Some Moral Issues in Risk Assessment

Cranor, Carl F.

doi:10.1086/293263

Cited by 50 publications

(33 citation statements)

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“…Hence, Dobbins (1987: 43) proposed that it would be useful to "increase the chance of an alpha error in an individual study from the usual 5% level to 10% or greater" (cf. Cranor 1990). However, an increased value of α * would increase the probability of type I errors (false positives), which is not in itself an advantage.…”

Section: An Applications-adjusted Corpusmentioning

confidence: 99%

Values in pure and applied science

Hansson

2007

Found Sci

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In pure science, the standard approach to non-epistemic values is to exclude them as far as possible from scientific deliberations. When science is applied to practical decisions, non-epistemic values cannot be excluded. Instead, they have to be combined with (value-deprived) scientific information in a way that leads to practically optimal decisions. A normative model is proposed for the processing of information in both pure and applied science. A general-purpose corpus of scientific knowledge, with high entry requirements, has a central role in this model. Due to its high entry requirements, the information that it contains is sufficiently reliable for the vast majority of practical purposes. However, for some purposes, the corpus needs to be supplemented with additional information, such as scientific indications of danger that do not satisfy the entry requirements for the corpus. The role of non-epistemic values in the evaluation of scientific information should, as far as possible, be limited to determining the level of evidence required for various types of practical decisions.

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Section: An Applications-adjusted Corpusmentioning

confidence: 99%

Values in pure and applied science

Hansson

2007

Found Sci

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“…Numerous authors have argued that it would be impractical and harmful for scientists to eliminate all the frames, metaphors, and values from their communication (see, e.g., Cranor, 1990;Douglas, 2009;Elliott, 2011;Larson, 2011). Nevertheless, if the scientific community is to maintain its reputation for being objective and for providing information in a manner that serves society as a whole (Hardwig, 1994), it needs to find ways to acknowledge and address this value-ladenness (and, as part of a larger project, to improve public education about this aspect of science).…”

Section: The Ethics Of Scientific Communication: Four Strategies To Amentioning

confidence: 99%

Backtracking and the Ethics of Framing: Lessons from Voles and Vasopressin

McKaughan

Elliott

2013

Accountability in Research

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When communicating scientific information, experts often face difficult choices about how to promote public understanding while also maintaining an appropriate level of objectivity. We argue that one way for scientists and others involved in communicating scientific information to alleviate these tensions is to pay closer attention to the major frames employed in the contexts in which they work. By doing so, they can ideally employ useful frames while also enabling the recipients of information to "backtrack" to relatively uncontroversial facts and recognize how these frames relate to their own values and perspectives. Important strategies for promoting this sort of backtracking include identifying the weaknesses of particular frames, preventing misunderstanding of them, differentiating well-supported findings from more speculative claims, and acknowledging major alternative frames.

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“…Risks are acceptable insofar as they have a greater benefit-to-risk ratio. In addition to considering risk-benefit information, judgments about the acceptability of risks may take into account whether risks are voluntarily assumed or involuntarily imposed on individuals (Cranor 1990); the relationship between who bears the negative consequences should a risk be realized and who stands to benefit from creating or imposing certain risks (Cranor 2007); the distribution of risks across a population (Harris et al 2009); and the process by which a risk is created, sustained, or allowed (Wolff 2006;Murphy and Gardoni 2010).…”

Section: Treatment Of Uncertainty In Engineeringmentioning

confidence: 99%

Classification and Moral Evaluation of Uncertainties in Engineering Modeling

2010

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Engineers must deal with risks and uncertainties as a part of their professional work and, in particular, uncertainties are inherent to engineering models. Models play a central role in engineering. Models often represent an abstract and idealized version of the mathematical properties of a target. Using models, engineers can investigate and acquire understanding of how an object or phenomenon will perform under specified conditions. This paper defines the different stages of the modeling process in engineering, classifies the various sources of uncertainty that arise in each stage, and discusses the categories into which these uncertainties fall. The paper then considers the way uncertainty and modeling are approached in science and the criteria for evaluating scientific hypotheses, in order to highlight the very different criteria appropriate for the development of models and the treatment of the inherent uncertainties in engineering. Finally, the paper puts forward nine guidelines for the treatment of uncertainty in engineering modeling.

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Some Moral Issues in Risk Assessment

Cited by 50 publications

References 0 publications

Values in pure and applied science

Values in pure and applied science

Backtracking and the Ethics of Framing: Lessons from Voles and Vasopressin

Classification and Moral Evaluation of Uncertainties in Engineering Modeling

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