The Potential of Forensic Speech Science to Counteract Crimes Committed Using Generative Artificial Intelligence

The authors research the criminalistic aspects of risks associated with the emergence and spread of a new information technology, namely, generative artificial intelligence used to create various information products quickly and effectively. The assessments of this technology are controversial (especially in view of its potential diverse applications) due to a high public danger of its application in criminal activities or for military purposes. The authors examine the approaches of different researchers to using generative artificial intelligence to commit crimes, present their own position regarding the possible criminal law qualification of such actions, and describe possible directions of improving the legislation. The conducted research allowed the authors to conclude that the risks of damaging public relations protected by the law via the use of generative artificial intelligence are mainly associated with computer-mediated communication. It seems that this technology is most often used to commit crimes through deception and information manipulation, such as fraud, spread of disinformation, involvement into extremist (including terrorist) activities, etc. It is facilitated by the wide possibilities of using artificial intelligence to create various information products: text, audio- and video-recordings, images, software, etc. At the same time, the work of generative artificial intelligence involves a specific mechanism of trace formation and is manifested in the forensically (primarily — diagnostically) relevant features. It is possible to establish these features through the use of criminalistic knowledge and means. It seems that the most relevant current source of the resources providing research support for the law enforcement work is a new special criminalistic theory — criminalistic speech science.

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Publication Details

Journal
Russian Journal of Criminology
Published
2025-03-21
DOI
https://doi.org/10.17150/2500-4255.2025.19(1).96-106
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
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article

The Potential of Forensic Speech Science to Counteract Crimes Committed Using Generative Artificial Intelligence

E. I. Galyashina, К. М. Bogatyrev
Russian Journal of Criminology
Adversarial Robustness in Machine Learning
article

The Potential of Forensic Speech Science to Counteract Crimes Committed Using Generative Artificial Intelligence

E. I. Galyashina, К. М. Bogatyrev
article en

Abstract

The authors research the criminalistic aspects of risks associated with the emergence and spread of a new information technology, namely, generative artificial intelligence used to create various information products quickly and effectively. The assessments of this technology are controversial (especially in view of its potential diverse applications) due to a high public danger of its application in criminal activities or for military purposes. The authors examine the approaches of different researchers to using generative artificial intelligence to commit crimes, present their own position regarding the possible criminal law qualification of such actions, and describe possible directions of improving the legislation. The conducted research allowed the authors to conclude that the risks of damaging public relations protected by the law via the use of generative artificial intelligence are mainly associated with computer-mediated communication. It seems that this technology is most often used to commit crimes through deception and information manipulation, such as fraud, spread of disinformation, involvement into extremist (including terrorist) activities, etc. It is facilitated by the wide possibilities of using artificial intelligence to create various information products: text, audio- and video-recordings, images, software, etc. At the same time, the work of generative artificial intelligence involves a specific mechanism of trace formation and is manifested in the forensically (primarily — diagnostically) relevant features. It is possible to establish these features through the use of criminalistic knowledge and means. It seems that the most relevant current source of the resources providing research support for the law enforcement work is a new special criminalistic theory — criminalistic speech science.

Russian Journal of CriminologyVol. 19(1)
Kutafin Moscow State Law University (RU)
Openalex Percentile: Top 97%
Adversarial Robustness in Machine Learning
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