Overview

This book, geared toward academic researchers and graduate students, brings together research on all facets of how time and causality relate across the sciences. Time is fundamental to how we perceive and reason about causes. It lets us immediately rule out the sound of a car crash as its cause. That a cause happens before its effect has been a core, and often unquestioned, part of how we describe causality. Research across disciplines shows that the relationship is much more complex than that. This book explores what that means for both the metaphysics and epistemology of causes - what they are and how we can find them. Across psychology, biology, and the social sciences, common themes emerge, suggesting that time plays a critical role in our understanding. The increasing availability of large time series datasets allows us to ask new questions about causality, necessitating new methods for modeling dynamic systems and incorporating mechanistic information into causal models.

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9781108476676

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Reviews

'Understanding the causal relations that make the world go round would be so much easier if mechanisms didn't operate over time, or at least if they operated at a single time scale. But mechanisms do unfold over multiple time scales, making not only inferences about causality tricky, but the very definition of causality the most slippery of conceptual issues. This book unpacks all this at the cutting edge of philosophy and science. It even addresses what may be the heart of the problem: how people understand causality and its counterpart, time.' Steven Sloman, Brown University, Rhode Island 'A very useful collection on a fascinating topic. The connection between time and causation seems as obvious in science as in everyday life, yet turns out to be deeply puzzling, as soon as we dig below the surface. The essays collected here offer an excellent and accessible introduction to the issues, from an impressively interdisciplinary range of perspectives.' Huw Price, University of Cambridge

'Understanding the causal relations that make the world go round would be so much easier if mechanisms didn't operate over time, or at least if they operated at a single time scale. But mechanisms do unfold over multiple time scales, making not only inferences about causality tricky, but the very definition of causality the most slippery of conceptual issues. This book unpacks all this at the cutting edge of philosophy and science. It even addresses what may be the heart of the problem: how people understand causality and its counterpart, time.' Steven Sloman, Brown University, Rhode Island

Author Information

Samantha Kleinberg is an Associate Professor of computer science at Stevens Institute of Technology, New Jersey. She received her Ph.D. in computer science from New York University, and previously held an NSF/CRA Computing Innovation Fellowship at Columbia University. She is the recipient of NSF CAREER and JSMF Complex Systems Scholar Awards and is a Kavli Fellow of the National Academy of Sciences. She is the author of Causality, Probability and Time (Cambridge, 2012) and Why: A Guide to Finding and Using Causes (2015).

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