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The Precautionary Principle and Expert Disagreement.
1Institute of Philosophy/INCET, Jagiellonian University in Kraków, Grodzka 52, 31-044 Kraków, Poland.
Erkenntnis
|September 27, 2021
Summary
The Precautionary Principle, often seen as a harm-prevention rule, may be better understood as an epistemic guide for belief formation. This research proposes a probabilistic approach to combining expert opinions, enhancing the ecumenical principle.
Area of Science:
- Philosophy of Science
- Decision Theory
- Risk Assessment
Background:
- The Precautionary Principle is traditionally viewed as a decision rule for harm prevention.
- Martin Peterson proposed an epistemic interpretation, emphasizing belief formation over action selection.
- Peterson introduced the ecumenical principle, advocating consideration of all expert views in precautionary appraisals.
Purpose of the Study:
- To challenge Peterson's exclusion of probabilistic rules in precautionary reasoning.
- To propose a probabilistic framework for combining expert opinions under the ecumenical principle.
- To demonstrate how a broader conception of probability can overcome criticisms of combining expert views.
Main Methods:
- Philosophical analysis of the Precautionary Principle and epistemic rules.
- Critique of Martin Peterson's arguments regarding probabilistic rules and expert disagreement.
- Development of a probabilistic rule for combining expert opinions consistent with the ecumenical principle.
Main Results:
- Peterson's epistemic view of the Precautionary Principle is re-examined.
- A probabilistic rule for combining expert opinions is presented as compatible with the ecumenical principle.
- This probabilistic rule is shown to be robust against criticisms regarding precision and warranted information.
Conclusions:
- The Precautionary Principle can be effectively guided by epistemic rules that incorporate probabilistic methods.
- Combining expert opinions through a broader probabilistic conception strengthens the ecumenical principle.
- This approach offers a more nuanced and comprehensive framework for precautionary decision-making under uncertainty.
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