The Epistemology of the Precautionary Principle: Two Puzzles Resolved

Steglich‐Petersen, Asbjørn

doi:10.1007/s10670-014-9694-x

“…Similar reasoning might also be employed to shift the burden of proof (Powell, 2010;Steglich-Petersen, 2015). For instance, given a suspected risk of substantial harm, it might be argued that proponents of a novel technology must provide positive evidence of its safety, over and above standard procedures.…”

Section: The Precautionary Principle As a Decision Rulementioning

confidence: 99%

“…Steglich-Petersen (2015) attempts to do so but fails to resolve the original puzzle, asCarter and Peterson (2016) point out in reply. The solution I offer in Sect.…”

mentioning

confidence: 99%

Climate Uncertainty, Real Possibilities and the Precautionary Principle

Hopster

¹

2021

Erkenn

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A challenge faced by defenders of the precautionary principle is to clarify when the evidence that a harmful event might occur suffices to regard this prospect as a real possibility. Plausible versions of the principle must articulate some epistemic threshold, or de minimis requirement, which specifies when precautionary measures are justified. Critics have argued that formulating such a threshold is problematic in the context of the precautionary principle. First, this is because the precautionary principle appears to be ambiguous about the distinction between risk and uncertainty: should the principle merely be invoked when evidential probabilities are absent, or also when probabilities have low epistemic credentials? Secondly, defenders of the precautionary principle face an aggregation puzzle: in judging whether or not the de minimis requirement has been met, how should first-order evidential probabilities and their second-order epistemic standing be aggregated? This article argues that the ambiguity can be resolved, and the epistemological puzzle can be solved. Focusing on decisions in the context of climate uncertainty, I advance a version of the precautionary principle that serves as a plausible decision rule, to be adopted in situations where its main alternative—cost–benefit analysis—does not deliver.

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“…The remedy (R) can be formulated either to highlight the costs of acting or the costs of inaction (cf Steglich-Petersen 2015)…”

mentioning

confidence: 99%

Climate Uncertainty, Real Possibilities and the Precautionary Principle

Hopster¹

2021

Preprint

0

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A challenge faced by defenders of the precautionary principle is to clarify when the evidence that a harmful event might occur suffices to regard this prospect as a real possibility. Plausible versions of the principle must articulate some epistemic threshold, or de minimis requirement, which specifies when precautionary measures are justified. Critics have argued that formulating such a threshold is problematic in the context of the precautionary principle. First, this is because the precautionary principle appears to be ambiguous about the distinction between risk and uncertainty: should the principle merely be invoked when evidential probabilities are absent, or also when probabilities have low epistemic credentials? Secondly, defenders of the precautionary principle face an aggregation puzzle: in judging whether or not the de minimis requirement has been met, how should first-order evidential probabilities and their second-order epistemic standing be aggregated? This article argues that the ambiguity can be resolved, and the epistemological puzzle can be solved. Focusing on decisions in the context of climate uncertainty, I advance a version of the precautionary principle that serves as a plausible decision rule, to be adopted in situations where its main alternative – cost-benefit analysis – does not deliver.

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“…Sandin (1999: 892) also asserted that "the threat dimension concerns ontology, the uncertainty dimension concerns epistemology"; thus the mapping of risk components onto Sandin's (1999) dimensions of the Precautionary Principle shows us that the Precautionary Principle comprises both ontological and epistemological components. The Precautionary Principle's epistemology (Aven 2011, Carter and Peterson 2015, SteglichPetersen 2015, Carter and Peterson 2016 and ontology (Aven 2011) both have been studied. These philosophical investigations, while valuable, do not relate to the present discussion of psychometrics.…”

Section: The Precautionary Principle: What Is It?mentioning

confidence: 99%

Advances in technology commercialization models

Marinakis¹

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The Richards model has a shape parameter m that allows it to fit any sigmoidal curve. This article demonstrates the ability of a modified Richards model to fit a variety of technology diffusion curvilinear data that would otherwise be fit by Bass, Gompertz, Logistic, and other models. The performance of the Richards model in forecasting was examined by analyzing fragments of data computed from the model itself, where the fragments simulated either an entire diffusion curve but with sparse data points, or only the initial trajectory of a diffusion curve but with dense data points. It was determined that accurate parameter estimates could be obtained when the data was sparse but traced out the curve at least up to the third inflection point (concave down), and when the data was dense and traced out the curve up to the first inflection point (concave up). Rogers' Innovation I, II and III are discussed in the context of the Richards model. Since m is scale independent, the model allows for a typology of diffusion curves and may provide an alternative to Rogers' typology.

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The Epistemology of the Precautionary Principle: Two Puzzles Resolved

Cited by 3 publications

References 9 publications

Climate Uncertainty, Real Possibilities and the Precautionary Principle

Climate Uncertainty, Real Possibilities and the Precautionary Principle

Climate Uncertainty, Real Possibilities and the Precautionary Principle

Advances in technology commercialization models

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