Large language models in daily life: Users’ perceptions of beneficial assistance and undue reliance

Abstract

Large language models (LLMs), such as ChatGPT and Gemini, have rapidly become an integral part of daily life, driven by their advanced conversational capabilities and versatility. Despite widespread adoption, understanding of users’ perceptions regarding the balance between beneficial assistance and undue reliance on LLMs remains limited. To close this gap, we conducted a qualitative questionnaire study (N = 223) to investigate how users perceive the impact of LLMs on their daily lives. Results indicate that users find beneficial support through significantly enhanced productivity, creativity, learning, cognitive offloading, and quality of work. However, problematic reliance also emerges, leading to self-doubt, concerns on reduced efficiency, diminished skill confidence, guilt, and negative self-perceptions. Nevertheless, many users maintain a balanced perspective, viewing LLMs primarily as helpful tools rather than necessities and employing deliberate usage strategies to retain autonomy and competence. The findings are discussed through the lens of self-determination theory and contribute important insights into how LLM interactions may fulfill or compromise fundamental psychological needs of autonomy, competence, and relatedness. The findings offer implications for designing technologies that optimize user well-being while mitigating negative effects.

Ähnliche Arbeiten