In pursuit of a fit-for-purpose uncertainty guide

Measurement uncertainty is a measure of the quality of a measurement; it enables users of measurements to manage the risks and costs associated with decisions influenced by measurements, and it supports metrological traceability by quantifying the proximity of measurement results to true SI values. The Guide to the Expression of Uncertainty in Measurement (GUM) ensures uncertainty statements meet these purposes and encourages the world-wide harmony of measurement uncertainty practice. Although the GUM is an extraordinarily successful document, it has flaws, and a revision has been proposed. Like the already-published supplements to the GUM, the proposed revision employs objective Bayesian statistics instead of frequentist statistics. This paper argues that the move away from a frequentist treatment of measurement error to a Bayesian treatment of states of knowledge is misguided. The move entails changes in measurement philosophy, a change in the meaning of probability, and a change in the object of uncertainty analysis, all leading to different numerical results, increased costs, increased confusion, a loss of trust, and, most significantly, a loss of harmony with current practice. Recommendations are given for a revision in harmony with the current GUM and allowing all forms of statistical inference.