MTS is the department’s Mind, Technology, and Society speaker series. It is hosted by a different faculty member each semester. Founded by a generous gift from Professors Robert Glushko and Pamela Samuelson, MTS brings researchers and industry professionals from across the globe to present a variety of interdisciplinary work in cognitive science. See our UCMerced CogSci youtube channel for videos of past MTS talks!
CIS graduate students, faculty, and staff, and all who are interested are invited! Members of other departments at UC Merced as well as the general public are encouraged to attend. (Note: current CIS Ph.D. students are required to attend MTS each semester in residence, to fulfill their COGS 250 course requirement).
Dr. Dubova's talk will be 3-4:30pm in COB 265, presenting on "Cognitive Mechanisms of Discovery".
Abstract:
To understand and navigate our world, both individuals and scientific communities create simplifying representations, such as concepts and theories. How do we construct useful representations from our experiences, and how do we use these representations to guide our learning? In this talk, I discuss empirical research on the mechanisms of human concept learning, highlighting the ease with which we adopt new, even arbitrary, conceptualizations. I illustrate how these acquired concepts instantly shape how we perceive and explore the world. For example, I show that our perception of objects becomes biased by our conceptual needs and our knowledge about these objects. I demonstrate that similar mechanisms are at play when scientific conceptualizations, such as the DSM in psychology and the periodic table in chemistry, guide scientific exploration. Then, I discuss the double-edged nature of theory-guided discovery—although conceptualizations can efficiently steer us towards new experiences that further refine our knowledge, they can also lead our exploration astray. I present a computational model of scientific discovery in which agents conduct experiments, build theories, and share results to advance collective understanding of the world. The model reveals that when new experiments are guided by existing theoretical frameworks, scientific communities risk missing important aspects of the world not yet captured by their theories. I conclude by reviewing some of my current and future research that integrates cognitive psychology, machine learning, and philosophy of science to enhance our understanding of how theories and observations can inform each other to support—rather than hinder—human learning and scientific progress.
For more information or to sign up for email announcements, please contact the talk series organizer: cis-mts-lead@lists.ucmerced.edu.
