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Laws of Fear: Beyond the Precautionary Principle

Sunstein, Cass R.·2005·Cambridge University Press eBooks

Abstract

What is the relationship between fear, danger, and the law? Cass Sunstein attacks the increasingly influential Precautionary Principle - the idea that regulators should take steps to protect against potential harms, even if causal chains are uncertain and even if we do not know that harms are likely to come to fruition. Focusing on such problems as global warming, terrorism, DDT, and genetic engineering, Professor Sunstein argues that the Precautionary Principle is incoherent. Risks exist on all sides of social situations, and precautionary steps create dangers of their own. Diverse cultures focus on very different risks, often because social influences and peer pressures accentuate some fears and reduce others. Instead of adopting the Precautionary Principle, Professor Sunstein argues for three steps: a narrow Anti-Catastrophe Principle, designed for the most serious risks; close attention to costs and benefits; and an approach called 'libertarian paternalism', designed to respect freedom of choice while also moving people in directions that will make their lives go better. He also shows how free societies can protect liberty amidst fears about terrorism and national security. Laws of Fear represents a major statement from one of the most influential political and legal theorists writing today.

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Metadata

Authors
Sunstein, C. R.
Venue
Cambridge University Press eBooks
Published
2005-03-31
OpenAlex
W4241512701
Cited by
843
References
0
FWCI
34.21
Type
book
Language
en
Open access
closed

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CoChat. (2026). Citation check: Laws of Fear: Beyond the Precautionary Principle. https://app.cochat.ai/papers/10.1017/cbo9780511790850
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Sunstein, C. R. (2005). Laws of Fear: Beyond the Precautionary Principle. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511790850

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.