Artificial intelligence for the detection of forensic practitioner errors: a review

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Abstract

The article discusses the opportunities and challenges associated with the use of artificial intelligence analyze and mitigate forensic practitioner errors. The significance of the study is justified by the increasing demands on the accuracy of expert opinions in forensic medicine and the need to minimize errors that can result in erroneous legal judgments. The advancements in technologies such as machine learning, neural networks, and deep learning algorithms are opening up new opportunities to improve the quality of expert work.

A review incorporated a SWOT analysis to assess the advantages and disadvantages of artificial intelligence in forensic practice, along with potential opportunities and risks. The analysis demonstrated that the major advantages of artificial intelligence technologies are associated with high accuracy, stability, response time, and the ability to identify complex data patterns. However, the analysis also identified significant limitations, including the need for high-quality training datasets, significant financial costs, and problems related to the interpretability of artificial intelligence solutions. The identified risks include ethical aspects, information security, and legal limitations.

This review focuses on the analysis of current artificial intelligence solutions for the detection and correction of forensic errors, with particular attention paid to innovative methods that can improve the diagnosis of the mechanism of injury, the identification of the cause of death, and the recognition of inconsistent expert opinions. The article discusses real-life examples of using artificial intelligence technologies in forensic practice, and the prospects for their further integration. The analysis demonstrates the significant potential of artificial intelligence to improve the accuracy and reliability of forensic examinations.

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About the authors

Aigerim K. Bakenova

Academy of Public Administration under the President of the Republic of Kazakhstan

Author for correspondence.
Email: alesina93@gmail.com
ORCID iD: 0009-0007-7813-9175
SPIN-code: 7972-1858
Казахстан, 33а Abay ave, Astana, 010000

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

Казахстан, Koshy

Anna A. Aubakirova

St. Petersburg University of Humanities and Social Sciences

Email: anna_lir@mail.ru
ORCID iD: 0000-0002-6547-0869
SPIN-code: 3074-7383

Dr. Sci. (Legal), Professor

Россия, Saint Petersburg

Dmitry 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

Россия, Ekaterinburg

Larissa K. Kussainova

Karaganda University named on E.A. Buketov

Email: klarisa_777@mail.ru
ORCID iD: 0000-0002-8208-6623
SPIN-code: 5926-1900
Scopus Author ID: 57964019600
ResearcherId: rid66058

Cand. Sci. (Legal), Associate Professor

Казахстан, Karaganda

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