  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.
