09:00 - 10:30
Parallel sessions 4
09:00 - 10:30
Room: HSZ - N2
Chair/s:
Teresa Luther
The increasing integration of artificial intelligence (AI) into everyday life – through local large language models, multimodal assistants, and personalized system designs – raises essential questions about how people perceive, trust, and interact with AI systems over time. This symposium brings together findings from an interdisciplinary longitudinal study investigating the perception and dynamics of human – AI interaction across six measurement points within one year. The project explores how individual characteristics, behavioral responses, and usage contexts jointly shape willingness to delegate to AI – both in writing and decision-making contexts – as well as perceptions of trust, credibility, closeness, and self-efficacy. 
The first contribution presents data from the initial wave of data investigating predictors of individuals’ willingness to delegate writing tasks to AI. The second contribution investigates how trust and related perceptual facets—credibility, creepiness, and mind perception—shape people’s willingness to delegate decision-making to AI systems over time. The third contribution addresses perceived closeness and behavioral intention, examining how perceptions of AI agents as social actors—rather than mere tools—change over time and how these changes relate to feelings of loneliness, perceived intelligence, and behavioral intentions to use AI. The fourth contribution examines how perception of AI as tool or social actor and interaction modality (text vs. voice) shape credibility perceptions. Finally, the fifth contribution examines whether the perception of AI as tool vs. social actor also has consequences for cognitive self-esteem of the user, also over time. 
Together, these studies provide a comprehensive perspective on the evolving relationship between humans and AI. By integrating psychological, social, and technological viewpoints, the symposium offers novel insights into how trust, roles, and self-perceptions adapt to increasingly intelligent and omnipresent AI systems – highlighting implications for user-centered and ethically informed AI design. 
Submission 161
Handing over the Pen? How Perceptions of AI Shape Willingness to Delegate Writing Tasks
SymposiumTalk-01
Presented by: Teresa Luther
Teresa Luther 1, Joachim Kimmerle 1, 2
1 Leibniz-Institut für Wissensmedien Tübingen, Germany
2 Department of Psychology, University of Tübingen, Germany
The widespread adoption of artificial intelligence (AI) is reshaping human-AI collaboration, with AI systems increasingly augmenting human capabilities in automating tasks and optimizing workflows (Langer & Landers, 2019). AI delegation, as a distinct aspect of human-AI collaboration, has the potential to alleviate human effort in time-consuming tasks and enhance efficiency (Westphal et al., 2024). A key question is which factors influence people’s willingness to delegate tasks to AI. Prior research points to user-related and context-related determinants but rarely examined specific task types. Considering recent meta-analytic evidence of performance gains from human-AI synergy in content-creation tasks (Vaccaro et al., 2024) and the increasing use of AI for writing, understanding what influences people’s decisions to delegate tasks to AI in this context is crucial. As part of a longitudinal study on the dynamics of human-AI interaction over time, this contribution presents analyses from the first wave of data collection. Using a US-based online sample (N = 1007), participants indicated their preferred level of AI assistance for eight randomized writing tasks covering personal and professional contexts on a four-point scale, adopted from Lubars and Tan (2019). Multiple linear regressions were performed to identify significant user-, perception-, and task-related predictors of delegation willingness. Findings revealed that perceived trustworthiness and anthropomorphism significantly predicted greater willingness to delegate writing tasks to AI. In contrast, perceiving AI as a social actor or as intelligent did not.