This research aims to develop a Linguistic Probability Translator (LPT), initially as a useful research tool and subsequently for use as a decision aid within a communication community (defined as a collection of providers and receivers of risks estimates or forecasts). The LPT will improve the communication of subjective judgments and forecasts from experts to decision makers (DMs), and therefore also improve the resulting decisions. When fully realized, LPT will use quantitative methods based on empirical research to translate from one or many experts' individualized lexicons of uncertainty to a DM's individualized lexicon in a manner that best preserves the intended numerical and non-numerical meanings of the communication. If required, the LPT will translate the phrases into numerical probabilities or probability intervals, or from a numerical forecast into an appropriate phrase in a DM's lexicon. If there are multiple forecasts, LPT could translate each one into the DM's best phrase, or aggregate them and select a single best expression.
The creation of LPT will require basic and applied research, as well as software development. The basic research will focus on issues of measurement and human information processing regarding the formation and communication of uncertain judgements. The software development will focus on the actual construction of LPT, and the applied work will examine the effectiveness and quality of the system. Overall, this research will advance basic theory regarding the measurement and communication of opinion, and will result in a computerized decision aid to improve decision making in the field.