In 1950, Alan Turing asked "Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's?" Today, 75 years later, constructing a computer program that can learn like a child and that develops a human-like general intelligence and consciousness is still considered a grand, if not the ultimate, challenge for artificial intelligence (AI). An interdisciplinary community of scientists from AI, Cognitive Science, Psychology, Engineering, and Neuroscience are tackling this grand challenge. In the Developing Minds global lecture series we showcase the progress being made. It is organized by the Developmental AI Task Force of the IEEE Technical Committee on Cognitive and Developmental Systems of the IEEE Computational Intelligence Society. See also: IEEE Int. Conference on Development and Learning (ICDL), IEEE Transactions on Cognitive and Developmental Systems (TCDS). If you enjoy this lecture series, you may also enjoy the keynote lectures and all oral presentations from the last ICDL conference.

Next Event

Thursday, October 15, 2026

09:00 am EDT (Eastern Daylight Time, USA)

13:00 UTC (Universal Coordinated Time)

15:00 CEST (Central European Summer Time)

22:00 JST  (Japan Standard Time)

Zoom link:

https://uni-frankfurt.zoom-x.de/j/69608764770?pwd=gOHzVZ5y86Ic0MZFik6khLk0mF4FjO.1

Meeting-ID: 696 0876 4770

Code: 401171

Michael H. Goldstein

Cornell Universtiy, USA

"Mechanisms of socially guided vocal learning in human infants and songbirds: Connecting contingency to curiosity-driven learning"

Abstract

The ability to learn a vocal repertoire is a rare phenomenon, emerging in only a handful of groups, including humans and songbirds. A key parallel in the vocal development of certain songbirds and human babies is the social function of immature vocalizations. The form and timing of adult-infant interactions facilitate real-time vocal learning and have strong influences on the development of mature birdsong and language. Specifically, contingent responses of adults to the plastic song of birds and the babbling of babies have strong influences on learning. What makes contingency effective? We will examine curiosity-driven learning (CDL) as a framework for a mechanistic understanding of learning from contingent social interactions. In CDL, intrinsic reward is generated by changes in the predictability of social interactions as a function of immature vocal behavior. We will discuss several tests of this idea at the behavioral and neural levels in songbirds and human infants.  Taken together, my studies indicate that temporal characteristics of social interaction are rewarding to young songbirds and human infants, and reward pathways may drive learning in social contexts.

Short Bio

Michael Goldstein is a Professor of Psychology and a Stephen H. Weiss Presidential Fellow at Cornell University. He received his PhD in developmental psychology and animal behavior from Indiana University. Michael studies the development and evolution of vocal communication and social learning. He takes a comparative approach, investigating vocal communication and social development in human infants and songbirds. His research on the developmental processes by which knowledge of speech and song are acquired has revealed new mechanisms by which the social environment influences the learning of species-typical adaptive skills. By studying social interaction and learning as it occurs in moment-to-moment interactions between infants and social partners, Michael’s research connects our knowledge of social influences on developmental outcomes with specific processes of learning. A major finding from his work is that immature vocal behavior, such as babbling in humans and plastic song in songbirds, has crucial functional significance for learning, but only when studied in a social context.  Michael received the David Kucharski Young Investigator Award from the International Society for Developmental Psychobiology and the Distinguished Early Career Contribution Award from the International Society on Infant Studies. His research has been supported by grants from NICHD and NSF. 

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Upcoming Events

• 2026-10-15: Michael H. Goldstein, Cornell Univ., USA

Previous Events

• 2026-10-01: Jun Tani, "From Embodied Language Grounding to Systematic Generalization: Developmental Origins of Compositionality in Robots".  Video

• 2026-06-25: Andrew Barto, "Rediscovering Reinforcement Learning". Video

• 2026-04-02: Lisa Oakes, "Learning to look and looking to learn: Developmental cascades in infant attention". Video

• 2025-12-04: Jenny Saffran, "Learning to understand: Statistical learning and language development". Video

• 2025-11-13: Tadahiro Taniguchi, "Developing Collective Minds: Symbol Emergence and Co-creative Learning via Collective Predictive Coding". Video

• 2025-10-16: Denis Mareschal, "The challenges and rewards of pursuing real-world Developmental Science". Video

• 2025-09-25: Uri Hasson,  "Developing cognitively feasible learning agents that can acquire language like children through real-life experiences". Video not yet available.

• 2024-12-12: Daniel Messinger, "Does Interaction Drive Development? Lessons from infant emotion, autism, and preschool language". Video

• 2024-11-12: Justin N. Wood, "Radical empiricism: The origins of knowledge as a mini-evolution". Video

• 2024-04-18: Sabine Hunnius, "Early cognitive development: Five lessons from infant learning". Video

• 2024-01-24: Caroline Rowland, "What predicts how quickly children learn language?" Video

• 2023-11-30: Brenden Lake, "Addressing two classic debates in cognitive science with deep learning". Video

• 2023-06-28: Angelo Cangelosi, "Developmental Robotics for Language Learning, Trust and Theory of Mind". Video

• 2023-04-27: Karl Friston, "Active Inference and Artificial Curiosity". Video

• 2023-03-02: Masashi Sugiyama, "Theory and Algorithm towards Reliable Machine Learning". Video

• 2022-12-08: Karen E. Adolph, "Development of intelligent behavior: Lessons from Infants". Video

• 2022-11-17: Gary Marcus, "Towards a Proper Foundation for Robust Artificial Intelligence". Video

• 2022-07-28: Sergey Levine, UC Berkeley, "From Reinforcement Learning to Embodied Learning". Video

• 2022-06-01: Susan Goldin-Meadow, U. of Chicago, "The Mind Hidden in Our Hands". Video

• 2022-03-31 : Atsushi Iriki, Riken, "Self-in-the-world map evolved in the primate brain as a basis of civilized Homo sapiens". Video

• 2022-01-27: Josh Tenenbaum, MIT, "Reverse Engineering Human Cognitive Development: What do we start with, and how do we learn the rest?". Video

• 2021-11-11: Linda B. Smith, Indiana University, "Babies, bodies, brains and machines". Video  

• 2021-09-30: Pierre-Yves Oudeyer, INRIA, "Developmental Artificial Intelligence: machines that learn like children and help children learn better".  Video

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