Kaplan & Garrick (1981)
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Foundational paper establishing formal quantitative framework for risk analysis using probability triplets and Bayes' theorem, providing mathematical foundations for risk assessment methodologies applicable to AI safety risk quantification.
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Kaplan and Garrick (1981) propose a foundational quantitative definition of risk based on the concept of a 'set of triplets,' establishing a formal framework for risk analysis. The paper extends this definition to incorporate uncertainty and completeness, utilizing Bayes' theorem for probabilistic reasoning. The authors apply their framework to discuss key concepts including relative risk, the relativity of risk across contexts, and the acceptability of risk, providing a mathematical foundation for systematic risk assessment that has become influential in the risk analysis field.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| AI Risk Portfolio Analysis | Analysis | 64.0 |
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# On The Quantitative Definition of Risk Authors: Stanley Kaplan, B. John Garrick Journal: Risk Analysis Published: 1981-03 DOI: 10.1111/j.1539-6924.1981.tb01350.x ## Abstract A quantitative definition of risk is suggested in terms of the idea of a “set of triplets”. The definition is extended to include uncertainty and completeness, and the use of Bayes' theorem is described in this connection. The definition is used to discuss the notions of “relative risk”, “relativity of risk”, and “acceptability of risk”.
f1043d283b6cf307 | Stable ID: sid_z0PnZJS871