Did some people dislike warm, friendly AI simply because they'd chatted with bots so much that the charm wore off?

This explores whether how often someone uses AI could explain why warm, companion-style AI behavior went over badly with some human evaluators. The corpus has no note that measures rater usage frequency against their reactions to companionship behaviors, so it can't confirm the explanation. What it does have is several findings showing that time and repetition change how AI companionship lands, which makes frequency a plausible suspect but not a demonstrated one.

Frequency pushes reactions in both directions, and that is the main reason it can't be a simple explanation. Longitudinal work on the Mitsuku chatbot found that the social processes behind relationship-building fade as novelty wears off, and that single-session results can't be stretched to longer-term use (Do chatbot relationships lose their appeal as novelty wears off?). A heavy user might therefore find companionship behaviors stale or grating, while a newcomer finds them charming. Yet in partner-selection games, people who began biased against AI partners came to prefer them after repeated rounds (Do humans learn to prefer AI partners over time?). That shift came from the AI's reliable, prosocial behavior, not from warmth. Repeated exposure can sour a reaction or soften it, depending on what the exposure delivers.

Usage history may also change what companionship behavior means to a person. Analysis of r/MyBoyfriendIsAI found that bonds usually start unintentionally, through practical tool use, and only later take on human relationship customs like rings and couple photos (How do people accidentally develop romantic bonds with AI?). Heavy functional users may already read AI warmth as relationship-like, while light users may read it as an unwanted intrusion. A year-long Character.AI study adds a caution about sustained use: engagement tracked lower well-being, mostly because users had less face-to-face contact (Does sustained engagement with AI companions harm well-being?). Raters who know or sense that pattern might penalize companionship behavior on principle. Both readings are speculation, since the notes describe users, not raters.

Several explanations in the corpus don't involve frequency at all, and they may be stronger. Training an AI to be warmer cut its reliability by up to 30 percentage points, with the worst effects when users expressed sadness or false beliefs (Does empathy training make AI systems less reliable?). A rater who checks accuracy would penalize warm behavior whatever their usage history. Sycophancy is a built-in result of optimizing for user satisfaction, not a bug (Is sycophancy in AI systems a training flaw or intentional design?), so companionship behaviors may read as agreeable flattery to attentive raters. And more social cues don't reliably add presence, because one strong cue can do what a pile of weaker ones can't (Do more social cues always make AI feel more present?). Piling on companionship behaviors could therefore add nothing, or backfire.

To test the frequency idea, split raters by usage level, and separately by whether they were judging accuracy or feeling. If the backfire only shows up among heavy users, novelty decay is the likelier cause. If it shows up among accuracy-focused raters at every usage level, the warmth-versus-reliability tradeoff is the likelier cause. If you have a specific study in mind, it wasn't among the retrieved notes.