In Masters of Uncertainty, Phaedra Daipha develops a new conceptual framework for the process of decision making, after spending years immersed in the life of a northeastern office of the National Weather Service. Arguing that predicting the weather will always be more craft than science, Daipha shows how forecasters have made a virtue of the unpredictability of the weather. Impressive data infrastructures and powerful computer models are still only a substitute for the real thing outside, and so forecasters also enlist improvisational collage techniques and an omnivorous appetite for information to create a locally meaningful forecast on their computer screens. Intent on capturing decision making in action, Daipha takes the reader through engrossing firsthand accounts of several forecasting episodes (hits and misses) and offers a rare fly-on-the-wall insight into the process and challenges of producing meteorological predictions come rain or come shine.

Combining rich detail with lucid argument, Masters of Uncertainty advances a theory of decision making that foregrounds the pragmatic and situated nature of expert cognition and casts into new light how we make decisions in the digital age.

Available:

Amazon  |  Chicago UPBarnes&Noble

 

Praise

Finally, a social scientist has grappled with decision making in the wild. This wonderful book embeds the decision process in the understanding of the task-at-hand, weaving temporality and institutional context together in ways that should profoundly influence the next generation of thinkers.

--John Levi Martin, author of The Explanation of Social Action

Predicting the weather—often inconvenient, sometimes costly, occasionally deadly—is a scientific art form of enormous consequence. Daipha’s masterful account brings alive the ‘screen work’ of forecasters and their daily struggles with powerful, yet imperfect, computer models. Masters of Uncertainty will be remembered as a benchmark in the sociology of science, technology, and decision making.

--Paul N. Edwards, author of A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming

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© 2020 Phaedra Daipha

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