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).

Next Event

Thursday, October 16, 2025

10:00 am EST (Eastern Standard Time, US)

15:00 UTC (Universal Coordinated Time)

16:00 CET (Central European Time)

23:00 JST (Japan Standard Time)

Denis Mareschal

Birkbeck College, United Kingdom

"The challenges and rewards of pursuing real-world Developmental Science"

Abstract

Historically, the understanding of the brain-based mechanisms of learning in young children has relied on well-controlled lab-based experiments. This was for good scientific reasons. First, there was a drive to isolate individual causes of behaviours and therefore to carefully control the environments in which children behaved during a study. Moreover, the equipment required to assess the neural correlates of behaviours were cumbersome and difficult to move so children's mobility had to be restricted. Recent developments in wearable and wifi-enhanced technologies have now allowed us to literally "untether" children and explore their brain and behaviour as they move around and interact naturally. This has opened new avenues for research, but has equally revealed important new challenges to the way that we approach developmental sciences. In this seminar, I will draw on my lab's recent work on children's sensory cue integration, neural synchrony during children's collaborative problem solving and  the trials and tribulations of translating basic cognitive neuroscience research into real-world effective classroom interventions to highlight some of the challenges that contemporary developmental sciences faces.

Short Bio

Professor Denis Mareschal is Director of the Centre for Brain and  Cognitive Development, at Birkbeck University of London, and a founding member of the Centre for Educational  Neuroscience. After completing a BA in Natural Science at Cambridge, he moved on to studying learning -- initially in the form of an MA in Psychology and Artificial Intelligence at McGill in Montreal, Canada and then through completing a DPhil in Psychology at Oxford. Professor Mareschal's research has focussed on identifying the mechanisms of learning and development in infancy and childhood through the combined use of behavioural studies, computational modelling and neuroimaging. He has received a number of awards for his work, including the Marr Prize from the Cognitive Science Society, the Young Investigator Award from the International Congress on Infant Studies and the Margaret Donaldson Prize  from the BPS Developmental Section. Over the last 10 years he has led the UnLocke project (Unlocke.org) developing a neuroscience-based primary school maths and science education intervention. He is committed to taking neuroscience out of the lab and into the real-world, in terms of primary research and in terms of translational impact.

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Upcoming Events

• 2025-10-16: Denis Mareschal, Birkbeck College, University of London, UK

• 2025-11-13: Tadahiro Taniguchi, Kyoto University, Japan

• 2025-12-04: Jenny Saffran, University of Wisconsin-Madison, USA

Previous Events

• 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

If you like our talks, also check out the keynote lectures from the 2022 ICDL conference!

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