of 41.3 million papers and 2.28 million careers, this paper elucidates the mechanisms, quantifies trade-offs, and proposes policy interventions to mitigate collective limitations while preserving gains. Findings reveal a classic social dilemma, akin to generative AI's effects on creativity, urging a balanced approach to AI integration in science