Use of artificial intelligence and human chipping in forensic medicine: a review
- Authors: Sadykov M.B.1, Begaliyev Y.N.1, Bakhteev D.V.2, Kaziyeva A.N.3, Khussainov O.B.3
-
Affiliations:
- Academy of Law Enforcement Agencies Under the General Prosecutors Office of the Republic of Kazakhstan
- Ural State Law University named after V.F. Yakovlev
- Abai Kazakh National Pedagogical University
- Issue: Vol 10, No 1 (2024)
- Pages: 88-98
- Section: Reviews
- URL: https://bakhtiniada.ru/2411-8729/article/view/254430
- DOI: https://doi.org/10.17816/fm16093
- ID: 254430
Cite item
Full Text
Abstract
This article outlines some aspects of the use of artificial intelligence and human chipping in forensic medicine.
An overview of the use of artificial intelligence and human chipping in forensic medical examination is provided, as well as a definition of the ethical and legal issues of integrating artificial intelligence and human chipping into forensic medical examination.
This article discusses the work of scientists of Kazakhstan and foreign countries aimed at studying the use of artificial intelligence and human chipping in forensic medical examination. Notably, the greatest application of artificial intelligence systems at this stage of development of science and technology has been found in forensic psychiatry. We noted the lack of research on the use of human microchipping for forensic purposes. In general, studies addressing the synergy between artificial intelligence and human chipping for use in forensic medicine and the legal and ethical aspects of their use in this area are limited.
Considering the generalization of scientific works and analysis of domestic and foreign experience on the issue, we present the ethical and legal aspects of the integration of artificial intelligence and human chipping in forensic medicine. Owing to the lack of sufficient sources in modern scientific literature devoted to the integrated use of artificial intelligence and human chipping in forensic examination as a whole, a SWOT analysis was conducted, which showed that these technologies have some advantages and opportunities regarding efficiency and accuracy.
Based on a study of the literature and practice of using artificial intelligence and human chipping in forensic medicine, legal aspects related to the synergy of artificial intelligence and human chipping have been identified, which can be divided into several key areas: confidentiality and data security, informed consent, ownership, and control.
Furthermore, based on the literature and the practice of using artificial intelligence and human chipping in forensic medicine, legal aspects related to the synergy of artificial intelligence and human chipping were identified, which can be divided into several key areas: respect for autonomy, confidentiality and ethics of data processing, lack of harm, and informed consent.
Full Text
##article.viewOnOriginalSite##About the authors
Mukhtar B. Sadykov
Academy of Law Enforcement Agencies Under the General Prosecutors Office of the Republic of Kazakhstan
Author for correspondence.
Email: mukhtar.sadykov@gmail.com
ORCID iD: 0000-0002-1705-0157
SPIN-code: 2224-4845
Kazakhstan, Koshy
Yernar N. Begaliyev
Academy of Law Enforcement Agencies Under the General Prosecutors Office of the Republic of Kazakhstan
Email: ernar-begaliev@mail.ru
ORCID iD: 0000-0001-6659-8576
SPIN-code: 1929-3392
Dr. Sci. (Legal), Professor
Kazakhstan, KoshyDmitry V. Bakhteev
Ural State Law University named after V.F. Yakovlev
Email: dmitry.bakhteev@gmail.com
ORCID iD: 0000-0002-0869-601X
SPIN-code: 8301-7165
Dr. Sci. (Legal), Associate Professor
Russian Federation, EkaterinburgAssel N. Kaziyeva
Abai Kazakh National Pedagogical University
Email: assel01@mail.ru
ORCID iD: 0000-0002-7734-4667
SPIN-code: 6172-0214
Cand. Sci. (Economic)
Kazakhstan, AlmatyOleg B. Khussainov
Abai Kazakh National Pedagogical University
Email: oleg.khusainov.60@inbox.ru
ORCID iD: 0000-0003-4065-1652
SPIN-code: 8592-4410
Cand. Sci. (Legal)
Kazakhstan, AlmatyReferences
- Fang YT, Lan Q, Xie T, et al. New opportunities and challenges for forensic medicine in the era of artificial intelligence technology. Fa Yi Xue Za Zhi. 2020;36(1):77-85. EDN: TOXTKZ doi: 10.12116/j.issn.1004-5619.2020.01.016
- Kokin AV. Forensic expertise in the era of the fourth industrial revolution (Industry 4.0). Theory Practice Forensic Science. 2021;16(2):29-36. EDN: MEMZCO doi: 10.30764/1819-2785-2021-2-29-36
- Piraianu AI, Fulga A, Musat CL, et al. Enhancing the evidence with algorithms: How artificial intelligence is transforming forensic medicine. Diagnostics. 2023;13(18):2992. doi: 10.3390/diagnostics13182992
- Thurzo A, Kosnáčová HS, Kurilová V, et al. Use of advanced artificial intelligence in forensic medicine, forensic anthropology and clinical anatomy. Healthcare (Basel). 2021;9(11):1545. EDN: RGJPVF doi: 10.3390/healthcare9111545
- Voevodkin DV, Rustemova GR, Begaliev EN, et al. Identifying fake conclusions of forensic medical examinations using an artificial intelligence technology based on the experience in the Republic of Kazakhstan: A review. Russ J Forensic Med. 2023;9(3):287-298. EDN: EFNJIE doi: 10.17816/fm8270
- Lefèvre T. Artificial intelligence in forensic medicine. Living reference work entry. Springer International Publishing; 2021. P. 1-9.
- Tortora L, Meynen G, Bijlsma J, et al. Neuroprediction and A.I. in forensic psychiatry and criminal justice: A neurolaw perspective. Front Psychol. 2020;11:220. doi: 10.3389/fpsyg.2020.00220
- Linthicum KP, Schafer KM, Ribeiro JD. Machine learning in suicide science: Applications and ethics. Behav Sci Law. 2019;37(3):214-222. doi: 10.1002/bsl.2392
- Pigliucci M. The end of theory in science? EMBO Rep. 2009;10(6):534. doi: 10.1038/embor.2009.111
- Fernandes K, Cardoso JS, Astrup BS. A deep learning approach for the forensic evaluation of sexual assault. Pattern Anal Applic. 2018;21:629-640. doi: 10.1007/s10044-018-0694-3
- Tursunov AB, Galitsky FA, Begaliev EN, et al. Forensic and forensic aspects of childhood traumatism as a result of domestic injuries and traffic accidents: A review. Russ J Forensic Med. 2023;9(3):299-308. EDN: ORUBFH doi: 10.17816/fm12389
- Guez S, Laugier V, Saas C, Lefèvre T. L’IA, le légiste et le magistrat: Traitement médicolégal des violences interpersonnelles. In: Julia G., editor. Sciences et sens de l’intelligence artificielle, Thèmes et commentaires. Dalloz; 2020.
- Cantürk I, Özilmaz L. A computational approach to estimate postmortem interval using opacity development of eye for human subjects. Comput Biol Med. 2018;98:93-99. doi: 10.1016/j.compbiomed.2018.04.023
- Abugabah A, Nizamuddin N, Abuqabbeh A. A review of challenges and barriers implementing RFID technology in the Healthcare sector. Procedia Computer Science. 2020;170:1003-1010. doi: 10.1016/j.procs.2020.03.094
- Orakbayev AB, Kurmangali ZhK, Begaliyev YeN, et al. On the issue of using the results of a virtual autopsy in criminal investigation: A review. Russ J Forensic Med. 2023;9(2):183-192. EDN: OEERGD doi: 10.17816/fm774
- Barinov EH, Romanova OL, Sundukov DV, et al. A case of death in a sewer collector. Medical newsletter of Vyatka. 2023;(3):98-101. EDN: KMYMKX doi: 10.24412/2220-7880-2023-3-98-101
- Reardon S. AI-controlled brain implants for mood disorders tested in people. Nature. 2017;551:549-550. doi: 10.1038/nature.2017.23031
- Iqbal F, Debbabi M, Fung BC. Artificial intelligence and digital forensics. In: Machine learning for authorship attribution and cyber forensics. International Series on Computer Entertainment and Media Technology. Springer, Cham; 2020. P. 139-150.
- Gerke S, Minssen T, Cohen G. Ethical and legal challenges of artificial intelligence-driven healthcare. In book: Artificial Intelligence in Healthcare. Academic Press; 2020. С. 295-336. doi: 10.1016/B978-0-12-818438-7.00012-5
- Rawling P. Deontology. Cambridge University Press; 2023. doi: 10.1017/9781108581196
Supplementary files
