AI outperforms humans in establishing interpersonal closeness in emotionally engaging interactions – but only when labelled as human

AI outperforms humans in establishing interpersonal closeness in emotionally engaging interactions – but only when labelled as human | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article AI outperforms humans in establishing interpersonal closeness in emotionally engaging interactions – but only when labelled as human Tobias Kleinert, Marie Waldschütz, Julian Blau, Markus Heinrichs, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6803722/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Jan, 2026 Read the published version in Communications Psychology → Version 1 posted You are reading this latest preprint version Abstract With the increasing accessibility of large language models to the public, questions arise about whether—and under what conditions—social-emotional interactions with artificial intelligence (AI) can lead to human-like relationship building. Across two double-blind randomized controlled studies with pre-registered analyses, 492 participants engaged in 15-minute online interactions using a modified, text-based version of the ‘Fast Friends Procedure’ (a method designed to enable rapid relationship building), with pre-generated responses by either human partners or a minimally prompted large language model. When labelled as human, the AI outperformed human partners in establishing feelings of closeness during emotionally engaging ‘deep-talk’ interactions. This striking effect appears to stem from the AI’s higher levels of self-disclosure, which in turn enhanced participants’ perceptions of closeness. Labelling the partner as an AI reduced, but did not eliminate, relationship building, likely due to participants’ lower motivation to engage in interactions with an AI, reflected in both shorter responses and reduced feelings of closeness. These findings highlight AI’s potential to relieve overburdened social fields while underscoring the urgent need for ethical safeguards to prevent its misuse in fostering deceptive social connections. To fully harness the benefits of AI in social applications such as psychotherapy and caregiving, it is crucial to promote acceptance of AI interactions in these fields while simultaneously mitigating the risks of misuse. Social science/Psychology/Human behaviour Scientific community and society/Social sciences/Communication Scientific community and society/Social sciences/Psychology/Human behaviour artificial intelligence conversational AI social-emotional interactions relatio building interpersonal closeness Full Text Additional Declarations There is NO Competing Interest. Supplementary Files Kleinertetalsupplements.pdf Supplementary Material KleinertetalReportingSummary.pdf reporting-summary Cite Share Download PDF Status: Published Journal Publication published 14 Jan, 2026 Read the published version in Communications Psychology → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6803722","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":475601979,"identity":"74ccfa8e-7c42-4ee2-b564-5b48739fd4f9","order_by":0,"name":"Tobias 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