D avid C eccarelli & G iulia F rezza (eds.), Predictability and the unpredictable. Life, evolution and behaviour , R
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David Ceccarelli & Giulia Frezza (eds.), Predictability and the unpredictable. Life, evolution and behaviour, Roma: CNR Edizioni, 2018, 288 pp Nicolas Pastor1
© Springer Nature Switzerland AG 2020
Anyone wondering about the limits of predictability will certainly share the observation made by the editors of this volume: biology, and more specifically evolutionary biology, poses a real challenge to strong determinism and to the “culture of predictability” (p. 10) that is often regarded as an ideal of good science. This book provides the reader with a detailed mapping of the moving border that separates the predictable from the unpredictable in biology. The vast body of literature in this field makes it difficult to identify the ultimate determinants of this unpredictability, be it for the specialist or for the beginner, which is why a book such as this is so welcome. It presents the state of the art with an introduction as engaging as it is well written, and it contains fifteen clearly written essays gathered in three large thematic clusters. The first cluster deals with the study of stochasticity at different scales. Ignazio Licata highlights the importance of the choices that scientists must make when attempting to predict the evolution of complex and emerging systems. Luigi Preziosi discusses the predictability of cellular migrations and how the modelling of these phenomena must integrate the notions of robustness and multi-stability in order to capture their dynamics. Fabio Sterpetti deals with the epistemic status of randomness illustrated by genetic drift, as well as the explanatory nature of mathematical models in population genetics. The predictability of evolution at the genetic level is questioned by Virginie Courtier-Orgogozo and Arnaud Martin. Drawing on a large body of data, they demonstrate the central role of gene regulation in understanding, and even predicting, evolution at this level. This first thematic cluster ends with an article by Philippe Huneman on the predictability of neutral models in ecology (such as Hubbell’s theory) and in genetics (such as Kimura’s neutralist model). The second thematic cluster adopts a historical and epistemological approach to predictability in biology, from neuroscience to biomedicine. It discusses the * Nicolas Pastor [email protected] 1
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relationship between digital taxonomy and ‘big data’, whose ambivalence is underlined by Barbara Continenza. Maël Montévil and Giuseppe Longo also examine the value of big data. Noting that such data tends to generate spurious correlations, these authors call for the formulation of a genuine theoretical framework of organisms so that these data can be properly utilized. Carmela Morabito teaches us what epigenetics implies for our understanding of the development of cognitive functions and literacy. Finally, Giulia Frezza discusses two seemingly opposing discourses on dementia, with one pointing to an almost inevitab
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