Subaward: Testing the Scenario Hypothesis: The Effect of Alternative Characterizations of Uncertainty on Decision Structuring

DESCRIPTION: There is considerable current interest in decision support that might help improve difficult decisions, such as those that planners make when considering uncertain, long-term environmental changes. Previous research and practice suggests that scenario-based planning processes can help decision makers to restructure decisions by designing additional and adaptive options. This research tests this scenario hypothesis by comparing decisions using decision-support tools that provide forecasts in one of two ways: either by presenting best-estimate probabilities or by presenting alternative scenarios. The hypothesis states that the scenario version will lead to higher probability of a successful restructuring of the decision options. Participants have the challenge of managing a hypothetical fishery. Acting as individuals or in groups, they set a suitable catch-limit policy for a period extending into the future. Participants then use an interactive fisheries model decision-support tool that helps them to evaluate options and to design new ones, while placing reasonable constraints on the options available and their potential performance. Participants are informed that key input data, such as the sustainable yield from the fishery, are the subject of scientific disagreement, resulting in deep uncertainty about the future. The fisheries model will show that a particular adaptive management strategy will, in contrast to other decision options, satisfy the participants' conflicting objectives over a wide range of expectations about sustainable yield and other uncertainties. But the options initially given the participants will not include this adaptive strategy nor will they find it immediately obvious that such a strategy exists. The primary experimental manipulation is whether the decision-support tool organizes information in terms of best-estimate forecasts or in terms of scenarios. The primary outcome measure is the probability of identifying the successful adaptive strategy.

The ability to help decision makers design new and potentially more successful decision options could be a valued aspect of decision support. But much research on decision making and decision support focuses on choice among a fixed set of options, rather than on the design of new options that might reduce difficult tradeoffs. The presence of deep uncertainty - where decision makers may be unsure about contingencies and probabilities - can make it even more difficult to understand or agree on the potential consequences of alternative options, and thus to design new options effectively. The results of these experiments shed light on the social and psychological processes involved in complex, deeply-uncertain policy decisions. The work also informs improvements in decision support methodologies and contributes to ongoing policy discussions regarding the most effective means of conveying deeply uncertain information.

OUTCOMES: 2011-2013: Researchers will conduct experiments on decision-making using a hypothetical scenario example to measure the probability with which the subjects identify the successful adaptive strategy, or make the "correct" decision. The results of the experiments will shed light on the social and psychological processes involved in complex, deeply-uncertain policy decisions.