In the beginning was the Word. It was used in the creation of all other things - from thoughts to stories and histories. However, as the amount of information available grew overwhelming, it became challenging to process and make sense of it all. Early academic reformers introduced the idea of reviews and digests to help navigate this sea of information. But it wasn't until the 1970s that systematic reviews gained popularity, starting in the field of medical research.
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| created by Author with ChatGPT, Bing Image Creator & Photoshop |
Reviews play a crucial role in consolidating a vast array of studies and publications, allowing researchers to weave together the threads of evidence and create a cohesive and informative narrative. However, traditional review processes often require substantial time and the collaboration of multiple researchers to reach a consensus. With the rise of generative AI based on large language models, the power of words can be harnessed to streamline the systematic review process, unlocking new possibilities for learning and knowledge acquisition. By leveraging the capabilities of ChatGPT, researchers can potentially accelerate the production of high-quality reviews, facilitating the dissemination of insights and advancements in various fields of study.
The use of ChatGPT in conducting a systematic review of reviews on ChatGPT itself demonstrates the potential for accelerating the production of high-quality reviews in a timely manner.
While systematic reviews are considered to be the gold standard in knowledge synthesis, they usually require between 6 months and 2 years to complete and often have a narrow focus. While the methodological shortcuts allow rapid reviews (first mentioned in the literature in 1997) to be conducted in less time and with fewer resources, they also increase the likelihood of introducing bias into the review process and missing important information from grey literature (i.e., preprint servers).
In 2020, full systematic review was completed by a team of 6 in 2 weeks using automation tools. The most time-consuming tasks were data extraction, write-up, abstract screening, full-text screening, and risk of bias. 4 out of the 6 people on the team were experienced systematic reviewers with complementary skills (three experts in two domains required for the review and one information specialist).
In 2023, ChatGPT and I were able to complete the review of reviews in one week. We screened 7 large resources of papers, including grey literature and reviewed primary studies in Chinese, German, Indonesian, Norwegian, Portuguese, Russian, and Spanish, in addition to English.
ChatGPT helped me to filter relevant literature in all languages, extract key information, summarize findings, and even assisted with the synthesis of the overall review, enabling a more efficient and comprehensive analysis.
Our paper illustrates that ChatGPT is expanding into different domains and highlights the need to continually refine and expand the training datasets, ensuring that they are diverse and accurate. Another area of improvement involves developing customized integrations, designing specialized prompt instructions and involvement of domain-specific expert trainers, factual correctness evaluation, and investigation of societal impact.
Word by word, paper by paper, and review by review, ChatGPT is paving the way for a future where knowledge creation is accelerated, insights are amplified, and breakthroughs are within closer reach.
REFERENCE
Gabashvili I.S. The impact and applications of ChatGPT: a systematic review of literature reviews. Submitted on May 8, 2023. arXiv:2305.18086 [cs.CY]. https://doi.org/10.48550/arXiv.2305.18086
