It can feel easier to tell an AI companion something you would hesitate to tell a friend. Suppose a colleague talked over you in a meeting and you have replayed it all afternoon. Telling a friend, you might watch their face, wonder whether they think you are overreacting, and know they may remember it next time your job comes up. Typing the same story into a companion app can feel like skipping that. We have written about the human cues companion apps imitate. Part of the ease may come from what feels missing instead: a listener who could judge you and repeat it.
The audience changes what feels safe
A 2014 experiment by Lucas, Gratch, King, and Morency, published in Computers in Human Behavior, tested whether the perceived listener changes how freely people disclose. Participants completed a health screening with a virtual interviewer. Some were told it ran automatically, and others were told a person was controlling it. The researchers varied that belief separately from whether a human actually operated the system, isolating what people thought they were talking to. Those who believed they were talking to a computer reported less fear of disclosing and less effort to manage the impression they made. They also showed more sadness, and observers rated them more willing to open up.
Everyone talked to the same type of virtual interviewer, a 2014 system that predates current language-model companions. The study measured willingness during one screening interview and reported nothing about privacy or whether disclosing helped anyone later. What it supports is modest: thinking no person is listening can make some people say more.
Feeling heard does not require believing a person is there
A 2018 experiment by Ho, Hancock, and Miner in the Journal of Communication tested whether the label on the listener changes what disclosing does in the moment. Participants shared either emotional or factual material and were told their partner was a person or a chatbot. In every case the partner was a person. Trained research assistants wrote every reply, using validating responses, whatever the participant had been told. Emotional disclosure, compared with factual, produced the immediate reported benefits the researchers measured, and believing the partner was a chatbot did not significantly change those outcomes.
Read that narrowly. It does not show that a real chatbot replies as well as a trained person, and finding no difference is not proof of equivalence. The sample was fewer than a hundred university-affiliated participants, measures were taken right after the chat with no later follow-up, and the study says nothing about therapy or lasting wellbeing. Within those limits, the chatbot label did not erase the immediate benefit of being heard well.
Decide which details the conversation needs
Both experiments were controlled studies, and the newer one is eight years old. A 2026 interview study by Chiu and Foote in the Journal of Computer-Mediated Communication talked with fifteen adults in early 2025, chosen as active and highly engaged companion users, ten of whom mainly used Replika. Interviewees described less worry about gossip or judgment because the companion sat outside their social circle, which echoes the 2014 result. Some of the same people described that comfort while knowing that a company, not the companion, controlled their data. Several used fake names or left out identifying details, and some sounded resigned about privacy. Fifteen interviews cannot say how common any of this is, and interviews are not an audit of what any provider keeps. In these accounts, comfort with the companion and unease about the platform sit together in one person, and people already manage the tension by choosing what to type.
That choice is the part you control. The meeting example above is an invented illustration. Start with what happened and how it felt: someone talked over you, you stayed quiet, and you spent an hour angry at yourself. Try sending that before you add the colleague’s name, the employer, or the follow-up messages. If the reply misses something you care about, add the detail that fills the gap. How much context is enough depends on what you want from the reply, so the table below is our suggested starting point, not a proven anonymization method.
| What you want from the reply | Context that helps | Details to consider leaving out |
|---|---|---|
| To feel less alone about being talked over | That it happened, that you stayed quiet, how you felt afterward | The coworker’s name, the company name |
| To rehearse what you will say tomorrow | What you wish you had said, what you want from the next conversation | Pasted messages or emails, which you can summarize instead |
Leaving names out does not make you anonymous, because a detailed enough situation can identify people on its own. It only means you did not hand the names over directly.
Choosing details does nothing about what you have already sent. Whether an old conversation can be removed is a separate question about what the provider deletes and when, covered in our guide to AI companion privacy and deletion.
Before you send the next personal story, remove one detail the reply does not need.