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A person’s hand held above a laptop keyboard with digital graphics superimposed. The graphics include a glowing scale symbol in the center, a head icon labeled “AI” on the left with circuit lines, and a human head icon on the right with a brain illustration. Speech bubble icons appear around the heads, representing communication or decision-making between artificial intelligence and human thinking. The scene suggests balance between AI and human judgment.

New Joint AI Methods Group

Guiding responsible use of AI in evidence synthesis

JBI is delighted the announce the formation of the Joint AI Methods Group, a new collaborative effort designed to examine and shape how artificial intelligence can be appropriately applied within evidence synthesis.

The Joint AI Methods Group is a collaboration between global evidence synthesis organisations, Cochrane, Campbell Collaboration, JBI and the Collaboration for Environmental Evidence (CEE).

The group brings together methodological specialists, domain experts, and technical advisers to consider the role of emerging AI tools in activities such as screening studies, extracting data, and assessing quality.

The initiative reflects the increasing interest in digital support systems within systematic review processes, alongside the need for clear standards to ensure that innovations enhance, rather than compromise, methodological rigour. The Joint AI Methods Group will evaluate current capabilities, identify areas where AI may support efficiencies, and outline situations where traditional approaches remain essential.

JBI Executive Director Professor Zoe Jordan, member of the Joint AI Methods Group, emphasised the importance of careful and transparent adoption of new technology for evidence synthesis, including diverse types of systematic reviews, scoping reviews. “AI has the potential to assist with tasks that can be time-consuming for review teams,” Professor Jordan said. 

“Our focus is on ensuring that when AI methods are applied, they are clearly explained, tested for reliability, and aligned with trusted evidence standards. The Joint AI Methods Group will help provide researchers with practical direction grounded in methodological quality.”

This endeavour builds on JBI’s ongoing contribution to global methodological development and its commitment to supporting evidence-based decision-making. Training and educational materials are expected to be produced as guidance matures, ensuring review authors can apply recommended approaches confidently and consistently.

“Our aim is to support the research community in engaging with AI in a thoughtful and systematic manner,” Professor Jordan added. “Careful evaluation and clear guidance will be key as these technologies continue to evolve.”

The Joint AI Methods Group is part of the International Collaboration for Automation in Systematic Reviews (ICASR) and participates in the Evidence Synthesis Infrastructure Collaborative safe and responsible use of AI working group. The Group is also involved in the responsible AI use in evidence synthesis recommendations and guidance (RAISE), which offers tailored advice for a diverse range of roles in the evidence synthesis ecosystem. 

The aim of the Joint AI Methods Group is to work across these organisations and developments in the field, and facilitate discussion and critical thinking, particularly around standards for accuracy, evaluations and validation, with events, webinars and other activities.  The Group plans to release a Position Statement later in the year to define the Group’s position on AI for researchers and authors within JBI, Cochrane, Campbell Collaboration, and CEE to ensure they have clarity and are empowered to use them responsibly and ethically in their evidence synthesis. 

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