This paper re-interprets the precautionary principle as a ‘social epistemic rule’. First, it argues that sometimes policy-makers should act on claims which have not been scientifically established....

Moral theory has mostly focused on idealized situations in which the morally relevant properties of human actions can be known beforehand. Here, a framework is proposed that is intended to sharpen moral intuitions and improve moral argumentation in problems involving risk and uncertainty. Guidelines are proposed for a systematic search of suitable future viewpoints for hypothetical retrospection. In hypothetical retrospection, a decision is evaluated under the assumption that one of the branches of possible future developments has materialized. This evaluation is (...) based on the deliberator’s present values, and each decision is judged in relation to the information available when it was taken. The basic decision rule is to choose an alternative that comes out as morally acceptable (permissible) from all hypothetical retrospections. (shrink)

In the first part of the paper, three objections to the precautionary principle are outlined: the principle requires some account of how to balance risks of significant harms; the principle focuses on action and ignores the costs of inaction; and the principle threatens epistemic anarchy. I argue that these objections may overlook two distinctive features of precautionary thought: a suspicion of the value of “full scientific certainty”; and a desire to distinguish environmental doings from allowings. In Section 2, I argue (...) that any simple distinction between environmental doings and allowings is untenable. However, I argue that the appeal of such a distinction can be captured within a relational account of environmental equity. In Section 3 I show how the proposed account of environmental justice can generate a justification for distinctively “precautionary” policy-making. (shrink)

In order to explore the quantifiability and formalizability of uncertainty a wide range of uncertainties are investigated. They are summarized under eight main categories: factual, possibilistic, metadoxastic, agential, interactive, value, structural, and linguistic uncertainty. This includes both classical uncertainty and the uncertainties commonly called great, deep, or radical. For five of the eight types of uncertainty, both quantitative and non-quantitative formalizations are meaningful and available. For one of them (interactive uncertainty), only non-quantitative formalizations seem to be meaningful, and for two (...) (agential and structural uncertainty) neither quantitative nor non-quantitative formalization seems to be a useful approach. (shrink)

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. (shrink)