Google is experimenting with a new AI based search tool called Scholar Labs that aims to help users find detailed research papers. The tool is being positioned as a fresh step forward, but it also raises an important question about whether AI can reliably surface high quality science.
Scholar Labs uses artificial intelligence to understand the key themes and relationships in a research query. It is currently available only to a small number of logged in users. In a demonstration, the tool was shown answering a question about brain computer interfaces. The first result was a review paper from 2024 published in a journal named Applied Sciences. Scholar Labs also explained why it chose that result, noting that the paper covers electroencephalogram signals and outlines important algorithms in the field.
However, the tool does not include filters that many researchers rely on to judge study quality. One such measure is the number of citations a paper receives. This number hints at how often other scientists have found the study useful. Some papers attract hundreds of citations within months while older papers may gather thousands over years. Another common measure is the impact factor of a journal. Journals with higher impact factors often carry a stronger reputation for rigorous research. Applied Sciences reports an impact factor of two point five, while Nature reports a significantly higher impact factor of forty eight point five.
The original Google Scholar still allows users to sort results by relevancy and displays citation counts. The goal of the new tool is to surface “the most useful papers for the user’s research quest,” according to a spokesperson. The system ranks studies by evaluating the full text, the place of publication, the authors, and how often and how recently the work has been cited in scholarly literature.
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