What is a Discourse Graph?
Lines of inquiry this paper opens 24
Research framings built by reading the notes related to this paper — the questions it feeds into.
Can language models reason beyond surface pattern matching? Can readers reliably distinguish AI-written text from human writing?- What changes when published text was never written for its readers?
- How does the author-function itself change when AI replaces human authorship?
- Why does production time matter to the meaning of generated text?
- Why does AI writing seem more competent and informative than human writing?
- What signals of individual identity become unreliable in AI-assisted text?
- What structural difference exists between AI posts and human conversational writing?
- Does AI writing erase markers of non-native English speaker identity?
- What makes readers treat AI-generated text as authoritative?
- What specific distortions does AI writing assistance introduce into text?
- Why does AI text enter human reading circuits despite structural disruption?
- What properties of natural text does artificial text actually eliminate?
- How can structurally different text produce equivalent real-world effects?
- Why does AI-generated content feel flat compared to human commentary?
- What happens to rhetoric and ethos when the speaker is absent?
- How does AI speech differ from broadcast speech in its carrier structure?
- What makes AI posts less likely to invite replies than human-written content?
- How does the post register specifically displace human influencer content on social media?
- What interventions beyond writer revision could reduce AI distortion in published content?
- What happens when writers lose the three-party audience structure in AI?