Computer modelling: all about the image?

Sunday 20 October, 9.30am until 10.15am, Frobisher Auditorium 2 Battle over Scientific Information

Computer modelling is magic that turns empirical observations into our imaginary future. How many of us will need pensions, artificial hips, or houses in 2050? How much will sea levels rise or incomes fall? Plug enough data into a computer model, and out pour figures and graphs. But from pensions to climate, the line between projecting a trend and predicting the future is often blurred. What assumptions went into constructing the model of reality that underlies the mathematical model? Any projection assumes a host of factors will stay the same, or change predictably. In the real world, things are less consistent.

We need some kind of guide to how the future will probably turn out, if we are to plan anything that takes a few years to bring to fruition. Building power stations, for example, or training doctors. But we also need a good idea of how closely to trust that guide. The precision of graphs and numbers can stamp complex, informed speculation with undue scientific authority. So what are the limitations of mathematical modelling? Should we be more sceptical of its authority? And how much does it matter if some of the details are wrong?

Dr Robin Purshouse
lecturer, University of Sheffield; member, "Sheffield Alcohol Policy Model" team

Dr Jonathan Rougier
reader in statistics, University of Bristol

Hilary Salt
actuary; founder, First Actuarial

Timandra Harkness
journalist, writer & broadcaster; presenter, Futureproofing and other BBC Radio 4 programmes; author, Big Data: does size matter?

Produced by
Timandra Harkness journalist, writer & broadcaster; presenter, Futureproofing and other BBC Radio 4 programmes; author, Big Data: does size matter?
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