Talking with Language Models
When we interact with large language models (LLMs), are we having a conversation? They are designed to invite us to treat them as intelligent interlocutors who remember, act, and make commitments. But appearances deceive. We introduce the artifactual stance, a framework that reconceives human-AI interaction as artifact-mediated exchanges of candidate texts. LLM outputs are candidate texts optimized for utility, not utterances bearing meaning or force. LLMs are sophisticated text generators, not speakers. Between sessions, nothing runs; between turns, no one remembers. What persists is a configuration and a transcript. The "conversation" is a user's solo performance, interpretive labour di...
| Authors | James Ravi Kirkpatrick, Alexandru Radulescu, Rachel Katharine Sterken |
|---|---|
| Primary category | cs.CY |
| Published | 6 October 2026 |
| Last updated at source | 6 October 2026 |
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