An important part of this concept is that observation cannot be prior to theory, as one must have a theory in order to decide what to observe Popper Hence, science begins with a problem, not an attempt to solve the problem, and the sources of scientific problems are attempts to solve prior problems. Problem Formulation An important consequence of Popper's conceptual model for scientific risk assessment is that the assessment should begin by defining the problem P 1 , not by collecting data EE.
Problem definition normally begins with the objectives of the laws under which the proposed action is regulated; these "management objectives" are usually general statements about protection of the environment, although endangered species legislation may specify species and habitats to be protected. To allow a scientific determination of risk, specific targets for protection, called assessment endpoints, must be derived from the management objectives. The assessment should comprise an entity e.
For example in the UK, the management objective of conserving biodiversity is represented by an assessment endpoint of an index of the population sizes of bird species common on farmland Gregory et al. Usually it is not possible or desirable to measure directly the risk of a proposed action to the assessment endpoints.
Instead a conceptual model that links the proposed action to the assessment endpoint is developed, and from this model specific "risk hypotheses" are derived.
These hypotheses correspond to the trial solution part of Popper's model. Because scientific knowledge derives from tests of hypotheses, not from proofs of hypotheses, it is not possible to prove that an action presents no risk to the assessment endpoints.
It is possible, however, to attain high confidence that an action presents low risk "is safe" by rigorous tests of risk hypotheses. For example, a conceptual model may suggest that the use of a chemical presents low risk to the abundance of an endangered species because the species will not be exposed the chemical.
The risk hypothesis derived from this model is that the concentration of the chemical in the habitat of the endangered species is not significantly different from zero or from a value that is "in effect zero" for the purposes of assessing risk. The hypothesis could be tested by mathematical modelling of the dispersal of the chemical under the proposed use, and confidence in the risk assessment could be increased by making conservative assumptions about the values of parameters in the model.
GM food approval in Australia
If the risk hypothesis is not falsified after testing under highly conservative conditions, there is high confidence that the use of the chemical presents negligible risk to the endangered species Raybould The derivation of risk hypotheses is called problem formulation, and is an essential, but often neglected aspect of risk assessments for the cultivation of GM crops. By erecting specific hypotheses to be tested, problem formulation identifies requirements for data. Without hypothesis testing, there is no method to identify data requirements because risk assessment will proceed on the flawed assumption that safety can be proved by the accumulation of data that show no effect.
Collection of additional data could always be justified because it would provide "more evidence to prove safety".
Safety Assessment of Genetically Modified Foods
Hypothesis testing provides a clear criterion to judge the value of additional data: unless the additional data offer a more rigorous test of the risk hypothesis than existing data, and thereby increase certainty of the risk assessment, they are superfluous Raybould If the introduction of environmentally beneficial products is delayed while superfluous data are collected, environmental risk is increased Cross If delay can increase risk, no study can be free from risk, and requirements for data to assess the risk of an action must be balanced with the loss of potential benefits of that action while the data are collected.
Therefore to minimise environmental risk, problem formulation should devise risk hypotheses that can be rigorously tested with the minimum need to acquire additional data Raybould Risk Characterisation The testing of risk hypotheses is called risk characterisation, and corresponds to the error elimination part of Popper's scheme. Hypotheses are tested by comparing their predictions with observations. For a hypothesis to be scientific it must be possible to falsify it; a hypothesis that predicts every possible outcome of a test is not scientific Popper It follows that good scientific theories make specific predictions, and rigorous tests of theories attempt to create conditions under which the theory is most likely to fail.
The logic of risk characterisation under Popper's model is that a specific hypothesis should be formulated such that if it is not falsified, further risk characterisation would be unproductive. To build confidence that risk characterisation can stop, tests of the hypothesis should create conditions under which the hypothesis is most likely to fail. If the hypothesis is not falsified under those conditions, testing can stop and the risk assessment be completed.
Safety Assessment of Genetically Modified Foods
Hence risk assessment should seek to assess risk initially under "worst-case" conditions, and if the risk is minimal, no further data should be required. If the risk hypothesis is falsified, a new hypothesis is formulated P 2 under Popper's scheme and further characterisation of the risk is made under more realistic conditions.
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Popper's conceptual model shows that the development of scientific knowledge is continuous; knowledge acquired after a trial solution and error elimination presents new problems for which trial solutions are proposed. The same applies to risk assessment. No amount of corroborative data can prove a risk hypothesis. Also, new information may falsify theories on which the initial problem formulation was based, and therefore a different risk hypothesis should be tested to give sufficient certainty that the proposed action poses no unacceptable risks.
Genetically Modified Plants
The best that risk assessment can achieve is high confidence of minimal risk given present knowledge. The decision to stop risk characterisation is therefore a judgement that further testing will not increase knowledge of risk significantly, and hence effort is better spent increasing knowledge of a different problem. Decision making Characterization of risk is not a decision to permit or forbid a proposed action. The results of the risk assessment must be evaluated along with any societal concerns that fall outside the risk assessment; this evaluation is risk analysis.
Confusion between risk assessment and risk analysis is part of the reason for controversy about role of science in making decisions about the use of new technology. Non-scientific concerns about scientific advances have become confounded with scientific estimates of risk. This leads to "debates" about science, when what is really being debated is the weight that should be given to scientific assessments relative to other concerns about public policy when making decisions Johnson et al.
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This article in AJ Vol. Heidi F.
Abstract Following the production of the first transgenic plants, health issues concerning the safety of using genetically modified GM crops in foods and feeds have been discussed, debated, and evaluated. Search Publications Advanced Search. Member Login Email Address. Create Account.