Research on the Willingness of Wuhan Residents to Use Face Recognition in the Era of Artificial Intelligence
Based on Principal Component Analysis
- DOI
- 10.2991/978-94-6463-058-9_97How to use a DOI?
- Keywords
- Artificial intelligence; Face recognition; Willingness to use; Principal component analysis
- ABSTRACT
Based on the innovative development of artificial intelligence, face recognition has become one of the most popular topics today, but the technology also has many security risks.The research of residents' willingness to use face recognition products has practical and theoretical significance for the development of face recognition field.Taking Wuhan residents as the research object, 1006 samples were sampled by combining hierarchical sampling and three-stage sampling, and the principal component analysis method was used to dig deeply to analyze the relationship between the basic information of residents and the willingness to use face recognition products.The results show that the user characteristics of face recognition products are significantly different and the willingness to use is affected by many factors.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yihong Xu AU - Yifan Liu AU - Rongxiao Yu PY - 2022 DA - 2022/12/27 TI - Research on the Willingness of Wuhan Residents to Use Face Recognition in the Era of Artificial Intelligence BT - Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022) PB - Atlantis Press SP - 607 EP - 614 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-058-9_97 DO - 10.2991/978-94-6463-058-9_97 ID - Xu2022 ER -