We look at this thoughtful attempt to dig into the complexity of real world situations and the attempts to make better models to understand what is happening around us and why. See more about the author Doyne Farmer here.Making Sense of Chaos: A Better Economics for a Better World, reviewedThis is a challenging topic to do well. Models are always limited by their inherent nature, how many factors do you incorporate? How much data do you need, over how long a time period? How do you factor in the slightly to very unpredictable behaviour of humans themselves, and their inclination towards capricious behaviour sometimes? The author does a good job of explaining these challenges, while offering some small hope with positive and interesting examples.The ability to predict the weather is one example that the author refers to. Citing the observation, that, with each decade that passes, humanity seems able to predict one more day further into the future. For sure we can't yet say what the weather will be one month from now, but one to three day forecasts are pretty reliable, and even four to six days out, we are now able to have a pretty good idea of what is coming down the line.Of course human's impact on global warming, and more unstable weather systems does then counter impact on these improvements.Farmer also discusses the solar industry with interesting, and potentially hopeful and positive predications about the continued fall in the price of solar generated energy units, relative to those generated from fossil fuels. We found this book to be well written, self critical, and aiming to tackle something which, by it's vary nature is extremely difficult to do really well. If you are looking to get up to speed in any of the topics tackled then we would recommend it.More about the bookIn Making Sense of Chaos one of our most influential scientists, J Doyne Famer, tackles these questions and more. Introducing the new field of complexity economics, he describes how rebellious economists and other scientists are revolutionising our ability to predict the economy, developing new approaches to global problems - like climate change, inequality, and the devastating impact of financial crises, which hit the poorest hardest.These issues are all rooted in the economy, yet mainstream economics isn't helping to solve our most pressing problems. Farmer explains why it can't do the job, and suggests a better alternative, called complexity economics. Complex systems are characterized by emergent phenomena - creating a whole that is qualitatively different from the sum of its parts. Examples are the human brain, the weather system, and of course, the economy.The ideas behind complexity economics have been around for many years, but enabled by enormous improvements in computing power and big data, its time has come. We can now build real-world computer simulations of the economy that track its emergent behaviour in detail. For instance, it is possible to simulate how the occupational labour force changes through time, how economic policies affect rich or poor households, or how the economy will evolve during the energy transition.This new science, Farmer shows, will allow us to test ideas and make better economic predictions, enabling us to better tackle global problems like inequality and climate change, creating sustainable growth, and more. And, ultimately, create a better world.More about the authorDoyne Farmer is an American complex systems scientist and entrepreneur who pioneered many of the fields that define the scientific agenda of our times: chaos, complex systems, artificial life, wearable computing, and more.Currently he is Director of the Complexity Economics programme at the Institute for New Economic Thinking at the Oxford Martin School, Baillie Gifford Professor of Complex Systems Science at the University of Oxford, Chief Scientist at Macrocosm, and an External Professor at the Santa Fe Institute.Previously, he was a...