Survey experiment found regulatory commitment influences willingness to share personal information, highlighting the importance of algorithmic transparency.
The role of government AI relies on the dynamic interaction between public input and AI output, and at the same time brings new privacy concerns. So, is the public willing to provide personal information for processing by government AI? Established studies have not yet discussed this topic in depth. Using technology enactment theory, this study employs a survey experiment to analyse the effects of government regulatory commitment and algorithmic transparency on the public's willingness to share personal information.The findings indicate that although both factors have a significant effect on the public's willingness to share personal information, however,the effect of algorithmic transparency is more nuanced: The public's willingness to share personal information relies more on government regulatory guarantees than on an understanding of the algorithmic decision-making process, and may even be inhibited by the exposure of AI's deep data analytics capabilities, which activates the public's wariness of deep data use. Technology trust is the intermediary factor affecting the public's willingness to share personal information. These insights offer theoretical and policy implications for designing accountable, citizen-centred government AI systems and improving public engagement in data-driven governance.
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Yingwei Wang (2025) studied this question.
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