Think Again: Brain Models to Advance Decision Making

Article excerpt

* When an intelligence analyst is presented with photos taken from a satellite or an unmanned aircraft, he is able to look at the images and piece them together with supplemental data to draw conclusions and make decisions.

But along the way, he may form cognitive biases that cloud his judgment and prevent him from considering other explanations for what he is seeing. Being able to understand and predict when and how that bias might interfere with the analytical process--and finding a way to mitigate it--could improve the accuracy and speed of intelligence information that military commanders ultimately rely upon to make critical decisions.

The Intelligence Advanced Research Projects Agency is funding a multi-year program that aims to build a cognitive neuroscience-based model of the sense-making process--the human ability to draw inferences from data that is sparse, noisy and uncertain. Three teams are working to construct a computational model that represents seven major brain systems interacting to produce that human analytical behavior, said project manager Brad Minnery. Though sense-making has been studied by a number of researchers in the psychology, cognitive science, neuroscience and artificial intelligence fields, the current models tend to be descriptive and non-mathematical, he said. "These models are of limited utility to the intelligence community because they cannot make specific, quantitative predictions as to how analysts will perform on complex sense-making tasks where cognitive bias is likely to be a factor," he explained.

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The program, called ICArUS, or integrated cognitive-neural architectures for understanding sense-making, seeks to develop a different kind of model.

"A sense-making model based on cognitive neuroscience will ultimately prove to have more robust predictive ability, especially when it comes to predicting the quirks and idiosyncrasies of human sense-making, including cognitive bias," Minnery said.

One of the most significant challenges in the program lies in integrating multiple computational models of individual brain systems into a single coherent model, he said. "Historically, most neuroscientists have studied the brain in a piecewise fashion, focusing their efforts on understanding the role that individual brain regions play in individual cognitive functions," he said. "However, sense-making is a multi-faceted phenomenon that encompasses several cognitive skills and that involves multiple brain areas interacting in concert. Achieving this level of functional integration is essential for program success. …