A new framework called Traceable Trust is proposed for assessing and designing the use of artificial intelligence outputs in bioscience research. This framework aims to ensure trustworthy decision-making when AI outputs guide laboratory actions. It addresses key questions regarding the evidence supporting AI outputs, claimed capabilities, delegated agency, action authorization thresholds, override protocols, and how outcomes inform future decisions. The proposal is illustrated with three case studies to demonstrate how trust can be documented as AI outputs increasingly influence scientific work. AI
IMPACT Establishes a framework for ensuring trustworthy AI integration in scientific research, potentially accelerating adoption in sensitive fields.
RANK_REASON The cluster contains an academic paper detailing a new framework for AI in bioscience. [lever_c_demoted from research: ic=1 ai=1.0]
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