ORCID Number
0000-0002-9833-7036
Date of Award
Summer 6-9-2025
Access Type
Dissertation - Open Access
Degree Name
Doctor of Philosophy in Human Factors
Department
Human Factors and Behavioral Neurobiology
Committee Chair
Joseph R. Keebler
Committee Chair Email
keeblerj@erau.edu
First Committee Member
Elizabeth Lazzara
First Committee Member Email
lazzarae@erau.edu
Second Committee Member
Barbara S. Chaparro
Second Committee Member Email
chaparb1@erau.edu
Third Committee Member
Alex Chaparro
Third Committee Member Email
chapara3@erau.edu
Fourth Committee Member
Tara Cohen
Fourth Committee Member Email
tara.cohen@cshs.org
College Dean
Jayathi Raghavan
Abstract
As artificial intelligence (AI) continues to be integrated into collaborative work environments, understanding how humans interact with AI teammates is increasingly important. This study examined how people’s beliefs about who they are working with (whether a teammate is human or AI) can influence teamwork outcomes. Specifically, we explored how perceived teammate identity affects task performance and team experience, with a focus on trust and communication as potential mediators, and AI literacy (familiarity and comfort with AI) as a moderator. Participants completed a series of timed, collaborative problem-solving tasks using a bomb defusal simulation. Each participant worked with both a human and an AI teammate, and some were misled about the identity of their teammate to assess the effects of expectation versus reality. This design allowed us to compare the performance of human-human teams to human-AI teams, while also testing how perceptions may have shaped teamwork dynamics and task performance. Findings revealed that working with a human teammate led to higher task performance outcomes, including less mistakes made and more successful puzzle completion in a shorter amount of time. Additionally, regardless of one’s perceptions of the teammate's identity, participants rated significantly higher team performance scores actually working with a human teammate. Importantly, AI literacy also moderated some of these relationships, meaning participants with high AI literacy reported lower levels of trust in AI teammates and higher levels of trust in human teammates, while participants with low AI literacy exhibited the opposite relationship. Together, these findings highlight that effective human-AI collaboration is influenced not only by the actual performance of AI systems but also by how those systems are perceived. The results offer practical insights for designing AI systems for specific task attributes and contexts, as well as informing training programs and other integration strategies necessary to support the successful collaboration between humans and AI in real-world settings.
Scholarly Commons Citation
Korentsides, Jenna, "Teamwork and Artificial Intelligence (AI) : Examining the Effects of Teammate Identity, Deception, and AI Literacy on Team Dynamics and Performance in Human-Human vs. Human-AI Teams" (2025). Doctoral Dissertations and Master's Theses. 910.
https://commons.erau.edu/edt/910
