Questioning the impact of AI and interdisciplinarity in science: Lessons from COVID-19

• URL: http://arxiv.org/abs/2304.08923v1
• Date: Tue, 18 Apr 2023 11:56:05 GMT
• Title: Questioning the impact of AI and interdisciplinarity in science: Lessons from COVID-19
• Authors: Diletta Abbonato, Stefano Bianchini, Floriana Gargiulo, and Tommaso Venturini
• Abstract summary: 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. 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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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