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Testing an algorithm in ‘silent mode’ is a period of algorithmic evaluation where the artificial intelligence (AI) tool is running on live or near-live data, making inferences about patients in real-time. These predictions are evaluated for accuracy and provide a test of the model’s performance in its intended clinical setting but without yet affecting patient care or institutional operations. Many believe it is a critical step to provide key assurances for the responsible and efficient integration of machine learning (ML) tools into clinical and administrative settings.

CANAIRI, or the Collaboration for trANslational AI tRIals (CANAIRI) project, will develop consensus-based standards of best practices and key capabilities for conducting clinical trials. The group advocates for a widening of these ‘silent’ trials toward one that is sociotechnical in nature and wants to draw attention to the importance of this critical testing stage for AI in healthcare.

As a first step, the group uses the term ‘translational trial’ to widen the scope and practices of silent trials to include human factors, implementation science, operational/systems integration, social license, legal and ethical, economics, environmental, and regulatory considerations. It calls these ‘translational trials’ to emphasise that when technology is translated from bench to bedside, it needs to be tested to ensure that it is as closely mapped as possible to what the bedside looks like and what the needs are.

Project CANAIRI will undertake an international consensus-generating methodology to identify current practices for translational/silent evaluations, develop guidance for health settings, and generate kno