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International Conference on Uncertainty in Risk Analysis

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Wiley Online Library

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The views or positions expressed in this publication do not necessarily represent in legal terms the official position of the European Food Safety Authority (EFSA). EFSA assumes no responsibility or liability for any errors or inaccuracies that may appear.

Abstract

The European Food Safety Authority (EFSA) and the German Federal Institute for Risk Assessment (BfR) organised the International Conference on Uncertainty in Risk Analysis. Its aim was to bring together internationally recognized leaders of uncertainty analysis in food safety, environmental, occupational, animal, and plant health and to start a holistic discussion of uncertainty: its cognitive basis, methods and approaches of analysis, communication and consideration in decision making, and in discourse with society. The conference was held from February 21‐22, 2019 at the BfR in Berlin. On February 20, the preconference workshops took place with in total four parallel workshops.In total, nearly 300 people participated in the conference,18% of them coming from outside the European Union. Most of the presentations were livestreamed. The importance of uncertainty analysis for scientific assessments, the associated implications for decision making, and the need to communicate the most relevant uncertainties to decision makers and to the broad public was emphasised.Three main conclusions were drawn: firstly,training can be helpful in improving understanding of uncertainty. Secondly, scientists have an ethical responsibility to communicate uncertainty. In the short term this may not necessarily result in increased public trust of scientific work but enables society to engage in more informed discourse which should lead to better understanding and trust in the longer term.Thirdly, the risk assessor needs to take active steps to avoid undetected sources of uncertainty: to discover potential surprises and take account of uncertainty arising from choices of model structure, the use of standard measures and even the unambiguous definition of the problem itself.