Researcher wants to get to the heart of causal learning and causal reasoning Published Aug. 4, 2010 By Elizabeth Long 711th Human Performance Wing WRIGHT-PATTERSON AFB -- An expert in cognitive science is leading the way in the study of causal learning and causal reasoning - how people learn about the causal structure of the world, and how they think about the world and understand and explain it in terms of their causal knowledge. Dr. David Danks, associate professor of Philosophy and Psychology at Carnegie Mellon University, and a research scientist at the Institute for Human & Machine Cognition, recently visited Wright-Patterson Air Force Base in Ohio to discuss the issue with Air Force Research Laboratory, 711th Human Performance Wing cognitive scientists and other participants at a recent Human Effectiveness seminar. Dr. Danks says research in the areas of causal learning and causal reasoning is quite underexplored in the scientific community. "I am interested in trying to broaden the scope of our psychological or cognitive models," Dr. Danks explained, "to understand how it is that we can make observations of the world, use them to make decisions, use them to understand and use them to categorize. How is it that we can perform all these different operations in what is a remarkably complicated world, and do them virtually seamlessly?" Dr. Danks argues that graphical models provide a unifying framework for multiple complex cognitive capacities, and many different cognitive capacities can be understood as different operations on shared graphical models. "How is it I can show you a couple examples of things and you will immediately, without even thinking, learn a new category, learn something about the causal structure of the world, and be able to make use of that new knowledge in novel situations?" he said. According to Dr. Danks, cognitive scientists can increase their understanding of how humans think if they increase the scope of research projects instead of narrowing them. "It helps us understand the nature of causal learning when we can talk about it in the same language that we can talk about concept learning," he said. "Now we do not have to draw an artificial distinction between learning concept and learning a causal structure, for example. We do not have to draw an artificial distinction between causal reasoning and decision making." Dr. Danks said the research into causal learning has many useful applications to the military and to society in general. For example, he said, understanding how someone makes a decision can help trainers teach people how to improve their decision-making skills. He added that people are constantly making inferences about others and knowing how we make these inferences can help teams function better. "If you understand how people attribute reasons to other people, you can predict how they are going to behave in various kinds of settings and you can structure the environment to encourage certain kinds of interactions," Dr. Danks said. Another application of the research involves understanding how people develop models of their environment and change those models in light of the evidence they see. "If you want people to make good decisions, especially when they are in stressful situations or in a hostile environment like they could be in the Air Force, it is important to understand how people form hypotheses about what is going on in their environment and how they change or do not change them in light of the evidence," he explained. "If people tend to believe the hypotheses more than they ought to, given the evidence that they have seen, then it would be important in an operational context, to put measures in place to encourage people to move off of those hypotheses or to consider alternative ones. Dr. Danks believes cognitive research serves a noble and necessary purpose. "I think if we better understand how the human mind works, we are a better society," he said.