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Empirical Analysis of AI Fraud Crimes and Governance Strategies

Author(s)

Wenbo Fu*, Zhihui Ban

Affiliation(s)

The National Police University for Criminal Justice, Baoding, Hebei, China *Corresponding Author.

Abstract

Artificial Intelligence (AI) has turned science fiction into reality, increasingly coming into public view and influencing and changing people's lives and ways of thinking. The barriers to AI usage are gradually being lowered, which raises the risk of misuse, including legal risks such as "deepfakes," data breaches, and face-swapping infringement. AI fraud has emerged as a significant branch of new types of fraud, characterized by greater intelligence, diverse methods, strong deception, easier trust acquisition, and a higher success rate. This article presents an empirical analysis of 25 cases collected from online and practical sources, examining the incidence, types, and implementation carriers of AI fraud. It discusses the challenges in governing AI fraud crimes and proposes governance strategies. These strategies include improving legislation to enhance the legal adaptability and constraints of AI, ensuring the legal and compliant use of AI technology; cultivating specialized talents at the intersection of AI technology and law; strengthening enforcement efforts and improving investigation and evidence collection methods to combat technology with technology; and facilitating efficient collaboration among various departments and industries to form a united front. Together, we can address AI fraud crimes and protect the property safety and legitimate rights and interests of the public.

Keywords

AI Fraud; Crimes; Empirical Analysis

References

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