Convergence of disciplines: a systematic review of multidisciplinary development approaches in artificial intelligence
Abstract
The integration of artificial intelligence (AI) across multiple disciplines is fostering a transformative shift in research and practice. This paper explores how multidisciplinary collaboration with AI is reshaping traditional methodologies and catalyzing innovation in diverse fields such as medicine, psychology, agriculture, mathematics, physics, and economics. A systematic review was conducted following the PRISMA 2020 guidelines. Relevant literature was identified through searches in PubMed, Scopus, and Google Scholar, covering publications from 2013 to August 2023. Inclusion criteria focused on English-language articles examining the intersection of AI and multidisciplinary applications. Additional studies were identified by screening reference lists of included articles. The analysis revealed that AI's multidisciplinary integration has significantly influenced practices across multiple domains. In medicine, AI supports diagnosis and treatment planning; in psychology, it enhances mental health interventions; and in agriculture, it contributes to addressing global food security challenges. The reviewed literature highlights how AI collaboration with fields such as physics, economics, and history is leading to innovative problem-solving strategies and paradigm shifts. The findings underscore the substantial potential of a multidisciplinary approach to AI. This convergence is not only accelerating technological advancement but also fostering more comprehensive and effective…
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Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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