Editing Openai/6910f719-b034-8006-930d-0d5190a7c617 (section)

===== - A 2024 paper by Emma Borg, LLMs, Turing tests and Chinese rooms: the prospects for meaning in large language models, asks precisely whether the CRA can be extended or must be reinterpreted when considering LLMs. PhilPapers<ref>{{cite web|title=PhilPapers|url=https://philpapers.org/rec/BORLTT-2|publisher=philpapers.org|access-date=2025-11-10}}</ref> =====
* A preprint by Johannes Brinz, The Flashcard Sorter — Applicability of the Chinese Room Argument to Large Language Models (LLMs)?, argues that although LLMs differ from the “Good Old‑Fashioned AI” (GOFAI) the CRA targeted, the core conclusion (that symbol‑manipulation isn’t sufficient for “understanding”) still holds. PhilArchive<ref>{{cite web|title=PhilArchive|url=https://philarchive.org/rec/BRITFS-2|publisher=philarchive.org|access-date=2025-11-10}}</ref>
* A 2025 Forbes article by Gabriel A. Silva, ‘Can AI understand... Says no — but is it right?’ holds the CRA remains relevant given the advanced language capabilities of current systems, even if weakened. Forbes<ref>{{cite web|title=Forbes|url=https://www.forbes.com/sites/gabrielasilva/2025/04/23/can-ai-understand-the-chinese-room-argument-says-no-but-is-it-right/|publisher=forbes.com|date=2025-04-23|access-date=2025-11-10}}</ref>