Causality
Causality 豆瓣
作者: Phyllis Illari / Federica Russo Oxford University Press 2014
Head hits cause brain damage - but not always. Should we ban sport to protect athletes? Exposure to electromagnetic fields is strongly associated with cancer development - does that mean exposure causes cancer? Should we encourage old fashioned communication instead of mobile phones to reduce cancer rates? According to popular wisdom, the Mediterranean diet keeps you healthy. Is this belief scientifically sound? Should public health bodies encourage consumption of fresh fruit and vegetables? Severe financial constraints on research and public policy, media pressure, and public anxiety make such questions of immense current concern not just to philosophers but to scientists, governments, public bodies, and the general public.
In the last decade there has been an explosion of theorizing about causality in philosophy, and also in the sciences. This literature is both fascinating and important, but it is involved and highly technical. This makes it inaccessible to many who would like to use it, philosophers and scientists alike.
This book is an introduction to philosophy of causality - one that is highly accessible: to scientists unacquainted with philosophy, to philosophers unacquainted with science, and to anyone else lost in the labyrinth of philosophical theories of causality. It presents key philosophical accounts, concepts and methods, using examples from the sciences to show how to apply philosophical debates to scientific problems.
Causality 豆瓣
作者: Judea Pearl Cambridge University Press 2009 - 9
Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers' questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a wide variety of fields. Dr Judea Pearl has received the 2011 Rumelhart Prize for his leading research in Artificial Intelligence (AI) and systems from The Cognitive Science Society.