Decision Analysis In Political Science: The Problem With The Uncertainty Principle

Abstract

Decision analysis is considered to be one of the most important research methods in political science. The problem, however, is to determine to what extent such analysis can be reliable. The application of classical decision theory, referring to statistical research and probability theory, to the assessment of the political decision-making process is usually inadequate. This results, among other things, from the inability to obtain reliable knowledge about the initial state of the decision and the state of nature, differences in the perspectives of the assessing entities, differences in short- and long-term priorities, and above all, the impossibility of achieving several goals at the same time due to their mutual exclusion. These difficulties are generalized by the ‘uncertainty principle,’ analogous to the Heisenberg equation: the more certain priorities are realized, the less it is possible to realize others. Similarly, the use of some paths of justification excludes others in the real decision-making process. What can serve as a useful procedure, however, is the ‘expansion of time horizons,’ i.e. the gradual distancing of the time perspective of benefits.