哈萨克斯坦共和国通过应用人工智能技术检测法医学鉴定虚假结论的经验：科学综述

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本文探讨了专家失误的现有分类、失误责任的衡量标准，以及在法医学活动中应用数理统计和机器学习（以下简称人工智能）来识别专家失误和鉴定虚假结论的法律问题。

我们尝试了制定评价法医专家结论的标准，以确定其关联性、可接受性、可靠性和客观性，以及区分专家失误与故作虚伪和鉴定虚假结论的客观可能性。

对人工智能的使用进行了SWOT分析，以解决在所考虑的领域应用人工智能的问题，从而确定了使用人工智能的优点和缺点。

数理统计和机器学习方法并不是检测检测鉴定虚假结论的通用方法，同时，鉴于这种方法既可能给出假阳性结果，也可能给出假阴性结果，其结果应由独立专家进行验证。此外，为了有效防止伪造事实，作者得出结论，有必要采取综合措施，其中不仅包括发现操纵行为，还包括防止其发生的可能性，以及惩罚肇事者。为此，作者建议对哈萨克斯坦共和国现行法律进行一系列修订和补充。

作者简介

Denis V. Voyevodkin

Academy of Law Enforcement Agencies Under the General Prosecutors Office of the Republic of Kazakhstan

编辑信件的主要联系方式.
Email: voevodkin.denis@gmail.com
ORCID iD: 0000-0002-1763-1808
SPIN 代码: 5512-0338
哈萨克斯坦, Kosshy

Gauhar R. Rustemova

The Almaty Academy of the Ministry of Internal Affairs of the Republic of Kazakhstan

Email: g.rustemova@mail.ru
ORCID iD: 0009-0001-4002-9815
SPIN 代码: 3793-6920

Dr. Sci. (Jurisprud.), Professor

哈萨克斯坦, Almaty

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

Dr. Sci. (Jurisprud.), Professor

哈萨克斯坦, Kosshy

Kussain A. Igembayev

Akimat of Astana

Email: kussain-igembaev@mail.ru
ORCID iD: 0009-0008-9436-7722
哈萨克斯坦, Astana

Zauresh N. Ayupova

Academy of Law Enforcement Agencies Under the General Prosecutors Office of the Republic of Kazakhstan

Email: zauresh.ayupova@bk.ru
ORCID iD: 0009-0005-3152-8531
哈萨克斯坦, Kosshy

参考

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2. Fig. 1. Screenshot of the “Zandylyk” program used in the Republic of Kazakhstan.

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