Questioning the science in risk assessment
The so-called scientific or quantitative approach to health risk assessment aims to produce the best possible numerical estimates of the chance or probability of adverse health outcomes for use in policy-making. Although high credibility is usually given to this approach, how valid is this assumption? Why is this approach often seen as more valid than the judgements made by the public or social scientists?
Although risk assessment appears to follow a scientifically logical sequence, in practice there are considerable difficulties in making "objective" decisions at each step in the calculations. Thus the risk modeller has to adopt a specific definition of risk and needs to introduce into the model a series of more subjective judgements and assumptions (3,4). Many of these include implicit and subjective values, such as the numerical expression for risk, weighting the value of life at different ages, the discount rates and choice of adverse health outcomes to be included. For instance, scientific judgements may be needed on the effects of different levels of exposure or which outcomes to include, particularly which disease episodes should be counted among the adverse events.
During the 1980s, scientific predictions were seen to be rational, objective and valid, while public perceptions were believed to be largely subjective, ill-informed and, therefore, less valid. This led to risk control policies that attempted to "correct" and "educate" the public in the more valid scientific notions of risk and risk management. However, this approach was increasingly challenged by public interest and pressure groups, which asked scientists to explain their methods and assumptions. These critical challenges often revealed the high levels of scientific uncertainty that were inherent in many calculations. Such groups then became more confident, enabling them to argue strongly for the validity of their own assessments and interpretation of risks.