AntI-Social Facilitation: Evaluation Apprehension and Performance Mediated by AI
Academic Level at Time of Presentation
Senior
Major
Psychology
Minor
Social & Behavioral Studies
List all Project Mentors & Advisor(s)
Dr. Jana Hackathorn; Dr. Sean Rife
Presentation Format
Poster Presentation
Abstract/Description
Purpose: Social facilitation can be described as the process through which one’s performance is influenced by the presence of others, leading to improvement on simple or well-learned tasks and performance decline on complicated or unfamiliar tasks (Cottrell et al., 1968; Bond & Titus, 1983). Prior research examining AI and social facilitation has been largely relegated to videogames (Anderson-Hanley, 2011), however AI may be less likely to induce social facilitation effects, or induce a smaller effect, than conventional human interaction (Siemon, 2023). Thus, the purpose of this study is to find to what degree social facilitation processes occur between humans and AI in job interviews, a critical part of the human experience where social facilitation effects could be disastrous.
Procedures: First, participants complete a survey measuring their general attitude towards AI (Krageloh et al., 2025) and their trait evaluation apprehension (Leary, 1983). Then, participants participate in an interview wherein there are two conditions one where the participant is told they are interacting with an AI via an online chatroom and one where the participant is told they are interacting with a human via an online chatroom. After which, they will be asked to complete another questionnaire, this time measuring their current evaluation apprehension (Leary, 1983). A perception check will also be conducted, asking the participant if they believed that they were interacting with a human or an AI.
Expected Results: It is hypothesized that participants who are told they are interacting with AI will report lower state evaluation apprehension than participants told they will be interacting with a human. It is also expected that trait evaluation apprehension will work to moderate this relationship, in that low apprehension scores will buffer social facilitation effects, and high scores will exacerbate them. Data collection to occur between November 2025 and March 2026.
Conclusions/Implications: The results of this study could shed new light into a burgeoning field in the development of AI, including the presence of social facilitation during human-AI interactions in the future. As well, the results of this study could work to bolster findings of prior research that found AI in competitive videogame environments produce social facilitation effects.
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Psychology: Projects In-Progress
AntI-Social Facilitation: Evaluation Apprehension and Performance Mediated by AI
Purpose: Social facilitation can be described as the process through which one’s performance is influenced by the presence of others, leading to improvement on simple or well-learned tasks and performance decline on complicated or unfamiliar tasks (Cottrell et al., 1968; Bond & Titus, 1983). Prior research examining AI and social facilitation has been largely relegated to videogames (Anderson-Hanley, 2011), however AI may be less likely to induce social facilitation effects, or induce a smaller effect, than conventional human interaction (Siemon, 2023). Thus, the purpose of this study is to find to what degree social facilitation processes occur between humans and AI in job interviews, a critical part of the human experience where social facilitation effects could be disastrous.
Procedures: First, participants complete a survey measuring their general attitude towards AI (Krageloh et al., 2025) and their trait evaluation apprehension (Leary, 1983). Then, participants participate in an interview wherein there are two conditions one where the participant is told they are interacting with an AI via an online chatroom and one where the participant is told they are interacting with a human via an online chatroom. After which, they will be asked to complete another questionnaire, this time measuring their current evaluation apprehension (Leary, 1983). A perception check will also be conducted, asking the participant if they believed that they were interacting with a human or an AI.
Expected Results: It is hypothesized that participants who are told they are interacting with AI will report lower state evaluation apprehension than participants told they will be interacting with a human. It is also expected that trait evaluation apprehension will work to moderate this relationship, in that low apprehension scores will buffer social facilitation effects, and high scores will exacerbate them. Data collection to occur between November 2025 and March 2026.
Conclusions/Implications: The results of this study could shed new light into a burgeoning field in the development of AI, including the presence of social facilitation during human-AI interactions in the future. As well, the results of this study could work to bolster findings of prior research that found AI in competitive videogame environments produce social facilitation effects.