Papers › AI Does Not Alter Perceptions of Text Messages
AI Does Not Alter Perceptions of Text Messages
N'yoma Diamond
For many people, anxiety, depression, and other social and mental factors can make composing text messages an active challenge. To remedy this problem, large language models (LLMs) may yet prove to be the perfect tool to assist users that would otherwise find texting difficult or stressful. However, despite rapid uptake in LLM usage, considerations for their assistive usage in text message composition have not been explored. A primary concern regarding LLM usage is that poor public sentiment regarding AI introduces the possibility that its usage may harm perceptions of AI-assisted text messages, making usage counter-productive. To (in)validate this possibility, we explore how the belief that a text message did or did not receive AI assistance in composition alters its perceived tone, clarity, and ability to convey intent. In this study, we survey the perceptions of 26 participants on 18 randomly labeled pre-composed text messages. In analyzing the participants' ratings of message tone, clarity, and ability to convey intent, we find that there is no statistically significant evidence that the belief that AI is utilized alters recipient perceptions. This provides hopeful evidence that LLM-based text message composition assistance can be implemented without the risk of counter-productive outcomes.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections