The Relationship Between the Degree of AI Cognition and Its Degree of Trust
Research Article
Open Access
CC BY

The Relationship Between the Degree of AI Cognition and Its Degree of Trust

Guanlin Feng 1*
1 Shanghai Starriver Bilingual School, Shanghai, China, 201108
*Corresponding author: fengguanlin2008@gmail.com
Published on 20 July 2025
Volume Cover
TNS Vol.125
ISSN (Print): 2753-8826
ISSN (Online): 2753-8818
ISBN (Print): 978-1-80590-233-1
ISBN (Online): 978-1-80590-234-8
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Abstract

This research explores the relationship between Artificial Intelligence (AI) literacy and trust in AI systems. As AI continues to be integrated into various aspects of daily life, understanding the connection between knowledge of AI and trust is crucial. The study develops a comprehensive AI literacy questionnaire, addressing key dimensions such as "Know and Understand AI," "Use and Apply AI," and "Evaluate and Create AI," alongside questions measuring the degree of trust in AI. The research finds a weak negative relationship between AI literacy and trust, which is different from existing literature that typically suggests a positive or neutral correlation. The results, though not statistically significant, highlight the importance of AI education and its potential role in shaping public trust. Despite limitations such as sample size and time constraints, the study offers valuable insights and contributes to the ongoing dialogue about AI literacy and trust. Future research, with a larger and more diverse sample, could help clarify these findings and further explore the interplay between AI literacy and trust across different populations and settings.

Keywords:

Artificial Intelligence, AI literacy, trust in AI, machine learning, AI education

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Feng,G. (2025). The Relationship Between the Degree of AI Cognition and Its Degree of Trust. Theoretical and Natural Science,125,29-38.

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Cite this article

Feng,G. (2025). The Relationship Between the Degree of AI Cognition and Its Degree of Trust. Theoretical and Natural Science,125,29-38.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of CONF-APMM 2025 Symposium: Multi-Qubit Quantum Communication for Image Transmission over Error Prone Channels

ISBN: 978-1-80590-233-1(Print) / 978-1-80590-234-8(Online)
Editor: Anil Fernando
Conference website: https://2025.confapmm.org/
Conference date: 29 August 2025
Series: Theoretical and Natural Science
Volume number: Vol.125
ISSN: 2753-8818(Print) / 2753-8826(Online)