This wiki channel is a proof of concept, and may (or may not) be available after a trial period. All entries(n=50+) in this "open textbook" are in development, and the wiki channel itself is incomplete, so check any facts, concepts and suggestions with your librarian. If you have questions, start a discussion on the talk page or email Dean Giustini, UBC biomedical librarian — dean.giustini@ubc.ca.
Knowledge synthesis (KS) refers to a synthesis of studies, research and related evidence...ask your librarian for assistance
The challenge for librarians (and researchers) are the AI tools themselves (ie., problems with credibility, transparency, and reproducibility) — and their impact on ethical knowledge synthesis (KS) conduct and workflows.
Some KS librarians are saying, "What, if any, are the opportunities presented by these AI tools? Can we trust them when we don't know how they work? We need to test, research, report and evaluate.
In other words: unproven AI tools disrupt and complicate our important work in supporting researchers' search activities in evidence syntheses.
Our focus is on using proven techniques to develop robust, reproducible searches for knowledge synthesis (KS) — adding in relevant AI and ensuring scientific reproducibility and ethical integrity.
Note: This open textbook (or wiki channel) is intended to help librarians and other information professionals learn about AI. It is not, in itself, meant to be seen as promotion of AI. If anything, the goal is harms mitigation.
Definitions:
What is knowledge synthesis?
The Canadian Institutes of Health Research (CIHR) defines knowledge synthesis as: "...integration of research findings of individual research studies within the larger body of knowledge on the topic. A synthesis must be reproducible and transparent in its methods, using quantitative and/or qualitative methods, and will often take the form of a systematic review. Such an investigation will follow the methods developed by organizations such as The Cochrane Collaboration and the Joanna Briggs Institute."
What is artificial intelligence (AI)?
According to Wikipedia: — "...artificial intelligence is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making."
AI-powered searching — a definition refers to a range of tools and advanced search skills that health librarians cultivate to provide advanced research and consultation services to users in the AI era. The ability to locate highly-relevant studies to support knowledge synthesis activities of researchers is in high demand in 2025, but AI is disruptive due to tools such as Open Evidence, otto-SR, Perplexity, PubMed.ai, Undermind.ai. (A few of these tools are also used in KS for screening and data extraction.)
Note: Will Google Scholar survive the rise of AI-powered searching?
Although OpenAI is leading in the general AI space, independent and big AI companies are developing new search tools all the time, and experimenting with AI-powered academic searching in support of research. How will these tools affect our traditional bibliographic databases?
Consensushttps://consensus.app/ uses AI to distill findings from scientific research "reading" papers and extract key results.
Dimensions AI https://www.dimensions.ai/ provides free access to over 100 million publications and preprints to help you find papers; it shows the context - with citations, news and social media mentions, and links to funded grants and patents.
Note: Please use your critical reading skills while reading entries. No warranties, implied or actual, are granted for any health or medical search or AI information obtained while using these pages. Check with your librarian for more contextual, accurate information.
