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Risk: Trying to quantify our uncertainty
If you have a question about this talk, please contact Janet Gibson.
David Spiegelhalter is Winton Professor of the Public Understanding of Risk at the University of Cambridge, which he combines with being a Senior Scientist in the MRC Biostatistics Unit. His background is in medical statistics, particularly the use of Bayesian methods in clinical trials, health technology assessment and drug safety. He led the statistical team in the Bristol Royal Infirmary Inquiry and also gave evidence to the Shipman Inquiry. He has been a consultant to a number of public and private organizations including pharmaceutical companies.
In his new post he leads a small team which is attempting to improve the way in which the quantitative aspects of risk and uncertainty are discussed in society.
He was elected FRS in 2005 and awarded an OBE in 2006 for services to medical statistics
There has been a traditional division between ‘risk’, which can be quantified using probability distributions, and ‘uncertainty’, which is the surrounding mess of doubt, disagreement and ignorance. In well-understood situations we may be happy to quote reasonable odds for future events, and I shall look at ways in which these risks can be communicated visually. When the problem is more complex, analysts may use a mixture of judgement and historical data to construct a mathematical model that can assess future risks, but deeper uncertainties may be glossed over. I will use examples from swine flu to climate change to illustrate different approaches to dealing with uncertainty, from ignoring it to trying to fully quantify it, and conclude that we should all try to be aware and open about the magnitude and potential consequences of our ignorance.
This talk is part of the Darwin College Lecture Series series.
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