David Orrell

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David Orrell (left) speaking with Robert Matthews at the Art Center Global Dialogues, Barcelona, 2008

David John Orrell (born 1962 in Edmonton) is a Canadian writer and mathematician. He received his doctorate in mathematics from the University of Oxford. His work in the prediction of complex systems such as the weather, genetics and the economy has been featured in New Scientist, the Financial Times, Adbusters, BBC Radio, Russia-1, and CBC TV. He now conducts research and writes in the areas of systems biology and economics,[1] and runs a mathematical consultancy Systems Forecasting. He is the son of theatre historian and English professor John Orrell.

His books have been translated into over ten languages. Apollo's Arrow: The Science of Prediction and the Future of Everything was a national bestseller and finalist for the 2007 Canadian Science Writers' Award. Economyths: Ten Ways Economics Gets It Wrong was a finalist for the 2011 National Business Book Award.

A consistent topic in Orrell’s work is the limitations of mathematical models, and the need to acknowledge these limitations if we are to understand the causes of forecast error. He argues for example that errors in weather prediction are caused primarily by model error, rather than the butterfly effect.[2] Economic models are seen as particularly unrealistic.[3] In Truth or Beauty: Science and the Quest for Order, he suggests that many such theories, along with areas of physics such as string theory, are motivated largely by the desire to conform with a traditional scientific aesthetic, that is currently being subverted by developments in complexity science.


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  1. ^ "Research". David Orrell: Writer and Mathematician. Retrieved 2 January 2014.  External link in |work= (help)
  2. ^ Orrell, David; Smith, Leonard; Barkmeijer, Jan; Palmer, Tim (2001). "Model error in weather forecasting". Nonlinear Proc. Geoph. 9: 357–371. 
  3. ^ Orrell, David; McSharry, Patrick (2009). "System economics: Overcoming the pitfalls of forecasting models via a multidisciplinary approach". International Journal of Forecasting. 25: 734–743. doi:10.1016/j.ijforecast.2009.05.002. 

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