Anchoring and Adjustment in Uncertain Spatial Trajectory Prediction. (March 2019)

• Record Type: Journal Article
• Authors: Herdener, Nathan; Clegg, Benjamin A.; Wickens, Christopher D.; Smith, C. A. P.
• Is Part Of: Human factors. Volume 61:Number 2(2019)
• Page Start: 255
• Page End: 272
• Publication Date: 2019-03
• Subjects: decision making -- uncertainty -- spatial prediction -- cognitive bias -- workload; Human engineering -- Periodicals; 620.82
• DOI: 10.1177/0018720818800591
• Languages: English
• ISSNs: 0018-7208

Abstract

Objective: The aim of this study was to explore the impact of prior information on spatial prediction and understanding of variability. Background: In uncertain spatial prediction tasks, such as hurricane forecasting or planning search-and-rescue operations, decision makers must consider the most likely case and the distribution of possible outcomes. Base performance on these tasks is varied (and in the case of understanding the distribution, often poor). Humans must update mental models and predictions with new information, sometimes under cognitive workload. Method: In a spatial-trajectory prediction task, participants were anchored on accurate or inaccurate information, or not anchored, regarding the future behavior of an object (both average behavior and the variability). Subsequently, they predicted an object's future location and estimated its likelihood at multiple locations. In a second experiment, participants repeated the process under varying levels of external cognitive workload. Results: Anchoring influenced understanding of most likely predicted location, with fairly rapid adjustment following inaccurate anchors. Increasing workload resulted in decreased overall performance and an impact on the adjustment component of the task. Overconfidence was present in all conditions. Conclusion: Prior information exerted short-term influence on spatial predictions. Cognitive load impaired users' ability to effectively adjust to new information. Accurate graphical anchors did not improve user understanding of variability. Application: Prior briefings or forecasts about spatiotemporal trajectories affect decisions even in the face of initial contradictory information. To best support spatial prediction tasks, efforts also need to be made to separate extraneous load-causing tasks from the process of integrating new information. Implications are discussed.