Large Language Model Use Impact Locus of Control

2025-05-16

AI Summary

This study investigates the psychological impact of AI-augmented writing on individuals’ locus of control, with particular attention to employment status as a moderating factor. A mixed-methods study involving 462 participants—combining quantitative surveys and in-depth interviews—reveals that employed individuals exhibit higher AI dependency and significantly more internalized locus of control, whereas unemployed individuals demonstrate diminished agency and heightened external locus of control. This is the first empirical demonstration that employment status critically moderates the relationship between AI use and perceived control, addressing a key gap in prior AI psychology research, which has largely overlooked socioeconomic context. The findings extend theoretical frameworks on individual differences in human–AI collaboration and provide empirically grounded insights for human-centered AI design, digital inclusion policies, and workplace technology interventions.

Technology Category

• Humans and AI: AI for Accessibility
• Philosophy and Ethics of AI: AI & Jobs/Labor
• Application Domains: Humanities & Computational Social Science

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems

Abstract

As AI tools increasingly shape how we write, they may also quietly reshape how we perceive ourselves. This paper explores the psychological impact of co-writing with AI on people's locus of control. Through an empirical study with 462 participants, we found that employment status plays a critical role in shaping users' reliance on AI and their locus of control. Current results demonstrated that employed participants displayed higher reliance on AI and a shift toward internal control, while unemployed users tended to experience a reduction in personal agency. Through quantitative results and qualitative observations, this study opens a broader conversation about AI's role in shaping personal agency and identity.

Problem

• Explores AI co-writing's impact on locus of control
• Investigates how employment status affects AI reliance
• Examines AI's role in shaping personal agency

Innovation

• Empirical study with 462 participants
• Analyzed AI reliance and locus of control
• Quantitative and qualitative methods combined