Behavioral and Perceptual Models for Secure Data Analysis and Management
DOI:
https://doi.org/10.18034/gdeb.v8i2.653Keywords:
Collective Behavior Analysis, Artificial intelligence, Data ModelAbstract
The ability to monitor and forecast citizen behavior on a large scale developed to be a top target for governments subject to security and intelligence that are collective in the current worldwide culture where the web has become the primary medium for commerce and communication. Meanwhile, significant privacy-related issues have surfaced considering the innovative opportunities that artificial intelligence (AI) generates for collective behavior analysis when presented to governments as a way in which the government will comprehend. In the current study, we conducted an extensive literature analysis using techniques such as data mining and interviews such as in-depth to determine the primary uses of Artificial Intelligence that governments use and describe citizens' privacy issues. Our findings showed that the government employed 11 AI initiatives to enhance interactions with residents, local organizations, services offered by government agencies, and the economy, among other things. Issues are identified relating to the risk of behavior modification, intelligent decision-making, data privacy regulation and law, digital surveillance, and decision automation as they pertain to people's privacy when governments deploy AI. Finally, the report concluded that the debate of developing rules centered on the moral citizen data architecture gathering, with consequences for governments aiming to regulate security, morality, and data privacy. We also suggest a study schedule with 16 research questions to be investigated in future studies.
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