#AMRG presents: Review of "Understanding Public Perceptions of Artificial Intelligence in China in Relation to Advanced Air Mobility"

What?

This article investigates public perceptions of artificial intelligence (AI) in China's Advanced Air Mobility (AAM) context. The study explores dimensions such as openness, usefulness, actual use, and trust in AI as it applies to AAM. Using survey data from 93 respondents, the research seeks to understand how trust and perception influence public acceptance of AI-driven AAM solutions.

Who?

• Authors: Hong Guan, Hao Liu, Bo Li, Jialin Li, Xinyue Jiang, Jihan Zhang, Yangruijie Yu, and Shuyuan Shi - School of Global Governance and School of Management, Beijing Institute of Technology, China.

Where?

• Published in: Engineering Proceedings (Eng. Proc. 2024, 80, 38).
• Available at: MDPI Journal
• DOI: 10.3390/engproc2024080038

Summary

The study examines public attitudes toward AI in AAM by conducting a survey with a five-point Likert scale. It explores perceptions regarding AI’s openness, usefulness, trustworthiness, and actual use. The authors highlight that while the public views AI use favorably, there are reservations about its openness and usefulness, indicating a level of hesitancy in accepting AI-based AAM technologies.

A correlation analysis reveals strong relationships between openness and usefulness, as well as between trust levels. Trust, openness, and usefulness appear to be intertwined rather than independent factors. A principal component analysis (PCA) was employed to explore underlying dimensions, but it did not yield clear distinctions among trust, openness, and usefulness, suggesting that public perceptions of AI in AAM are complex and interconnected.

Key Findings

• Openness and Usefulness: Respondents showed lower levels of openness to AI-driven AAM, which correlated strongly with perceptions of its usefulness.
• Trust Levels: General trust in AI-driven AAM was moderate, with varying levels of acceptance for fully autonomous versus human-assisted systems.
• Factor Analysis: PCA results showed overlapping dimensions among trust, openness, and usefulness, making it difficult to distinguish distinct factors.
• Demographics: The majority of survey respondents were young adults, highly educated, and predominantly from Beijing and Hunan.

Key Takeaways

1. Public skepticism exists regarding AI's openness and perceived usefulness in AAM.
2. Trust in AI remains moderate, with more confidence in human-assisted systems than in fully autonomous ones.
3. AI use is viewed positively, but it does not strongly influence overall perceptions of AAM adoption.
4. Further research is needed to better understand how to enhance public trust and the perceived usefulness of AI in AAM applications.

Article Rating

Rating: 7.5/10 This article provides valuable insights into public perceptions of AI in AAM, contributing to discussions on AI acceptance in transportation. The research is well-structured, but its limitations include a small sample size (93 respondents) and the inability to extract clear factors from the PCA. A larger, more diverse dataset and further refinement of the survey methodology would enhance the study’s validity. Despite these limitations, the paper effectively highlights the complexities of AI adoption in AAM, making it a relevant reference for future studies.

Brought to you by #AMRG

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