2024
Artificial intelligence for literature reviews: opportunities and challenges
Abstract: This paper presents a comprehensive review of the use of Artificial Intelligence (AI) in Systematic Literature Reviews (SLRs). A SLR is a rigorous and organised methodology that assesses and integrates prior research on a given topic. Numerous tools have been developed to assist and partially automate the SLR process. The increasing role of AI in this field shows great potential in providing more effective support for researchers, moving towards the semi-automatic creation of literature reviews. Our study focu…
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Cited by 118 publications
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“…[ 122 ] emphasizes the role of AI in making a more efficient and systematic reviewing process. The adoption of AI tools for scientific research is increasingly supported by studies such as [ 123 , 124 ], which highlight how AI-based tools can simplify the process of identifying and synthesizing scientific evidence, improving both accuracy and efficiency to the point of achieving levels comparable to those of human experts. Furthermore, this approach not only significantly accelerates article selection while maintaining the same methodological rigor but also reduces the risk of human error [ 125 , 126 ].…”
Section: Resultsmentioning
confidence: 99%
“…[ 122 ] emphasizes the role of AI in making a more efficient and systematic reviewing process. The adoption of AI tools for scientific research is increasingly supported by studies such as [ 123 , 124 ], which highlight how AI-based tools can simplify the process of identifying and synthesizing scientific evidence, improving both accuracy and efficiency to the point of achieving levels comparable to those of human experts. Furthermore, this approach not only significantly accelerates article selection while maintaining the same methodological rigor but also reduces the risk of human error [ 125 , 126 ].…”
Section: Resultsmentioning
confidence: 99%
“…The prospect of employing AI tools to aid in these intensive steps is attractive, and being actively explored by many scientific groups and software tool companies (Bolaños et al, 2024; Yip et al, 2024). However, due to the goal of maximum comprehensiveness and need for a careful balance between rigor and pragmatic flexibility to handle the highly heterogeneous and nuanced nature of the fundamental biology literature, the requirement for human judgement and validation is unlikely to be replaced by AI in the immediate future.…”
Section: Discussionmentioning
confidence: 99%
“…Research that has taken place advocating AI to assist or complement the work conducted by an IS note the complexity and nuances of IS undertakings and the difficulties faced with accuracy and robustness [ 23 , 39 ]. The contributions made to the AI discussion at CORE would support this, as concerns lay in the ethical questions around using AI including data privacy and bias in AI algorithms, as well as reservations on the quality of the data, low accuracy, illegitimate referencing, reproducibility of results, and ambiguous sourcing.…”
Section: Discussionmentioning
confidence: 99%
