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DTSTART;TZID=Europe/Berlin:20260618T160000
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CREATED:20260529T130501Z
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UID:28134-1781798400-1781803800@www.scienceofintelligence.de
SUMMARY:Martin Korth (Universität Münster)\, “Five philosophical problems that most likely matter for the science of intelligence”
DESCRIPTION:Sub-symbolic deep neural network based artificial intelligence (AI) systems run into all sorts of problems\, especially with hallucinations and in general with reliability. One way to conceptualize this is to understand sub-symbolic AI to lack proper world models\, i.e. some type of mapping of what’s supposedly real and what’s not — though it might be more helpful to concede that such AI systems have fuzzy implicit world models\, that are superpositions of all proper world models compatible with the statistics of the language token use in the training data. Understood in one of these ways\, it is tempting to think that the problems of these models can be solved by adding proper world model information\, only that the generation and operation of open\, extended world models is exactly the task at which classical symbolic AI approaches failed. Combined sub-symbolic and symbolic approaches (like neuro-symbolic AI or similar) are thus most likely doomed to run not only into some of the problems of both sub-symbolic and symbolic systems\, but even into additional problems related to the interfacing of the two. For this interfacing\, no generally applicable approach is known yet and given that (even after at least decades of research) our knowledge of how humans generate or access (layers of) symbol systems and world models is very limited\, it seems at least questionable that substantial progress will be made with this in the near future. I will discuss five well-established philosophical problems related to the generation and handling of world models: The symbol grounding problem of the unclear connection between data and meaning\, the framing problem of the unclear implementation of commonsense knowledge and know-how\, the hard problem of phenomenological experience\, the problem of how (broad and stable) abstraction works\, and the problem of (especially also the biological implementation of) universals. \nMartin Korth studied chemistry\, philosophy\, literature\, history\, and psychology in Münster and Hagen. He earned doctorates in theoretical chemistry and philosophy. Postdoctoral fellowships took him to Prague\, Cambridge (UK)\, and the Max Planck Institute for Coal Research in Mülheim. He then served as a Juniorprofessor for theoretical chemistry at the University of Ulm. He founded a startup in the field of artificial intelligence for electrochemical energy storage. He is currently the scientific director of the IT Department of the Natural Sciences at the University of Münster. \nImage created with DALL.E by Maria Ott.
URL:https://www.scienceofintelligence.de/event/martin-korth-universitat-munster-five-philosophical-problems-that-most-likely-matter-for-the-science-of-intelligence/
LOCATION:Marchstraße 23\, 10587 Berlin\, Room 2.057
CATEGORIES:Guest Lecture
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