Cost–benefit analysis (CBA) is much more philosophically interesting than has in general been recognized. Since it is the only well-developed form of applied consequentialism, it is a testing-ground for consequentialism and for the counterfactual analysis that it requires. Ten classes of philosophical problems that affect the practical performance of cost–benefit analysis are investigated: topic selection, dependence on the decision perspective, dangers of super synopticism and undue centralization, prediction problems, the indeterminateness of our control over future decisions, the need to exclude (...) certain consequences for moral reasons, bias in the delimitation of consequences, incommensurability of consequences, difficulties in defending the essential requirement of transferability across contexts, and the normatively questionable but equally essential assumption of interpersonal compensability. (Published Online July 31 2007). (shrink)

Clear-cut cases of decision-making under risk (known probabilities) are unusual in real life. The gambler’s decisions at the roulette table are as close as we can get to this type of decision-making. In contrast, decision-making under uncertainty (unknown probabilities) can be exemplified by a decision whether to enter a jungle that may contain unknown dangers. Life is usually more like an expedition into an unknown jungle than a visit to the casino. Nevertheless, it is common in decision-supporting disciplines to proceed (...) as if reasonably reliable probability estimates were available for all possible outcomes, i.e. as if the prevailing epistemic conditions were analogous to those of gambling at the roulette table. This mistake can be called the tuxedo fallacy . It is argued that traditional engineering practices such as safety factors and multiple safety barriers avoid this fallacy and that they therefore manage uncertainty better than probabilistic risk analysis (PRA). PRA is a useful tool, but it must be supplemented with other methods in order not to limit the analysis to dangers that can be assigned meaningful probability estimates. (shrink)