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 研究最具前途的技术之一,自疫情早期以来,医疗专业人员和 AI 专家之间的跨学科合作得到了积极鼓励。然而,我们对 COVID-19 和 AI 交叉领域的 10,000 多篇论文的分析表明,这些合作往往导致低可见度和影响力的科学成果。我们表明,科学影响力并不是由作者团队的整体跨学科程度确定的,而是由他们在研究中实际利用的知识多样性决定的。我们的结果提供了有关团队和知识结构如何影响新计算技术在科学中成功整合的见解。