TY - GEN
T1 - The Influence of Education and Self-perceived Tech Savviness on AI Reliance
T2 - 20th International Conference on Foundations of Computer Science and 20th International Conference on Frontiers in Education, held as part of the World Congress in Computer Science, Computer Engineering and Applied Computing
AU - Biswas, Mriganka
AU - Murray, John
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025/4/23
Y1 - 2025/4/23
N2 - The increasing pervasiveness of Artificial Intelligence (AI) within our daily lives necessitates a deeper understanding of how trust shapes our evolving relationship with technology. This mixed-methods study investigates how educational level, self-perceived ‘tech-savviness’, and emotional responses to tech absence, influences individual reliance on, and trust in, AI. Quantitative analysis reveals that individuals who have been in educational institutions for longer periods (e.g. obtained master’s degrees) demonstrate greater trust in AI, leading to stronger reliance, particularly for recommendations scores. Qualitative analysis uncovers a complex interplay between trust, convenience, task-specific trust, and concerns about autonomy. A striking finding is the prevalence of negative emotions, including a sense of “incompleteness,” during tech absence, especially among the tech-savvy group. This highlights how reliance can extend beyond functional utility and become psychologically intertwined with trust, potentially impacting self-perception. These findings challenge traditional models of technology adoption and emphasize the need for frameworks that consider the psychological dimensions of trust in understanding AI reliance. The interplay between education, trust-based reliance, and psychological factors will be crucial for individual adaptability and resilience in an increasingly AI-driven world.
AB - The increasing pervasiveness of Artificial Intelligence (AI) within our daily lives necessitates a deeper understanding of how trust shapes our evolving relationship with technology. This mixed-methods study investigates how educational level, self-perceived ‘tech-savviness’, and emotional responses to tech absence, influences individual reliance on, and trust in, AI. Quantitative analysis reveals that individuals who have been in educational institutions for longer periods (e.g. obtained master’s degrees) demonstrate greater trust in AI, leading to stronger reliance, particularly for recommendations scores. Qualitative analysis uncovers a complex interplay between trust, convenience, task-specific trust, and concerns about autonomy. A striking finding is the prevalence of negative emotions, including a sense of “incompleteness,” during tech absence, especially among the tech-savvy group. This highlights how reliance can extend beyond functional utility and become psychologically intertwined with trust, potentially impacting self-perception. These findings challenge traditional models of technology adoption and emphasize the need for frameworks that consider the psychological dimensions of trust in understanding AI reliance. The interplay between education, trust-based reliance, and psychological factors will be crucial for individual adaptability and resilience in an increasingly AI-driven world.
KW - Adaptability
KW - AI Reliance
KW - Emotional Responses
KW - Psychological Needs
KW - Trust
UR - https://www.scopus.com/pages/publications/105003909161
UR - https://link.springer.com/book/10.1007/978-3-031-85930-4
U2 - 10.1007/978-3-031-85930-4_1
DO - 10.1007/978-3-031-85930-4_1
M3 - Conference contribution
AN - SCOPUS:105003909161
SN - 9783031859298
T3 - Communications in Computer and Information Science
SP - 3
EP - 17
BT - Foundations of Computer Science and Frontiers in Education
A2 - Arabnia, H.R.
A2 - Deligiannidis, Leonidas
A2 - Amirian, Soheyla
A2 - Ghareh Mohammadi, Farid
A2 - Shenavarmasouleh, Farzan
PB - Springer, Cham
Y2 - 22 July 2024 through 25 July 2024
ER -