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How is Cochrane advancing responsible AI for evidence synthesis?
- Systematic reviews are built on the principles of rigour, transparency, and replicability. However, many current AI solutions don’t meet these principles. Cochrane says that "we are committed to addressing this challenge with an approach that is measured and responsible".
- Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.5 (updated August 2024). Cochrane, 2024.
How is Cochrane Integrating AI into Evidence Synthesis?
- Cochrane is implementing a range of automation solutions in its review processes.
- For example, machine learning is used to identify randomized controlled trials (RCTs), and Cochrane is integrating other technologies such as generative AI. It is primed to use AI and automation, due to high-quality, structured data from systematic reviews and included studies. For example, it can perform dynamic analysis reporting in RevMan, which allows authors to insert live results directly into their reviews while they’re writing and updating them a new feature in CENTRAL, our clinical trials database, that flags retracted publications to authors.
- Cochrane plans to increase reviews supported by Cochrane’s Evidence Pipeline, a service that combines automation and crowd verification to help authors identify relevant studies. In addition, it uses annotations on Patient/Population, Intervention, Comparison, Outcome (PICO) to inform decisions about new intervention review proposals. With technical advances, it is working on further guidance and training to improve AI literacy across our organization. https://www.cochrane.org/about-us/news/how-cochrane-advancing-responsible-ai-evidence-synthesis
- AI Methods Group <https://www.cochrane.org/about-us/news/new-ai-methods-group-spearhead-adoption-across-four-leading-evidence-synthesis-organizations> includes Cochrane, Campbell Collaboration, JBI, and the Collaboration for Environmental Evidence. The groups aims to standardize responsible AI use across evidence synthesis organizations; focuses on methods research, tool validation, and fostering collaboration via the International Collaboration for Automation in Systematic Reviews (ICASR).
- Cochrane’s Evidence Synthesis and Methods journal encourages research on AI applications in evidence synthesis, such as search strategy development, screening, and risk of bias assessment. Recent studies highlight modest adoption of traditional AI tools but promising advancements in language editing and data extraction.
- How is Cochrane advancing responsible AI for evidence synthesis?.
Responsible AI in Evidence Synthesis (RAISE)
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