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.