Chasing Yesterday: Struggle for Digitalization in Serial Violent Crimes Investigation in Russia

Keywords: artificial intelligence, machine learning, serial violent crimes, ViCAP, ViCLAS, data analysis, criminal statistics, databases, state information systems

Abstract

Mirroring the public administration digitalization trend, most Russian law enforcement agencies have either started or intensified digitalisation of their governance, criminal procedure, and operational-investigative activities. However, while setting certain rather ambitious goals, the agents of such changes at times lack, on the one hand, technical and scholar methodological issues and, on the other hand, do not pay the necessary attention to hiring skilled personnel for the divisions concerned. Those issues are especially relevant as Russian science and practice are falling behind already rather obsolete technical means in the field of quantitative analysis of data on serial violent crimes, prevention and countering of which have long been a ‘sore point’ of Russian law enforcement agencies. The author uses phenomenological approaches to the analysis of developmental patterns and digitalization of serial violent crimes investigation. Besides, the historical method and systemic approach to the analysis of regulatory acts, as well as specialised sources containing valuable information about the progress of quantitative research methodology in Russia and abroad, are used. Criminal anthropology approaches to the assessment of relevant behavioural characteristics of serial violent offenders, essential for the dataset creation process, were followed during the analysis of the methodological aspects of data collection and analysis. The records of interviews with attorneys, investigators, and employees of law enforcement higher educational institutions, conducted by the author, were also assessed. Methodological deficiency of databases containing criminological significant information about serial violent crimes, as well as the issue of the divisions responsible for detecting such crimes being under-equipped, were examined in detail in the article. The author is convinced that the system of criminal statistics in Russia is incapable of collecting and analysing quantitative data about crimes. Under such circumstances, it is justifiably questionable whether the introduction of not only artificial intelligence but also quantitative data analysis as a whole in the system of the Ministry of Internal Affairs, Public Prosecutor’s Office, and Investigative Committee of Russia will be productive.

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Author Biography

Egor Denisov, Alexandra Kuznetsova Law Office

Postgraduate Student

References

Aleksandrov A.S. (2011) Seven deadly sins of modern criminalistics. Yuridicheskaya nauka i praktika. Vestnik Nizhegorodskoj akademii MVD Rossii=Legal Studies and Practice. Journal of Nizhny Novgorod Academy of the MIA, vol. 15, no. 2, pp. 277–280 (in Russ.)

Antonyan Yu. M., Bluvstein Yu. D. (1974) Modeling methods in studies of the offender and criminal behaviour. Tutorial. Moscow, 54 p. (in Russ.)

Beauregard E., Martineau M. (2016) The origin of sexual homicide: a review. Crime Psychology Review, vol. 2, no. 1, pp. 80–94.

Bessonov A.A. (2021) The use of artificial intelligence algorithms in the criminalistic study of criminal activity (on the example of serial crimes). Vestnik Universiteta Kutafina=Courier of Kutafin Moscow Law University, vol. 78, no. 2, pp. 45-53 (in Russ.)

Boslaugh S. (2012) Statistics in a nutshell: a desktop quick reference. Gravenstein (Cal.): O’Reilly Media Inc., 591 p.

Brantingham P. J., Brantingham P. L. (1984) Patterns in crime. N.Y.: Macmillan, 403 p.

Brantingham P.J., Brantingham P.L., Andersen M. (2016) The geometry of crime and crime pattern theory. In: Environmental Criminology and Crime Analysis. 2nd ed. R. Wortley, M.Townsley (eds.). N.Y.: Routledge, 380 p.

Canter D. (2017). Criminal psychology. N.Y.: Routledge, 288 p.

Collins C. Dennehy D. et al. (2021) Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management, vol. 60, p. 102383.

Date C. (2019) Database design and relational theory: normal forms and all that jazz. Apress, 470 p.

De Lisi M. (2014) An empirical study of rape in the context of multiple murder. Journal of Forensic Sciences, vol. 59, no. 2, pp. 420–424.

Douglas J., Ressler R., Burgess A., Hartman C. (1986) Criminal profiling from crime scene analysis. Behavioural Science & Law, vol. 4, no. 4,

Douglas J., Burgess A., Burgess A., Ressler R. (1992) Crime classification manual. N.Y.: Lexington Books, 374 p.

Dressel J., Farid H. (2018) The accuracy, fairness, and limits of predicting recidivism. Science Advances, vol. 4, no. 1, p. 5580.

Hegel G. (2017) Science of logic. Objective logic. Moscow: Prime Media, 540 p. (in Russ.)

Howlett J. et al. (1986) Violent criminal apprehension program — VICAP: a progress report. FBI Law Enforcement Bulletin, vol. 55, no.12, pp. 14–22.

Icove D. (1986) Automated crime profiling. FBI Law Enforcement Bulletin, vol. 55, no. 12, pp. 27–30.

Isaenko V.N. (2005) Serial murder investigation. Manual. Moscow: Manuscript, 304 p. (in Russ.)

Ishchenko Ye. P. (2016) Criminalistics and not only: selected works. Moscow: Prospekt, 384 p. (in Russ.)

Isyutin-Fedotkov D.V. (2018) Basics of forensic research of personality. Moscow: Biblio-Globus, 288 p. (in Russ.)

Martin E., Schwarting D., Chase R. (2020) Serial killer connections through cold cases. National Institute of Justice Journal, no. 282, pp. 29–44.

Milovidova M.A. (1994) Forensic registration of criminal action performance methods and its usage in crime combating. Candidate of Juridical Sciences Thesis. Nizhnyi Novgorod, 231 p. (in Russ.)

Netsvetova N.V., Usanov I.V. (2009) Signs of seriality, peculiarities of its detection during investigation of crimes against a person (murders and rapes). Manual. Moscow: Yurlitinform, 104 p. (in Russ.)

Nicora G. et al. (2022) Evaluating point wise reliability of machine learning prediction. Journal of Biomedical Informatics, vol. 127, p. 103996.

Obraztsov V.A (2007) Criminalistics: binary categories. Мoscow: Unity–Dana, 296 p. (in Russ.)

Prorvich V.A. (2017) Identifying, solving, and investigating of interconnected crimes related to land ownership. In: Solution and investigation of serial crimes and cold cases: papers of conference. Moscow: Academy of Investigative Committee, pp. 361–366 (in Russ.)

Protopopov A.L. Investigation of sexual murder. Saint Petersburg: Law Center Press, 224 p. (in Russ.)

Reid S. (2017) Compulsive criminal homicide: A new nosology for serial murder. Aggression and Violent Behaviour, vol. 34, pp. 290–301.

Rosen L. (1995) Creation of the uniform crime report: the role of social science. Social Science History, vol. 19, no. 2, pp. 215–238.

Rossinskaya Ye. R. (2017) Forensic digital data collection during investigation of serial crimes and past crimes. In: Solution and investigation of serial crimes and cold cases. In: Papers of conference. Moscow: Academy of Investigative Committee, pp. 28–33 (in Russ.)

Rossmo D., Rombouts S. (2016) Geographic profiling. In: Environmental Criminology and Crime Analysis. 2nd ed. R. Wortley, M. Townsley (eds.). N.Y.: Routledge, 380 p.

Sheikh H., Prins C., Schrijvers E. (2023) Mission AI. The New System Technology. Cham: Springer, 430 p.

Slobogin C. (2021) Just algorithms: using science to reduce incarceration and inform a jurisprudence of risk. Cambridge: University Press, 169 p.

Sokol V. Yu. (2017) Crisis of domestic forensics. Krasnodar: University, 332 p. (in Russ.)

Sorochinski M., Salfati C. (2017) A Multidimensional Approach to Ascertaining Individual Differentiation and Consistency in Serial Sexual Assault: Is It Time to Redefine and Refine? Journal of Police and Criminal Psychology, vol. 33, issue 2, pp. 63–83.

Sturup J. (2018) Comparing serial homicides to single homicides: A study of prevalence, offender, and offence characteristics in Sweden. Journal of Investigative Psychology and Offender Profiling, vol. 15, pp. 75–89.

Terekhovich V.N., Nimande E.V. (2012) The object of cognition entity in criminalistics. Biblioteka kriminalista=Library of Criminalist, vol. 4, no. 3, pp. 7–13 (in Russ.)

Tolstolutsky V. Yu. (2008) Сonsistent patterns of the criminalistic reflection theory inherent to the subjective phase. Vestnik Nizhegorodskogo universiteta=Courier of Nizhni Novgorod State University, no. 2, pp. 203–209 (in Russ.)

Van Giffen B., Herhausen D., Fahse T. (2022) Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods. Journal of Business Research, vol. 144, pp. 93–106.

Vod’ko N.P. (1996) Why Chykatylo was pursued by law enforcement for so long? Мoscow: Prospekt, 80 p. (in Russ.)

Wilson D. (2018) Algorithmic patrol: the futures of predictive policing. In: Big Data, Crime and Social Control. A. Završnik (ed.). L.: Routledge, pp. 108–128.

Yaksic E., Harrison M. et al. (2021) A heuristic study of the similarities and differences in offender characteristics across potential and successful serial sexual homicide offenders. Behavioral Science & Law, vol. 39, no. 4, pp. 428–449. 43. Yatsutsenko V.V. (2021) Issues and prospects for introduction of digital technologies in the Prosecutor’s Office activities. Aktual’nye problemy rossiyskogo prava=Issues of Russian Law, vol. 16, no. 11, pp. 187–193 (in Russ.)

Zemskova E.N. (2017) Features of crime characteristics of offences in procurement of goods and services to government and local authorities. Moscow: Academy of Investigative Committee, pp. 210–218 (in Russ.)

Zuikov G.G. (1970) Investigation based on modus operandi of a crime. Moscow: Ministry of Interior Higher School, 189 p. (in Russ.)

Published
2023-12-30
How to Cite
DenisovE. (2023). Chasing Yesterday: Struggle for Digitalization in Serial Violent Crimes Investigation in Russia. Legal Issues in the Digital Age, 4(4), 68-91. https://doi.org/10.17323/2713-2749.2023.4.68.91