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We examine how discussing an interpersonal conflict with a sycophantic AI model affects users\\u2019 trust in the AI model, their self-perception in relation to the conflict, their willingness to repair the situation, and their overall evaluation of the AI model and its response quality.\\n\\nThe study is motivated by the increasing use of large language models (LLMs) in advice-giving scenarios, such as moral dilemmas and interpersonal conflicts. In these scenarios, AI models may exhibit sycophantic behavior, which may unduly shape user attitudes and choices.\\n\\nTo test this, we conduct a 2-condition between-subjects experiment in which participants are randomly assigned to one of two conditions: sycophantic or non-sycophantic.\\n\\nWe expect the following:\\nSycophantic responses will increase trust in the model, perceived self-rightness, and perceived response quality, but reduce intent to repair.\\n\\nThe results will contribute to research on human\\u2013AI interaction and responsible design of AI assistants.\"}], \"identifier\": [{\"@value\": \"https://doi.org/10.17605/OSF.IO/WD26Q\"}, {\"@value\": \"https://osf.io/wd26q\"}], \"isVersionOf\": [{\"@id\": \"https://osf.io/smvw7\", \"resourceType\": [{\"@id\": \"Project\"}], \"dateCreated\": [{\"@value\": \"2025-07-03\"}], \"creator\": [{\"@id\": \"https://osf.io/69vzr\", \"resourceType\": [{\"@id\": \"Agent\"}, {\"@id\": \"Person\"}], \"identifier\": [{\"@value\": 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