Why "Self-Generated Learning" May Be More Radical and Consequential Than First Appears

Explore the concept of "Self-Generated Learning" and its potentially radical implications in this 39-minute conference talk by Linda Smith, Distinguished Professor and Chancellor's Professor of Psychological and Brain Sciences at Indiana University, Bloomington. Delve into the workings of the mind, examining data on faces vs. hands and the importance of head stability in learning. Investigate highly biased views and complex dynamic systems, analyzing series of events, cross-recurrence, and predictive relations. Gain insights into what generates learning and the role of working memory. Discover how this research connects to embodied, situated, and grounded intelligence, with potential implications for AI development.

Introduction
The Mind
What I Do
Data
Faces vs Hands
Why is this important
Experiments
Head Stability
Highly Biased Views
Complex Dynamic Systems
Series of Events
CrossRecurrence
Predictive Relations
Example of Predictive Relations
What is Generating
What is Working Memory