Is there a limit to human judgement on uncertainty when making a scientific conclusion?

Abstract

Current scientific frameworks for characterising uncertainty in the conclusions of assessments evaluate both the strength of the scientific foundation for knowledge and the degree of certainty in the conclusion itself. These frameworks use a combination of qualitative and quantitative expressions of uncertainty. Judgements require a clear statement and a solid basis for the opinion. In practice, scientific principles for evaluating and communicating uncertainty are often challenged by experts' understanding of what is scientifically achievable. Structured approaches have been developed to elicit judgements from a group of experts, aiming to mitigate cognitive biases. Behavioural methods that seek, but do not enforce, consensus judgements are recognised as facilitating scientific reasoning. While these methods are designed for evaluating parameters within scientific models, what happens when judgments pertain to categorical statements closer to actual decision-making? This occurs in a post-modelling stage, where the combined impact of all identified sources of uncertainty must be considered. The discussion will be informed by experience working with scientific experts.  

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