Computers and Cognition

Discovery Core Experience: I&S Course

BCORE 104G: Computers & CognitionB CORE 107

60-Second Syllabus: Computers and Cognition

About This Course: Individuals and Societies Icon

Computers and Cognition Description It seems that human society is on the cusp of a revolution in both our understanding of human thought and our ability to build machines that can match, and maybe exceed, ourselves. But is that really true? How did computers and software arrive at this capability? In this course, we will explore the similarities and differences between computer processing and human cognition, forming a learning community that combines computer science and cognitive psychology for a deeper understanding of both. For decades, these disciplines have informed each other, with early computers inspiring models of human thinking, and now with neuroscience influencing the development of artificial intelligence.  Potential cognitive psychology topics covered include perception (including optical illusions and object identification), memory, judgments and decision making. Computing topics include basic concepts, such as abstraction and representation, and the many varying computational models of cognition through time. We will then combine these two points of view to consider questions such as what do we mean when we say that a person “thinks”, or is “self-aware”, and whether it is even possible for a machine to exhibit these characteristics. Even if we can’t definitively answer these big questions, we will gain an appreciation of our daily automatic tasks such as recognizing a friend or pouring a beverage. Students will learn basic programming concepts and the scientific method.

Why Should I Take This Course? 

Why is it such a struggle for humans to pass an exam that a computer could complete perfectly in a heartbeat? High powered computers can cycle through over 100 billion password guesses in 1 second, yet cutting edge robots still have mixed success opening door handles. How can studying the mind and computers together help us push the boundaries of both? In this interdisciplinary exploration we can tap into some of humanity's deepest questions about consciousness and the electrical energy that creates our reality.

What Will I Study?

We will examine how the mind and the computer perceive, learn, and remember. In doing so, you will learn how to improve your own memory and master foundational computer programming concepts.

Dr. Madeleine Gorges (She/Her/Hers)

School of Interdisciplinary Arts & Sciences

Headshot of Dr. GorgesAbout Dr. Gorges 

Dr. Gorges received a BA from Trinity University in studio art and Spanish. She also took classes at la Universidad Nacional de Cuyo in Mendoza, Argentina, and the University of Washington. After volunteering as a research assistant in neuroscience labs at the University of Washington she joined the Laboratory for the Neural Basis of Bilingualism at the University of Houston. She received her MA and PhD in Developmental, Cognitive, and Behavioral Neuroscience from the University of Houston. Her research interests include bilingualism, creativity, synesthesia, and teaching and learning. She currently enjoys teaching at the University of Washington Bothell and Lake Washington Institute of Technology, where she applies her knowledge of cognitive psychology to create memorable learning experiences.




Dr. Michael Stiber, Ph.D. (He/Him/His)

School of Science, Technology, Engineering & Mathematics

Headshot of Dr. StiberAbout Dr. Stiber: 

Dr. Stiber received a BS in Computer Science, a BS in Electrical Engineering, and an MS and PhD in Computer Science. He was an Assistant Professor in the Department of Computer Science at the Hong Kong University of Science & Technology and a Research Assistant Professor in the Department of Molecular and Cell Biology at the University of California, Berkeley. Dr. Stiber is a frequent visitor to the Department of Biophysical Engineering at Osaka University (Japan). His research interests include: computational neuroscience, biocomputing, neuroinformatics, simulation, scientific computing, neural networks, scientific data management and visualization, autonomous systems, nonlinear dynamics, and complex systems.