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Journal Neurocomputers №5 for 2024 г.
Article in number:
On the ethics of artificial intelligence
Type of article: scientific article
DOI: 10.18127/j19998554-202405-02
UDC: 004.8
Authors:

V.A. Shakhnov1, A.V. Proletarsky2, L.A. Zinchenko3, V.V. Kazakov4, V.V. Terekhov5

1–5 Bauman Moscow State Technical University (Moscow, Russia)

1 shakhnov@mail.ru, 2 pav_mipk@mail.ru, 3 lzinchenko@bmstu.ru,

4 samharm777@gmail.com, 5 vterekhov.bmstu@gmail.com

Abstract:

Artificial intelligence, including its machine learning subsection, is increasingly being used in various applications. The paper considers various approaches to machine learning, as well as some possible risks of its application from the point of view of ethics. A review of the latest systems has been carried out. Machine learning and artificial intelligence systems such as text systems ruGPT-3, FRED-T5, InstructGPT, ChatGPT (OpenAI), AI visual systems: ruCLIP, ruDALL-E, Kandinsky 2.1 from Sber, Shedevrum from Yandex and multi modal systems NeONKA (GigaChat), GPT-4 are described. There are also such basic algorithms as XGBoost, CatBoost, transformer architectures such as BERT, and recurrent architectures such as LSTM and GAN networks. The mechanism of Shapley values is described for analyzing machine learning and artificial intelligence systems to introduce greater transparency into the processes taking place in them and the principle of decision-making by such systems. The paper provides an overview of the ethical principles highlighted by the community in the field of artificial intelligence. The developed CognShield software, its tasks and the main structural elements of the user interface are described. An example of software analysis for compliance with the Code of Ethics in the field of Artificial Intelligence is given. In this paper, it is proposed to supplement the list of ethics criteria with the principle of adaptability, implying such behavior of the machine learning system, in which the system, depending on the “degree of confidence of the system in the forecast” (for example, deviations from a given probability threshold in the case of classification), the importance and degree of influence (determined based on the tasks of the machine learning system being developed) of the forecasting by various methods focuses the user on aspects of the interpretation of the result or recommendations for its application.

Pages: 17-29
For citation

Shakhnov V.A., Proletarsky A.V., Zinchenko L.A., Kazakov V.V., Terekhov V.V. On the ethics of artificial intelligence. Neuro-computers. 2024. V. 26. № 5. Р. 17-29. DOI: https://doi.org/10.18127/j19998554-202405-02 (In Russian)

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Date of receipt: 15.01.2024
Approved after review: 06.02.2024
Accepted for publication: 26.09.2024