Does personalization actually build closeness with chatbots?
When users feel closer to AI over time, is that because the system remembers personal details about them, or simply because they've interacted with it repeatedly? This RCT tests whether personalization features drive the relationship gains we observe.
In the same preregistered 5-day RCT (N=992, 4,960 conversations), many of the changes observed over the course of repeated relationship-advice conversations were driven by time in the study rather than by which personalization condition a participant was assigned to. The authors report that "in all conditions, participants perceived the chatbot as increasingly competent and useful over successive sessions, and reported growing closeness to it" — a pattern that held across the non-personalized control, the memory-based condition, and the survey-based condition alike. They state plainly that "several changes in human-AI interaction over time are driven primarily by repeated exposure rather than personalisation itself."
Critically, personalization produced null effects on several outcomes the authors expected it to move: "relative to participants in the control condition, participants in the memory and survey conditions did not experience more closeness to the model over time; they did not accept more incorrect AI suggestions [in a post-study overreliance task]; nor did they self-report greater depth or breadth in their self-disclosures." The authors read this as evidence that closeness and perceived competence are largely functions of session count and familiarity with the interaction format itself, rather than of any personal information the model held about the user.
This runs parallel to Do chatbot relationships lose their appeal as novelty wears off?, which found relationship-formation processes with Mitsuku wore off as novelty faded — both studies treat session number as doing real explanatory work that one-shot designs miss, though in opposite directions: Mitsuku's relational signals declined while this RCT's closeness and competence ratings rose. It also qualifies Does chatbot personalization build trust or expose privacy risks?, which attributes rising trust and closeness over time to personalization's "expectation ratchet" — this RCT's control condition shows the same closeness gains with no personalization at all, suggesting repeated exposure alone, not the ratchet mechanism specifically, may account for a substantial share of that trajectory. See also Does personalization type shape how people feel about sharing? for where personalization's effects, in this same study, were not null.
The excerpt does not report effect sizes or statistical tests for the session-number trends, and the authors explicitly caution that "our study does not support causal claims about the relationship between" perceived closeness and disclosure, proposing cross-lagged panel designs as a future test. The implication the evidence supports is that researchers and designers attributing longitudinal gains in user trust or closeness to personalization specifically should rule out a simpler explanation first: mere repeated exposure to the interaction, independent of what the system remembers or infers about the user.
Inquiring lines that read this note 4
This note is a source for these research framings, grouped by the broader line of inquiry each explores. Scan the bold lines of inquiry; follow any specific question forward.
Does chatbot personalization simultaneously increase both user trust and privacy concerns?- Do personalized chatbots increase both trust and privacy concerns simultaneously?
- Does personalization in chatbots increase trust and privacy concerns simultaneously?
- Does personalization in chatbots increase both trust and privacy concerns simultaneously?
- Why do users trust personalized chatbots even as privacy risks increase?
Related concepts in this collection 4
This note in its neighbourhood — explore the map, then jump to a related concept in the list below.
Click a node to walk · click center to open · click Open in graph to see this note in the full knowledge graph
-
Do chatbot relationships lose their appeal as novelty wears off?
Explores whether the positive social dynamics observed in one-time chatbot studies persist or fade through repeated interactions. Critical for designing systems intended for sustained engagement over weeks or months.
parallel exposure-driven dynamic, opposite direction
-
Does chatbot personalization build trust or expose privacy risks?
Explores whether personalization features that increase user trust and social connection simultaneously heighten privacy concerns and create rising behavioral expectations over time.
this RCT's control-condition gains qualify its personalization-driven "expectation ratchet" account
-
Does personalization type shape how people feel about sharing?
Two personalization strategies—memory-based versus survey-based—produced opposite effects on user comfort and regret. Understanding which approach feels trustworthy versus intrusive matters for AI design.
same study; the implementation-specific effects that were not null
-
Does ChatGPT's memory feature feel like a relationship or a machine?
Users experience ChatGPT's memory as having machine-like qualities yet fostering relationship-building. But what happens when they discover exactly what it remembers about them, and does that discovery match their expectations?
Qualifies A's null personalization effect: B finds revealing ChatGPT's retained memory often triggers negative expectancy violations, undermining closeness
Related papers in this collection 8
Papers most semantically related to this note, ranked by cosine similarity in the embedding space.
- Tailored to you: longitudinal effects of personalising language models
- From speaking like a person to being personal: The effects of personalized, regular interactions with conversational agents
- CompanionSim: Synthetic Data for Evaluating Anthropomorphism in Human-AI Relationships
- Dialoging Resonance: How Users Perceive, Reciprocate and React to Chatbot’s Self-Disclosure in Conversational Recommendations
- How AI and Human Behaviors Shape Psychosocial Effects of Extended Chatbot Use: A Longitudinal Randomized Controlled Study
- Chatbot vs. Human: The Impact of Responsive Conversational Features on Users’ Responses to Chat Advisors
- UX Roundup (28 Sep 2026): Bogus Deskilling Research
- Love in the Age of AI: An Integrative Process Model of Romantic Human-Chatbot Relationships
Original note title
repeated exposure, not personalization, drove perceived closeness and competence gains across a 5-day advice RCT