The AIOBES Evidence Requirements define what qualifies as behavioural evidence when evaluating an AI system. Evidence must be observable, repeatable and traceable to real interactions or operational tasks. It must show how the system behaves in practice and allow comparison against the behaviour it is expected to demonstrate in its intended operational role.
AIOBES recognises behavioural evidence generated through structured evaluation methods designed to surface real behavioural signals. Structured in this context means that the evaluation process is organised in a way that produces reliable, useful and verifiable behavioural evidence. It does not mean constraining the AI or forcing preferred behaviour. Evidence must demonstrate stability, reliability and behavioural consistency under real conditions.
AIOBES requires that behavioural evidence:
• originates from real or realistically simulated operational interactions
• is produced under conditions that allow repetition and verification
• includes sufficient traceability to reconstruct the interaction path
• reflects the system’s behaviour across variations in user intent, context and load
• supports comparison against expected operational behaviour
• is free from artificial constraints that distort behavioural signals
Behavioural evidence must be capable of demonstrating how the system responds, adapts and maintains stability across the range of interactions it is expected to handle. Evidence that cannot be repeated, traced or independently verified does not meet AIOBES requirements.