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Beyond Tools: Understanding How Heavy Users Integrate LLMs into Everyday Tasks and Decision-Making

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arxiv 2502.15395 v2 pith:GTBZ5DOV submitted 2025-02-21 cs.HC

classification cs.HC
keywords llmsusersheavydecision-makingeverydaytasksbeyondfindings
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Large language models (LLMs) are increasingly used for both everyday and specialized tasks. While HCI research focuses on domain-specific applications, little is known about how heavy users integrate LLMs into everyday decision-making. Through qualitative interviews with heavy LLM users (n=7) who employ these systems for both intuitive and analytical thinking tasks, our findings show that participants use LLMs for social validation, self-regulation, and interpersonal guidance, seeking to build self-confidence and optimize cognitive resources. These users viewed LLMs either as rational, consistent entities or average human decision-makers. Our findings suggest that heavy LLM users develop nuanced interaction patterns beyond simple delegation, highlighting the need to reconsider how we study LLM integration in decision-making processes.

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Cited by 2 Pith papers

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    A two-year interview study found generative AI boosted individual speed but did not fix team coordination, while shifting team culture toward efficiency and transparent AI use.

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    cs.HC 2025-08 conditional novelty 4.0 of 10

    A synthesis of the CHI 2025 workshop maps research and design opportunities for understanding, protecting, and augmenting human cognition with generative AI.

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