Lecture: Risk & Trying to Quantify Our Uncertainty
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.