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postgraduate thesis: The Impact of generative AI on cybercrime
Title | The Impact of generative AI on cybercrime |
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Authors | |
Issue Date | 2024 |
Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
Citation | Chong, W. [莊詠筠], Li, Y. [李雨佳], Xu, R. [徐然]. (2024). The Impact of generative AI on cybercrime. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. |
Abstract | This study aims to explore the role of generative artificial intelligence (AI) in facilitating
cybercrime and its supportive role in regulating crime. We employ a variety of research
methods, including secondary data analysis, news report research, literature review, legal and
regulatory studies, and semi-structured qualitative interviews. Through these methods, this
study analyzes in detail how the emergence of generative AI affects the motivations of
offenders, the likelihood of victimization, and the response strategies of legal regulations
within the framework of Routine Activity Theory. The study also finds that generative AI not
only enhances the technological capabilities and anonymity of offenders but also increases
the risk of victimization for ordinary users. Additionally, it highlights some inherent
problems with the current responses of regulators, such as legislation and platform safeguards,
which need to be addressed immediately. At the same time, from another perspective,
generative AI has shown significant potential in the process of legal regulation and law
enforcement to assist in identifying and preventing criminal behaviors. Based on a
comparative study of numerous AI laws and regulations at both domestic and international
levels, we put forward several recommendations aimed at providing a reference for the
development of future laws and regulations. Moreover, this study innovatively predicts
possible new forms of generative AI in cybercrime in the future, such as the combination of
online and offline crimes. Through a comprehensive analysis, this study not only reveals the
shortcomings of existing regulatory mechanisms but also provides improvement measures to
enhance the law's ability to respond to generative AI-related crimes. This study offers
important insights for criminological and legal academics, policymakers, and law
enforcement agencies. It emphasizes the need for multi-party collaboration to address the
challenges posed by emerging technologies and calls for a closer interaction between
technological evolution and legal supervision.
|
Degree | Master of Social Sciences |
Subject | Computer crimes Artificial intelligence |
Dept/Program | Criminology |
Persistent Identifier | http://hdl.handle.net/10722/352849 |
DC Field | Value | Language |
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dc.contributor.author | Chong, Wing-kwan | - |
dc.contributor.author | 莊詠筠 | - |
dc.contributor.author | Li, Yujia | - |
dc.contributor.author | 李雨佳 | - |
dc.contributor.author | Xu, Ran | - |
dc.contributor.author | 徐然 | - |
dc.date.accessioned | 2025-01-08T06:46:38Z | - |
dc.date.available | 2025-01-08T06:46:38Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | Chong, W. [莊詠筠], Li, Y. [李雨佳], Xu, R. [徐然]. (2024). The Impact of generative AI on cybercrime. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. | - |
dc.identifier.uri | http://hdl.handle.net/10722/352849 | - |
dc.description.abstract | This study aims to explore the role of generative artificial intelligence (AI) in facilitating cybercrime and its supportive role in regulating crime. We employ a variety of research methods, including secondary data analysis, news report research, literature review, legal and regulatory studies, and semi-structured qualitative interviews. Through these methods, this study analyzes in detail how the emergence of generative AI affects the motivations of offenders, the likelihood of victimization, and the response strategies of legal regulations within the framework of Routine Activity Theory. The study also finds that generative AI not only enhances the technological capabilities and anonymity of offenders but also increases the risk of victimization for ordinary users. Additionally, it highlights some inherent problems with the current responses of regulators, such as legislation and platform safeguards, which need to be addressed immediately. At the same time, from another perspective, generative AI has shown significant potential in the process of legal regulation and law enforcement to assist in identifying and preventing criminal behaviors. Based on a comparative study of numerous AI laws and regulations at both domestic and international levels, we put forward several recommendations aimed at providing a reference for the development of future laws and regulations. Moreover, this study innovatively predicts possible new forms of generative AI in cybercrime in the future, such as the combination of online and offline crimes. Through a comprehensive analysis, this study not only reveals the shortcomings of existing regulatory mechanisms but also provides improvement measures to enhance the law's ability to respond to generative AI-related crimes. This study offers important insights for criminological and legal academics, policymakers, and law enforcement agencies. It emphasizes the need for multi-party collaboration to address the challenges posed by emerging technologies and calls for a closer interaction between technological evolution and legal supervision. | - |
dc.language | eng | - |
dc.publisher | The University of Hong Kong (Pokfulam, Hong Kong) | - |
dc.relation.ispartof | HKU Theses Online (HKUTO) | - |
dc.rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works. | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject.lcsh | Computer crimes | - |
dc.subject.lcsh | Artificial intelligence | - |
dc.title | The Impact of generative AI on cybercrime | - |
dc.type | PG_Thesis | - |
dc.description.thesisname | Master of Social Sciences | - |
dc.description.thesislevel | Master | - |
dc.description.thesisdiscipline | Criminology | - |
dc.description.nature | published_or_final_version | - |
dc.date.hkucongregation | 2024 | - |
dc.identifier.mmsid | 991044889208903414 | - |