Paper
17 April 2008 A collaborative eye to the future
Kshanti A. Greene, Terrance Goan, Eugene R Creswick
Author Affiliations +
Abstract
We present a novel approach to predictive situation awareness that leverages human insight to enhance the forecasting abilities of Fusion levels 2 and 3. Existent technologies fail to support predictive and impact modeling under realistic conditions, particularly when there exist few historic exemplars on which to base inferences or when full awareness of the situation includes unobservable elements. We report on our ongoing efforts to develop FutureFusion, a collaborative system that builds predictive awareness and enables futurists to visualize paths to possible futures and formulate predictions on the ultimate outcome of scenarios of interest. FutureFusion's human interpretable knowledge representation is unique in its ability to capture qualitative descriptions of possible futures and quantify them to build computational models. Further, FutureFusion captures both popular consensus as well as high-risk outliers, thereby reducing the potential for surprise. Finally, by efficiently diversifying the modeling process across a heterogeneous and distributed community of experts, this approach avoids the common pitfalls of more traditional modeling approaches. FutureFusion helps to cast light on blindspots, mitigate human biases, and maintain a holistic, up-to-date predictive and impact awareness.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kshanti A. Greene, Terrance Goan, and Eugene R Creswick "A collaborative eye to the future", Proc. SPIE 6968, Signal Processing, Sensor Fusion, and Target Recognition XVII, 696813 (17 April 2008); https://doi.org/10.1117/12.779386
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Mathematical modeling

Visualization

Systems modeling

Eye

Human-machine interfaces

Logic

Process modeling

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