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arXiv AI By S. F. M. van Vlijmen, H. D. Lethe jr

Some hypotheses on how chatbots work in problem-solution-driven conversations: Large Language Models as confirmation of the Innovation Illusion

Read the original on arXiv AI →

The article examines chatbots as partners in problem‑solving conversations, arguing that basic chatbots—comprising a large language model (LLM) and a simple interface—are multifaceted but cannot match human cognitive flexibility. Drawing on Aggregation Dynamics, Cognitive Linguistics, Neuropsychology, and Psychology, the authors describe how LLMs encode artificial metaphorical problem propagations from training data, which only partially imitate human thinking. They conclude that further LLM development will not yield true thinking partners, yet chatbots are widely used, making their understanding socially and politically important.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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