assessor to provide a risk estimate when a decision needs to be made in the presence of some uncertainty. The assessor can use a standard default to extrapolate when there is little or no scientific information available to indicate what the shape of the dose–response curve is in the low-dose region for a carcinogen; the default in this case would be a linear, no-threshold model. Second, defaults are typically protective of health. EPA originally selected the linear, no-threshold default as a “conservative” or “health-protective” policy choice because it assumes that there is no dose below which risks are not increased. It is likely to generate the highest, or upper-bound, risk estimate consistent with the data; the actual risk almost certainly will not exceed the upper bound and will likely fall below it. Third, it can provide decision makers with a single, upper-bound point estimate, while acknowledging the uncertainty in that point estimate by indicating that the actual risk could fall anywhere between zero and that upper bound. If that upper bound is itself in the negligible risk range, the uncertainty statement allows the decision maker to assert that any actual risks are likely to be below the negligible range. Fourth, the use of a single point estimate and defaults allows for a simpler risk-communication message.
Using defaults to deal with uncertainty does, however, have a number of deficiencies, and that use has been the subject of much discussion and debate in the scientific literature (NRC, 1994, 2006, 2009). Defaults have been criticized for their lack of an adequate scientific basis. For example, the National Research Council (NRC) criticized EPA’s use of defaults in its dioxin risk assessment, in one instance stating that EPA’s use of the “default linear model lacked adequate scientific support” (NRC, 2006). In addition, if the fact that they are used and the implications of their use are not communicated with a risk estimate, they can mask the uncertainty, providing a sense of uncertainty that is inaccurate. The use of defaults has also been criticized for being overly conservative; that is, the regulatory standards that are based on defaults are more restrictive than necessary to protect public health. If, as with the linear, no-threshold default, most of the defaults in risk assessments are selected because they are conservative (that is, protective of health and resulting in lower permissible exposures or emissions), very little can be said about exactly how much uncertainty is associated with their cumulative use. Indeed, even in the case of the example of the upper-bound estimate yielded by the use of the linear, no-threshold default, there remain significant questions about how much greater the upper bound is than the true risk and whether the differences are at all consistent across different risk assessments—that is, whether there is any basis for believing that the upper-bound estimate for one substance has the same relation to the “true” risk as it does for another substance. As discussed below, these and other criticisms have led to suggestions for alternative ways to treat the problems of uncertainty in risk assessment.