Proceedings of the 12th UUM International Legal Conference 2023 (UUMILC 2023)

Properties of artificial intelligence systems in the context of their use in legal activities

Authors
Mukhtar Sadykov1, *, Mohammad Ershadul Karim2, Ane Tynyshbayeva3, Dmitry Bakhteev4
1Academy of Law Enforcement Agencies Under the Prosecutor General’s Office, Astana, Kazakhstan
2Universiti Malaya, Kuala Lumpur, Malaysia
3Academy of Public Administration Under the President of the Republic of Kazakhstan, Astana, Kazakhstan
4Ural State Law University, Yekaterinburg, Russia
*Corresponding author. Email: mukhtar.sadykov@gmail.com
Corresponding Author
Mukhtar Sadykov
Available Online 10 January 2024.
DOI
10.2991/978-94-6463-352-8_12How to use a DOI?
Keywords
artificial intelligence; fairness; accountability; transparency; legal regulation
Abstract

The study was undertaken to reflect on the values of modern artificial intelligence systems in the context of the use of such systems in legal, especially law enforcement activities. The application of artificial intelligence in the research focuses on the properties of fairness, accountability, and transparency. Fairness should exclude distortions in the operation of artificial intelligence systems, caused by the settings of scales or the specifics of the dataset collected for training the system. Accountability is seen as the property of an AI system to protect user data that is included in a dataset or processed by an AI system. Transparency, on the other hand, reflects the ability to verify the decision logic of an AI system and reverse-engineer its algorithm. This property is currently the least attainable, but it is directly related to the evaluation of the effectiveness of AI, and hence to the possibilities of integrating such systems into legal activities. This paper uses the current understanding of the capabilities of systems based on machine learning methods: convolutional artificial neural networks and transformer networks. The study reveals differences and discussions of AI perspectives in legislation and the state of legal regulation, public and academic approaches to this issue in the European Union, the USA, Canada, Singapore, China, Russia, and Kazakhstan. As a result, the study proposes a set of recommendations for banning/restricting the use of artificial intelligence and decision support systems, considering national and international legislation.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 12th UUM International Legal Conference 2023 (UUMILC 2023)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
10 January 2024
ISBN
10.2991/978-94-6463-352-8_12
ISSN
2667-128X
DOI
10.2991/978-94-6463-352-8_12How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Mukhtar Sadykov
AU  - Mohammad Ershadul Karim
AU  - Ane Tynyshbayeva
AU  - Dmitry Bakhteev
PY  - 2024
DA  - 2024/01/10
TI  - Properties of artificial intelligence systems in the context of their use in legal activities
BT  - Proceedings of the 12th UUM International Legal Conference 2023 (UUMILC 2023)
PB  - Atlantis Press
SP  - 156
EP  - 169
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-352-8_12
DO  - 10.2991/978-94-6463-352-8_12
ID  - Sadykov2024
ER  -