Judith Fan | Cognitive Tools for Uncovering Useful Abstractions
In the 17th century, the Cartesian coordinate system exposed the unity between algebra and geometry, accelerating the development of the math that took humans to the moon.
It was not just another concept, but a cognitive tool that people could wield to express abstract ideas in visual form. Judith Fan’s lab aims to uncover the psychological mechanisms that explain how people have come to deploy these technologies to learn, share knowledge, and innovate. The first part of this talk will focus on the lab’s recent work investigating drawing, which not only sheds light on how humans perceive and understand the visual world, but also accelerates their ability to communicate useful abstractions. The second part will describe emerging research into how humans discover new abstractions when building physical structures, and externalize these abstractions to support planning and collaboration. This talk will close by noting the implications of embracing such behaviors for advancing theories of human cognition and enhancing real-world impact, including in AI and education.
Related Events
Caroline Meinhardt, Thomas Mullaney, Juan N. Pava, and Diyi Yang | How Can AI Support Language Digitization and Digital Inclusion?
What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
What does digital inclusion look like in the age of AI? Over 6,000 of the world’s 7,000-plus living languages remain digitally disadvantaged.
AI+Science: Accelerating Discovery
AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery.
AI+Science: Accelerating Discovery is an interdisciplinary conference bringing together researchers across physics, mathematics, chemistry, biology, neuroscience, and more to examine how AI is reshaping scientific discovery.
Wolfgang Lehrach | Code World Models for General Game Playing
While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.
While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.