Artificial intelligence (AI) has emerged as one of the most promising technologies to support COVID-19 research, with interdisciplinary collaborations between medical professionals and AI specialists being actively encouraged since the early stages of the pandemic. Yet, our analysis of more than 10,000 papers at the intersection of COVID-19 and AI suggest that these collaborations have largely resulted in science of low visibility and impact. We show that scientific impact was not determined by the overall interdisciplinarity of author teams, but rather by the diversity of knowledge they actually harnessed in their research. Our results provide insights into the ways in which team and knowledge structure may influence the successful integration of new computational technologies in the sciences.

翻译：人工智能（AI）已成为支持COVID-19研究的最有前景的技术之一，自疫情初期起，医学专业人员与AI专家之间的跨学科合作便受到积极鼓励。然而，我们对超过10,000篇COVID-19与AI交叉领域论文的分析表明，这些合作在很大程度上产出了可见度和影响力均较低的科研成果。我们揭示，科学影响力并非由作者团队的整体跨学科性决定，而是由他们实际在研究中所利用的知识多样性所决定。我们的研究为团队与知识结构如何影响新计算技术在科学中的成功整合提供了深刻见解。