Addressing the Challenges of Artificial Intelligence used for Data Extraction in Systematic Literature Reviews
SLRs are an established method for synthesizing and evaluating evidence on a particular topic. They involve a systematic and transparent process for identifying, selecting, and extracting data from relevant studies, and for synthesizing and analyzing the data to draw conclusions about the topic being studied. Data extraction is a critical step in the SLR process, but it can be a time-consuming process that is open to error when done manually, particularly for large and complex reviews.
To address these challenges, researchers are increasingly turning to AI as a tool for data extraction in SLRs. This can significantly reduce the time and effort required for data extraction and can help to minimize errors and omissions, but it is only as good as the strategies, expertise, and perspectives applied by the researcher.
This whitepaper covers 5 key dimensions of AI use, including their challenges and solutions.