Welcome to the Thinking About Thinking [TAT] blog sponsored by the Computation and Cognition lab at New York University. We spend most of our time thinking about how people think, learn, and decide, and we wanted to share some of our musing with the Internet.

Why us? We get paid everyday to learn about human cognition and to pursue research in this area (pretty sweet gig, eh?). While there are a large number of excellent blogs devoted to cognitive science, we hope that our contributions can be a useful resource for students, teachers, researchers, and the general public looking to learn more about the cognitive sciences (i.e., artificial intelligence/machine learning/psychology/linguistics/developmental psychology/neuroscience/etc). What makes our blog different from all these great existing online resources perhaps remains to be seen, but we have it in mind to provide accessible reviews of cutting-edge peer-reviewed research with an eye to the relevance of cognitive science to everyday life. The additional advantage (for us at least) is that it forces us to digest, engage, and keep on top of the work in our area!

Who are we? “We” is the Computation and Cognition lab at New York University under the direction of Todd M. Gureckis. The “we” is grad students and researchers, undergraduate students, and other guests who plan to contribute stories and articles for the lab.

What do we do? Our lab studies human cognition (in particular human learning). The name of our lab is “computation and cognition” which reflect the two main strands that inform our work. Principally, we attempt to understand the nature of human cognition by developing computational theories of human information processing. What is a computational theory? Well, basically, it means we believe that the human mind can be productively understood as a information processing device similar to your laptop or computer. The question then is what is the “software” that the brain runs (i.e., what algorithms do people’s brains use to solve particular tasks/problems?). In our research, we propose and test various computational algorithms as candidate theories of how people think. By comparing the operation formal models and the behavior of humans, we can gain precise, scientific insight into how people perceive their environment, solve problems, and adapt their behavior. In addition, insights from these models can inform the development of artificial systems capable of learning on their own (such as in machine learning or artificial intelligence systems). You can read more about our lab here (a collection of peer-reviewed research papers are here).

What next? Thanks for tuning in, and please stick around and join us for some good old fashioned internet debates and discussions about Cognitive Science!