Two Oxford Martin School academics are challenging the idea that uncertainty in research is a reason to worry about the reliability of findings.
Professor Angela McLean, co-director of the Institute for Emerging Infections, and Professor Tim Palmer, co-director of the Programme on Modelling and Predicting Climate, helped create a new guide, Making Sense of Uncertainty, which was launched this week at the World Conference of Science Journalists in Helsinki.
They met with the guide’s other contributors over the course of 2012 to review what was being said about scientific uncertainty in the media, policy and public life, identify the misconceptions and share insights to help dispel them.
The team, specialists draw from across the fields of climate science, disease modelling, epidemiology, weather forecasting and natural hazard prediction, concluded that we should be relieved when scientists describe the uncertainties in their work. It doesn’t necessarily mean that we cannot make decisions, they say, but it does mean that there is greater confidence about what is known and unknown.
Charity Sense About Science, which commissioned the project, says that if policy makers and the public are discouraged by the existence of uncertainty, we miss out on important discussions about the development of new drugs, taking action to mitigate the impact of natural hazards, how to respond to the changing climate and to pandemic threats. Instead, it says, we need to embrace uncertainty, especially when trying to understand more about complex systems, and ask about operational knowledge: ‘What do we need to know to make a decision? And do we know it?’
Making Sense of Uncertainty discusses:
- The way scientists use uncertainty to express how confident they are about results
- That uncertainty can be abused to undermine evidence or to suggest anything could be true: from alternative cancer treatments to anthropogenic CO2 not changing the atmosphere.
- Why uncertainty is not a barrier to taking action
In her contribution to the guide, Professor McLean used examples of measles, swine flu and BSE outbreaks to demonstrate how uncertainty can inform decision-making, or be used by the media to alarm the public.
She wrote: “We used to think that everyone who caught flu became ill, but the 2009 H1N1 (swine flu) pandemic taught us that this clearly isn’t true. The biggest uncertainty throughout the pandemic was the proportion of people who would become ill after getting the virus.
"Models of the worst-case scenarios predicted this could be high, which was picked up in alarming headlines saying that lots of people would die from swine flu.
"In the end, roughly one third of the UK population were infected, which was as expected. But it was something of a surprise that only a tiny fraction became ill; it turns out that for H1N1 pandemic flu it is about 1 in 20.”