THE STUDY OF PUBLIC CONCERN REGARDING THE USE OF ARTIFICIAL INTELLIGENCE IN PUBLIC SURVEILLANCE AND SECURITY: A CASE STUDY OF THE BTS AND MRT MASS TRANSIT SYSTEMS
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Abstract
This study aims to (1) assess the level of public concern regarding the use of Artificial Intelligence (AI) for surveillance and security in the BTS and MRT mass transit systems, (2) analyze the factors influencing public concern about AI surveillance, (3) evaluate public opinions on the use of AI for analyzing and processing passenger behavior in mass transit systems, and (4) propose guidelines for developing AI-based surveillance and security systems that align with public needs and privacy expectations. This quantitative research employed a survey as the primary data collection tool. The sample consisted of 500 BTS and MRT passengers selected using stratified sampling. The data were analyzed using descriptive statistics to determine means and standard deviations, as well as correlation analysis and hypothesis testing to examine the factors influencing public concern.
The findings indicate that the public exhibits a high level of concern, particularly regarding privacy and data security, with concern levels averaging between 3.8 and 4.2. Perceived privacy risks were positively correlated with concern levels (r = 0.72, p < 0.01), whereas perceived AI benefits (r = -0.45, p = 0.05) and transparency in data management (r = -0.60, p = 0.02) were negatively correlated with concern levels. Additionally, 85% of respondents supported the need for agencies to disclose policies on data management and privacy protection transparently. The study suggests that AI-based surveillance measures should align with public expectations by emphasizing communication on AI benefits, transparent data management, and adequate privacy safeguards to build public trust in AI surveillance and security systems.
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References
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