Hot Topic: The Paradox of Artificial Intelligence | September 24

The Paradox of Artificial Intelligence: Smarter than a Grandmaster but More Ignorant than a Toddler

AI has surpassed top human players in games like chess and Go, it can learn from much more data than any human on earth and it sometimes recognizes patterns that elude experts. AI generates and translates texts at lightning speed and is on the verge of matching top radiologists in diagnoses, operating much faster and without fatigue.
However, in other areas, even toddlers outperform AI, especially in common sense, reasoning about cause and effect and learning from just a few examples. Unlike AI systems, children are naturally curious, exploring the world on their own while simultaneously learning within a social and cultural context. The paradox of today’s AI is that what is hard for humans, seems to be easy for machines, and what is hard for machines seems to be easy for humans.
In this Hot Topic panel discussion, leading scientists explore learning in humans and machines from the perspectives of computer science, mathematics and psychology. How do the learning processes of humans and machines differ? What can machines learn from humans, and what can humans learn from machines? What impact will AI systems like ChatGPT have on education in the future? Should we change how we teach math and computer science? How can we harness the advantages of intelligent machines without losing our own skills?

Moderator: Bennie Mols
Bennie Mols is a Dutch freelance science journalist, author and speaker with 25 years of experience who specializes in artificial intelligence and robotics. He has written over 700 popular science articles for various national and international media, including “Communications of the ACM”, and published 13 books, including his most recent one on artificial intelligence: “Slim, slimmer, slimst” (2023 – in Dutch). He holds degrees in Physics and Philosophy and a PhD in Physics.

Celeste Kidd
Associate Professor of Psychology, University of California, Berkeley (USA)

Po Shen Loh
Professor of Mathematics, Carnegie Mellon University (Pittsburgh, USA)

Brigitte Röder
Brigitte Röder (1967) is a Professor of Biological Psychology and Neuropsychology at the University of Hamburg (Germany). She studies how the human brain develops and adapts through learning processes (neuroplasticity) and how this depends on individual experiences. One of her research topics is about sensitive periods in the development of the brain during which children learn particularly easily. Röder uses behavioral and electrophysiological experiments as well as structural and functional magnetic resonance imaging (fMRI). She has won several awards for her research, among them the Gottfried Wilhelm Leibniz Prize in 2014 and the Wilhelm Wundt Medal of the German Psychological Society in 2020.

Eric Schulz
Director of the Institute of Human-Centered AI, Helmholtz Munich (Germany)

The 11th Heidelberg Laureate Forum took place from September 22–27, 2024. #HLF24

The Heidelberg Laureate Forum (HLF) is an annual networking conference where 200 carefully selected young researchers in mathematics and computer science spend a week interacting with the laureates of the most prestigious awards in their disciplines: the Abel Prize, ACM A.M. Turing Award, ACM Prize in Computing, Fields Medal, IMU Abacus Medal and Nevanlinna Prize.

The opinions expressed in the videos do not necessarily reflect the views of the Heidelberg Laureate Forum Foundation or any other person or associated institution involved in the making and distribution of these videos.

More information on the Heidelberg Laureate Forum: https://www.heidelberg-laureate-forum.org/

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