Sep 2026· Proceedings of the Human Factors and Ergonomics Society Annual Meeting· 0 citations· 11 references
TL;DR
It is suggested that perceived interaction competence and general evaluative orientation independently contribute to user experience with socially capable AI agents, which have practical implications for the design of AI systems.
Abstract
As socially capable artificial intelligence (AI) rapidly advances in sophistication, prevalence, and ubiquity, it becomes increasingly important to understand how human users perceive AI-generated messages. The present study examined whether users’ AI self-efficacy and attitudes toward AI predict their evaluations of AI-generated text. One hundred ninety-one participants rated 32 GPT-4-generated passages on likeability and perceived informational value, and completed measures of AI self-efficacy and attitudes toward AI. Multiple regression models were used to analyze the self-report data. Results indicated that both trait-level constructs contributed unique variance to each outcome, with AI self-efficacy more closely associated with perceived value and attitudes more closely associated with likeability. These findings suggest that perceived interaction competence and general evaluative orientation independently contribute to user experience with socially capable AI agents, which have practical implications for the design of AI systems.
Artificial intelligence (AI) can be appraised simultaneously as useful, capable, threatening, and demanding. Yet research typically treats attitudes toward AI as a single favorable-unfavorable continuum, obscuring how these evaluations coexist within individuals. Using a three-wave, time-lagged survey of 379 first-year...
Generative artificial intelligence (AI) has rapidly transformed human-computer interaction by adopting conversational and adaptive communication styles. This study examined how generative AI communication style and user attributes influence perception and decision-making during AI assisted interaction. One hundred twen...
Jordayne Wilkins, C. Mayhorn· Proceedings of the Human Fac...· 0 citations
As users increasingly engage with various unfamiliar artificial intelligence (AI) agents, initial impressions become crucial. AI agents’ self-disclosure can play a key role in shaping these impressions. This study aims to conceptualize AI agents’ self-disclosure, identify key user perceptual factors and examine how...
Min-Qian Yang, Pei-Luen Patirck Rau· Information Technology &...· 0 citations
This paper introduces a framework for understanding how generative AI affects user agency, drawing on psychological research distinguishing between expressed preferences and immediate, often-regretted desires. We conducted a study examining how AI usage relates to users’ self-reported capacity for accomplishing goals a...
E. Xing, Ravi Iyer, Rachel Xu et al.· Journal of Online Trust and...· 0 citations
The findings show that AI is not perceived as socially neutral but instead acquires racial meanings associated with credibility, authority, and capability, demonstrating how social categories shape perceptions of novel technological entities beyond their underlying algorithmic properties.
M. Gamez-Djokic, Adam Waytz· Journal of Personality and S...· 0 citations
Abstract Artificial intelligence (AI) is becoming increasingly common for health information seeking, yet many people are still skeptical of its performance. This between‐subjects online experiment tested whether informing readers that a text was produced by AI influenced their ratings in 774 participants. They were ra...
L. König, Maren C. Podszun, Wolfgang Gaissmaier et al.· Applied Psychology: Health a...· 0 citations
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