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UID:calendarize-institutskolloquium-florian-boge-tu-dortmund-inside-the-ch
 inese-library-why-there-still-is-no-strong-claim-to-strong-ai
DTSTAMP:20260407T190748Z
DTSTART:20260429T103000Z
DTEND:20260429T120000Z
SUMMARY:Institutskolloquium: Florian Boge (TU Dortmund) - "Inside the Chin
 ese Library: Why there Still is no Strong Claim to Strong AI"
DESCRIPTION:Modern Machine Learning (ML) models show impressive performanc
 e\, especially when it comes to natural language processing. Should we thu
 s believe that present-day Artificial Intelligence (AI) literally thinks a
 nd understands? To answer this question\, I renovate Searle's famous Chine
 se Room Argument (CRA) in the context of modern ML. I will first argue tha
 t Searle's own extension of the CRA to the context of ML with Artificial N
 eural Networks (ANNs) is flawed. By offering a more careful take on basic 
 ML theory\, I shall then suggest an alternative extension\, called the Chi
 nese Library\, in which almost all of the original intuitions are preserve
 d. Second\, I will highlight some well known issues with Searle's original
  argument\, and formulate a more cautious argument\, to the effect that th
 e total available behavioral evidence for machine understanding is defeate
 d by the applicability of the Chinese Library to modern ML. In essence\, I
  will thus argue that we are still short of evidence that puts us in a pos
 ition to reasonably believe in machine understanding.\nAlle Termine des In
 stitutskolloquiums im SoSe 2026 finden Sie hier.
X-ALT-DESC;FMTTYPE=text/html:<p>Modern Machine Learning (ML) models show i
 mpressive performance\, especially when it comes to natural language proce
 ssing. Should we thus believe that present-day Artificial Intelligence (AI
 ) literally thinks and understands? To answer this question\, I renovate S
 earle's famous Chinese Room Argument (CRA) in the context of modern ML. I 
 will first argue that Searle's own extension of the CRA to the context of 
 ML with Artificial Neural Networks (ANNs) is flawed. By offering a more ca
 reful take on basic ML theory\, I shall then suggest an alternative extens
 ion\, called the Chinese Library\, in which almost all of the original int
 uitions are preserved. Second\, I will highlight some well known issues wi
 th Searle's original argument\, and formulate a more cautious argument\, t
 o the effect that the total available behavioral evidence for machine unde
 rstanding is defeated by the applicability of the Chinese Library to moder
 n ML. In essence\, I will thus argue that we are still short of evidence t
 hat puts us in a position to reasonably believe in machine understanding.<
 /p>\n<p>Alle Termine des Institutskolloquiums im SoSe 2026 finden Sie <a h
 ref="https://www.philosophie.hhu.de/kontakt-und-services/aktuelle-meldunge
 n/newsmeldung/termine-des-institutskolloquiums-im-sose-2026">hier</a>.</p>
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