DOI: 10.56584/1560-8816-2023-4-198-202

УДК 338.242.2

 

АНАЛИТИЧЕСКИЙ ОБЗОР ТЕНДЕНЦИЙ РАЗВИТИЯ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА

 

Никифорова Н. А.,

к.э.н., доц., профессор Кафедры бизнес-аналитики Факультета налогов, аудита и бизнес-анализа, Финансовый университет при Правительстве Российской Федерации, Москва, Россия

 

ANALYTICAL REVIEW OF TRENDS IN THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE

 

Nikiforova N. A.,

Candidate of Economics, Associate Professor, Professor of the Department of Business Analytics, Faculty of Taxes, Audit and Business Analysis, Financial University under the Government of the Russian Federation, Moscow, Russia

 

Аннотация. Исследования и разработки технологий искусственного интеллекта (ИИ) предполагают выбор, выходящий далеко за рамки поиска узких инженерных решений проблем. В статье автор, опираясь на историю ИИ, проводит различие между ограниченным узким искусственным (ANI) и общим искусственным интеллектом (AGI). Обе формы, как утверждается, несут в себе риски. Далее в статье приводятся примеры различных нестабильных и потенциально опасных гонок, происходящих в ИИ, в том числе между различными исследовательскими группами ИИ (государственными и частными), между корпорациями и между государствами, рассматриваются различные тенденции, связанные с ИИ.

Ключевые слова: анализ, развитие искусственного интеллекта, технологии ИИ, финансирование ИИ, концепции

 

Abstract. Research and development of artificial intelligence (AI) technologies presuppose a choice that goes far beyond the search for narrow engineering solutions to problems. In the article, the author, based on the history of AI, distinguishes between limited narrow artificial intelligence (AI) and general artificial intelligence (AGI). Both forms are said to carry risks. The article goes on to provide examples of various unstable and potentially dangerous races taking place in AI, including between various AI research groups (public and private), between corporations and between states, and examines various trends related to AI.

Keywords: analysis, development of artificial intelligence, AI technologies, AI financing, concepts

 

Библиографический список:

1.      Basu M. (2016) South Korea to spend $840 million on AI research, GovInsider, 22 March, available at https://govinsider.asia/smart-gov/south-korea-to-spend-840-million-on-ai-research/ (дата обращения: 23.03.2024).

2.      Bohannon J. (2015) Fears of an AI pioneer, Science, 17 July, available at http://science.science mag.org/ content/349/6245/252.full Bohannon, J. (2015) ‘Fears of an AI pioneer’, Science, 17 July, available at http://science.sciencemag.org/content/349/6245/252.full (дата обращения: 23.03.2024).

3.      Byrnes N. (2017) As Goldman embraces automation, even the masters of the universe are threatened, MIT Technology Review, 7 February, available at https:// www.technologyreview. com/s/603431/as-goldman-embraces-automation-even-the-masters-of-the-universe-are-threatened/ (дата обращения: 23.03.2024).

4.      Crevier D. (1993) AI: The Tumultuous History of the Search for Artificial Intelligence, Basic Books, New York.

5.      D’Orazio D. (2014) Elon Musk says AI is “potentially more dangerous than nukes”, The Verge, 3 August, available at http://www.theverge.com/2014/8/3/5965099/elon-musk-compares-artificial-intelligence-to-nukes (дата обращения: 23.03.2024).

6.      Demura M. (2016) Researchers to develop Japanese-style AI, Nikkei Asian Review, 14 September, available at http://asia.nikkei.com/Tech-Science/Tech/Researchers-to-develop-Japanese-style-AI (дата обращения: 23.03.2024).

7.      Golubev K. (2014) Overview of AI research history in USSR and Ukraine: up-to-date just-in-time knowledge concept in Mercier-Laurent, E. and Boulanger, D. (eds) Artificial Intelligence for Knowledge Management, AI4KM 2012, IFIP Advances in Information and Communication Technology, Springer, Berlin.

8.      Hebb D. (1949) The Organisation of Behavior, Wiley, New York.

9.      Holley P. (2016) Why Stephen Hawking believes the next 100 years may be humanity’s toughest test, Washington Post, 20 January, available at https://www.washingtonpost.com/news/speaking-of-science/wp/2016/01/20/why-stephen-hawking- believes-the-next-100-years-may-be-humanitystoughest-test-yet/ (дата обращения: 23.03.2024).

10.    Krebs J. (2011) Risk, uncertainty and regulation, Philosophical Transactions of the Royal Society A: Maths, Physics, Engineering and Science, 369, 1956, pp.4842–52.

11.    Legg S. and Hutter M. (2007) Universal intelligence: a definition of machine intelligence, Minds & Machines, 17, 4, pp.391–444.

12.    McClaughlin K. (2016) Science is a major plank in China’s new spending plan, Science, 7 March, available at http://www.sciencemag.org/news/2016/03/science-major-plank-china-s-new-spendingplan (дата обращения: 23.03.2024).

13.    McCulloch W. and Pitts, W. (1943) A logical calculus of the ideas immanent in nervous activity, Bulletin of Mathematical Biophysics, 5, pp.115–33.

14.    Nikiforova N., Putikhin Y., Shlychkov D., Frolova V. (2023). Analysis of Ecosystem Business in Strategic Development. In: Polyakov, R. (eds) Ecosystems Without Borders 2023. EcoSystConfKlgtu 2023. Lecture Notes in Networks and Systems, vol 705. Springer, Cham. https://doi.org/10.1007/978-3-031-34329-2_3 (дата обращения: 31.03.2024).

15.    Turing A. (1950) Computing machinery and intelligence, Mind, 59, 236, pp.433–60.

16.    Wynne B.(1992) Misunderstood misunderstanding: social identities and public uptake of science, Public Understanding of Science, 1, 3, pp.281–304.